步行机器人中英文对照外文翻译文献
机器人结构论文中英文对照资料外文翻译文献
中英文对照资料外文翻译文献FEM Optimization for Robot StructureAbstractIn optimal design for robot structures, design models need to he modified and computed repeatedly. Because modifying usually can not automatically be run, it consumes a lot of time. This paper gives a method that uses APDL language of ANSYS 5.5 software to generate an optimal control program, which mike optimal procedure run automatically and optimal efficiency be improved.1）IntroductionIndustrial robot is a kind of machine, which is controlled by computers. Because efficiency and maneuverability are higher than traditional machines, industrial robot is used extensively in industry. For the sake of efficiency and maneuverability, reducing mass and increasing stiffness is more important than traditional machines, in structure design of industrial robot.A lot of methods are used in optimization design of structure. Finite element method is a much effective method. In general, modeling and modifying are manual, which is feasible when model is simple. When model is complicated, optimization time is longer. In the longer optimization time, calculation time is usually very little, a majority of time is used for modeling and modifying. It is key of improving efficiency of structure optimization how to reduce modeling and modifying time.APDL language is an interactive development tool, which is based on ANSYS and is offered to program users. APDL language has typical function of some large computer languages. For example, parameter definition similar to constant and variable definition, branch and loop control, and macro call similar to function and subroutine call, etc. Besides these, it possesses powerful capability of mathematical calculation. The capability of mathematical calculation includes arithmetic calculation, comparison, rounding, and trigonometric function, exponential function and hyperbola function of standard FORTRAN language, etc. By means of APDL language, the data can be read and then calculated, which is in database of ANSYS program, and running process of ANSYS program can be controlled.Fig. 1 shows the main framework of a parallel robot with three bars. When the length of three bars are changed, conjunct end of three bars can follow a given track, where robot hand is installed. Core of top beam is triangle, owing to three bars used in the design, which is showed in Fig.2. Use of three bars makes top beam nonsymmetrical along the plane that is defined by two columns. According to a qualitative analysis from Fig.1, Stiffness values along z-axis are different at three joint locations on the top beam and stiffness at the location between bar 1 and top beam is lowest, which is confirmed by computing results of finite element, too. According to design goal, stiffness difference at three joint locations must he within a given tolerance. In consistent of stiffness will have influence on the motion accuracy of the manipulator under high load, so it is necessary to find the accurate location of top beam along x-axis.To the questions presented above, the general solution is to change the location of the top beam many times, compare the results and eventually find a proper position, The model will be modified according to the last calculating result each time. It is difficult to avoid mistakes if the iterative process is controlled manually and the iterative time is too long. The outer wall and inner rib shapes of the top beam will be changed after the model is modified. To find the appropriate location of top beam, the model needs to be modified repetitiously.Fig. 1 Solution of Original DesignThis paper gives an optimization solution to the position optimization question of the top beam by APDL language of ANSYS program. After the analysis model first founded, the optimization control program can be formed by means of modeling instruction in the log file. The later iterative optimization process can be finished by the optimization control program and do not need manual control. The time spent in modifying the model can be decreased to the ignorable extent. The efficiency of the optimization process is greatly improved.2）Construction of model for analysisThe structure shown in Fig. 1 consists of three parts: two columns, one beam and three driving bars. The columns and beam are joined by the bolts on the first horizontal rib located on top of the columns as shown in Fig.1. Because the driving bars are substituted by equivalentforces on the joint positions, their structure is ignored in the model.The core of the top beam is three joints and a hole with special purpose, which can not be changed. The other parts of the beam may be changed if needed. For the convenience of modeling, the core of the beam is formed into one component. In the process of optimization, only the core position of beam along x axis is changed, that is to say, shape of beam core is not changed. It should be noticed that, in the rest of beam, only shape is changed but the topology is not changed and which can automatically be performed by the control program.Fig.1, six bolts join the beam and two columns. The joint surface can not bear the pull stress in the non-bolt joint positions, in which it is better to set contact elements. When the model includes contact elements, nonlinear iterative calculation will be needed in the process of solution and the computing time will quickly increase. The trial computing result not including contact element shows that the outside of beam bears pulling stress and the inner of beam bears the press stress. Considering the primary analysis object is the joint position stiffness between the top beam and the three driving bars, contact elements may not used, hut constructs the geometry model of joint surface as Fig.2 showing. The upper surface and the undersurface share one key point in bolt-joint positions and the upper surface and the under surface separately possess own key points in no bolt positions. When meshed, one node will be created at shared key point, where columns and beam are joined, and two nodes will be created at non shared key point, where column and beam are separated. On right surface of left column and left surface of right column, according to trial computing result, the structure bears press stress. Therefore, the columns and beam will share all key points, not but at bolts. This can not only omit contact element but also show the characteristic of bolt joining. The joining between the bottoms of the columns and the base are treated as full constraint. Because the main aim of analysis is the stiffness of the top beam, it can be assumed that the joint positions hear the same as load between beam and the three driving bars. The structure is the thin wall cast and simulated by shell element . The thickness of the outside wall of the structure and the rib are not equal, so two groups of real constant should he set. For the convenience of modeling, the two columns are alsoset into another component. The components can create an assembly. In this way, the joint positions between the beam core and columns could he easily selected, in the modifying the model and modifying process can automatically be performed. Analysis model is showed Fig.1. Because model and load are symmetric, computing model is only half. So the total of elements is decreased to 8927 and the total of nodes is decreased to 4341. All elements are triangle.3.）Optimization solutionThe optimization process is essentially a computing and modifying process. The original design is used as initial condition of the iterative process. The ending condition of the process is that stiffness differences of the joint locations between three driving bars and top beam are less than given tolerance or iterative times exceed expected value. Considering the speciality of the question, it is foreseen that the location is existent where stiffness values are equal. If iterative is not convergent, the cause cannot be otherwise than inappropriate displacement increment or deficient iterative times. In order to make the iterative process convergent quickly and efficiently, this paper uses the bisection searching method changing step length to modify the top beam displacement. This method is a little complex but the requirement on the initial condition is relatively mild.The flow chart of optimization as follows:1. Read the beam model data in initial position from backup file;2. Modify the position of beam;3. Solve;4. Read the deform of nodes where beam and three bars are joined;5. Check whether the convergent conditions are satisfied, if not, then continue to modify the beam displacement and return to 3, otherwise, exit the iteration procedure.6. Save the results and then exit.The program's primary control codes and their function commentaries are given in it, of which the detailed modeling instructions are omitted. For the convenience of comparing with the control flow, the necessary notes are added.the flag of the batch file in ANSYSBATCH RESUME, robbak.db, 0read original data from the backupfile robbak,.db/PREP7 enter preprocessordelete the joint part between beam core and columnsmove the core of the beam by one :step lengthapply load and constraint on the geometry meshing thejoint position between beam core and columns FINISH exit the preprocessorISOLU enter solverSOLVE solveFINISH exit the solverPOST1 enter the postprocessor*GET ,front,NODE,2013,U,Z read the deformation of first joint node on beam*GET,back,NODE, 1441 ,U,Z read the deformation of second joint node on beam intoparameter hacklastdif-1 the absolute of initial difference between front and hacklast timeflag=- 1 the feasibility flag of the optimizationstep=0.05 the initial displacement from initial position to the currentposition*D0,1,1,10,1 the iteration procedure begin, the cycle variable is I andits value range is 1-10 and step length is 1dif=abs(front-back) the absolute of the difference between front and hack inthe current result*IF,dif,LE,l .OE-6,THEN check whether the absolute difference dif satisfies therequest or noflag=l yes, set flag equal to 1*EXIT exit the iterative calculation*ELSEIF,dif,GE,lastdif,THEN check whether the dif value becomes great or not flag=2yes, set flag 2 modify step length by bisection methodperform the next iterative calculation, use the lastposition as the current position and modified last steplength as the current step lengthELSE if the absolute of difference value is not less thanexpected value and become small gradually, continue tomove top beam read the initial condition from back upfile enter the preprocessorMEN, ,P51X, , , step,, , ,1 move the core of the beam by one step length modify thejoint positions between beam core and column applyload and constraint meshingFINISH exit preprocessorISOLU enter solverSOLVE solveFINISH exit the solver/POST1 exit the postprocessor*GET,front,NODE,201 3,U,Z read the deformation of first joint node to parameter front *GET,back,NODE, 144 1,U,Z read the deformation of second joint node to parameter back lastdif-dif update the value of last dif*ENDIF the end of the if-else*ENDDO the end of the DO cycleMost of the control program above is copied from log file, which is long. The total of lines is up to about 1000 lines. Many codes such as modeling and post-process codes are used repeatedly. To make the program construct clear, these instructions can he made into macros, which are called by main program. This can efficiently reduce the length of the main program. In addition, modeling instructions from log file includes lots of special instructions that are only used under graphic mode but useless under hatch mode. Deleting and modifying these instructions when under batch mode in ANSYS can reduce the length of the file, too.In the program above, the deformation at given position is read from node deformation. In meshing, in order to avoid generating had elements, triangle mesh is used. In optimization, the shape of joint position between columns and beam continually is changed. This makes total of elements different after meshing each time and then element numbering different, too. Data read from database according to node numbering might not he data to want. Therefore, beam core first needs to he meshed, then saved. When read next time, its numbering is the same as last time.Evaluating whether the final result is a feasible result or not needs to check the flag value. If only the flag value is I, the result is feasible, otherwise the most proper position is not found. The total displacement of top beam is saved in parameter step. If the result is feasible, the step value is the distance from initial position to the most proper position. The sum of iterative is saved in parameter 1. According to the final value of I, feasibility of analysis result and correctness of initial condition can he evaluated.4）Optimization resultsThe sum of iterative in optimization is seven, and it takes about 2 hour and 37 minutes to find optimal position. Fig.3 shows the deformation contour of the half-construct. In Fig.3, the deformations in three joints between beam and the three driving bars is the same as level, and the corresponding deformation range is between -0.133E-04 and -0.1 15E-O4m, the requirement of the same stiffness is reached. At this time, the position of beam core along x-axis as shown in Fig. 1 has moved -0.71E-01m compared with the original designed positionBecause the speed of computer reading instruction is much faster than modifying model manually, the time modifying model can be ignored. The time necessary foroptimization mostly depends on the time of solution. Compared with the optimization procedure manually modifying model, the efficiency is improved and mistake operating in modeling is avoided.5）ConclusionThe analyzing result reveals that the optimization method given in this paper is effective and reaches the expected goal. The first advantage of this method is that manual mistakes do not easily occur in optimization procedure. Secondly, it is pretty universal and the control codes given in this paper may he transplanted to use in similar structure optimization design without large modification. The disadvantage is that the topology structure of the optimization object can not be changed. The more the workload of modifying the model, the more the advantages of this method are shown. In addition, the topology optimization function provided in ANSYS is usedto solve the optimization problem that needs to change the topology structure.The better optimization results can he achieved if the method in this paper combined with it.中文译文：机器人机构优化设计有限元分析摘要机器人结构最优化设计，设计模型需要反复的修正和计算。
机械工程及自动化专业外文翻译--可以行走、翻身并站立的有两手和两足的机器人
外文原文：Two-Armed Bipedal Robot that can Walk, Roll Over and Stand upMasayuki INABA, Fumio KANEHIROSatoshi KAGAMI, Hirochika INOUEDepartment of Mechano-InformaticsThe University of Tokyo7-3-l Hongo, Bunkyo-ku, 113 Tokyo, JAPANAbstractFocusing attention on flexibility and intelligent reactivity in the real world, it is more important to build, not a robot that won’t fall down, but a robot that can get up if it does full down. This paper presents a research on a two-armed bipedal robot, an apelike robot, which can perform biped walking, rolling over and standing up. The robot consists of a head, two arms, and two legs. The control system of the biped robot is designed based on the remote-brained approach in which a robot does not bring its own brain within the body and talks with it by radio links. This remote-brained approach enables a robot to have both a heavy brain with powerful computation and a lightweight body with multiple joints. The robot can keep balance in standing using tracking vision, detectwhether it falls down or not by a set of vertical sensors, and perform getting up motion colaborating two arms and two legs. The developed system and experimental results are described with illustrated real examples.1 IntroductionAs human children show, it is indispensable to have capability of getting up motion in order to learn biped locomotion. In order to build a robot which tries to learn biped walking automatically, the body should be designed to have structures to support getting up as well as sensors to know whether it lays or not.When a biped robot has arms, it can perform various behaviors as well as walking. Research on biped walking robots has presented with realization[1][2][3].It has mainly focused on the dynamics in walking,treating it as an advanced problem in control[3][4][5].However, focusing attention on the intelligent reactivity in the real world, it is more important to build, not a robot that won’t fall down, but a robot that can get up if it does fall down.In order to build a robot that can get up if it falls down, the robot needs sensing system to keep the body balance and to know whether it falls down or not. Although vision is one ofthe most important sensing functions of a robot, it is hard to build a robot with a powerful vision system on its own body because of the size and power limitation of a vision system. If we want to advance research on vision-based robot behaviors requiring dynamic reactions and intelligent reasoning based on experience, the robot body has to be lightweight enough to react quickly and have many DOFS in actuation to show a variety of intelligent behaviors.As for the legged robot [6] [7] [8],there is only a little research on vision-based behaviors[9]. The difficulties in advancing experimental research for vision-based legged robots are caused by the limitation of the vision hardware. It is hard to keep developing advanced vision software in limited hardware. In order to solve the problems and advance the study of vision-based behaviors, we have adopted a new approach through building remote-brained robots. The body and the brain are connected by wireless links by using wireless cameras and remote-controlled actuators.As a robot body does not need computers on-board,it becomes easier to build a lightweight body with many DOFS in actuation.In this research, we developed a two-armed bipedal robot using the remote-brained robot environment and made it toperform balancing based on vision and getting up through cooperating arms and legs. The system and experimental results are described below.2 The Remote-Brained SystemThe remote-brained robot does not bring its own brainwithin the body. It leaves the brain in the mother environment and communicates with it by radio links. This allows us to build a robot with a free body and a heavy brain. The connection link between the body and the brain defines the interface between software and hardware. Bodies are designed to suit each research project and task. This enables us advance in performing research with a variety of real robot systems[10].A major advantage of remote-brained robots is that the robot can have a large and heavy brain based on super parallel computers. Although hardware technology for vision has advanced and produced powerful compact vision systems, the size of the hardware is still large. Wireless connection between the camera and the vision processor has been a research tool. The remote-brained approach allows us to progress in the study of a variety of experimental issues in vision-based robotics.Another advantage of remote-brained approach is that the robot bodies can be lightweight. This opens up the possibility of working with legged mobile robots. As with animals, if a robot has 4 limbs it can walk. We are focusing on vision-based adaptive behaviors of 4-limbed robots,mechanical animals, experimenting in a field as yet not much studied.The brain is raised in the mother environment in-herited over generations. The brain and the mother environment can be shared with newly designed robots. A developer using the environment can concentrate on the functional design of a brain. For robots where the brain is raised in a mother environment, it can benefit directly from the mother’s ‘evolution’,meaning that the software gains power easily when the mother is upgraded to a more powerful computer. Figure 1 shows the configuration of the remote-brained system which consists of brain base, robot body and brain-body interface.In the remote-brained approach the design and theperformance of the interface between brain and body is the key. Our current implementation adopts a fully remotely brained approach, which means the body has no computer onboard. Current system consists of the vision subsystems, the non-vision sensor subsystem and the motion control subsystem. A block can receive video signals from cameras on robot bodies. The vision subsystems are parallel sets each consisting of eight vision boards.A body just has a receiver for motion instruction signals and a transmitter for sensor signals. The sensor information is transmitted from a video transmitter. It is possible to transmit other sensor information such as touch and servo error through the video transmitter by integrating the signals into a video image[11]. The actuator is a geared module which includes an analog servo circuit and receives a posit.ion reference value from the motion receiver. The motion control subsystem can handle up to 104 actuators through 13 wave bands and send the reference values to all the actuators every 20msec.3 The Two-Armed Bipedal RobotFigure 2 shows the structure of the two-armed bipedal robot. The main electric components of the robot are joint servo actuators, control signal receivers, an orientation sensor with transmitter, a battery set for actuators and sensors sensor and a camera with video transmitter. There is no computer on-board. A servo actuator includes a geared motor and analog servo circuit in the box. The control signal to each servo module is position reference. The torque of servo modules available cover 2Kgcm - 14Kgcm with the speed about 0.2sec/60deg. The control signal transmitted onradio link encodes eight reference values. The robot in figure 2 has two receiver modules onboard to control 16 actuators.Figure 3 explains the orientation sensor using a set of vertical switches. The vertical switch is a mercury switch. When the mercury switch (a) is tilted, the drop of mercury closes the contact between the two electrodes. The orientation sensor mount two mercury switches such as shown in (b). The switches provides two bits signal to detect four orientation of the sensor as shown in (c). The robot has this sensor at its chest and it can distinguish four orientation; face up, face down, standing and upside down.The body structure is designed and simulated in the mother environment. The kinematic model of the body is described in an object-oriented lisp, Euslisp which has enabled us to describe the geometric solid model and window interface for behavior design.Figure 4 shows some of the classes in the programming environent for remote-brained robot written in Euslisp. The hierachy in the classes provides us with rich facilities for extending development of various robots.4 Vision-Based BalancingThe robot can stand up on two legs. As it can change the gravity center of its body by controling the ankle angles, it can perform static bipedal walks. During static walking the robot has to control its body balance if the ground is not flat and stable.In order to perform vision-based balancing it is re-quired to have high speed vision system to keep ob-serving moving schene. We have developed a tracking vision board using a correlation chip[l3]. The vision board consists of a transputer augmented with a special LSI chip(MEP[14]: Motion Estimation Processor) which performs local image block matching.The inputs to the processor MEP are an image as a reference block and an image for a search window.The size of the reference block is up to 16 by 16 pixels.The size of the search window depends on the size of the reference block is usually up to 32 by 32 pixels so that it can include 16 * 16 possible matches. The processor calculates 256 values of SAD (sum of absolute difference) between the reference block and 256 blocks in the search window and also finds the best matching block, that is, the one which has the minimumSAD value.Block matching is very powerful when the target moves only in translation. However, the ordinary block matching method cannot track the target when it rotates. In order to overcome this difficulty, we developed a new method which follows up the candidate templates to real rotation of the target. The rotated template method first generates all the rotated target images in advance, and several adequate candidates of the reference template are selected and matched is tracking the scene in the front view. It remembers the vertical orientation of an object as the reference for visual tracking and generates several rotated images of the reference image. If the vision tracks the reference object using the rotated images, it can measures the body rotation. In order to keep the body balance, the robot feedback controls its body rotation to control the center of the body gravity. The rotational visual tracker[l5] can track the image at video rate.5 Biped WalkingIf a bipedal robot can control the center of gravity freely, itcan perform biped walk. As the robot shown in Figure 2 has the degrees to left and right directions at the ankle position, it can perform bipedal walking in static way.The motion sequence of one cycle in biped walking consists of eight phases as shown in Figure 6. One step consists of four phases; move-gravity-center-on-foot,lift-leg, move-forward-leg, place-leg. As the body is described in solid model, the robot can generate a body configuration for move-gravity-center-on-foot according to the parameter of the hight of the gravity center. After this movement, the robot can lift the other leg and move it forward. In lifting leg, the robot has to control the configuration in order to keep the center of gravity above the supporting foot. As the stability in balance depends on the hight of the gravity center, the robot selects suitable angles of the knees.Figure 7 shows a sequence of experiments of the robot in biped walking.6 Rolling Over and Standing UpFigure 8 shows the sequence of rolling over, sitting and standing up. This motion requires coordination between arms and legs.As the robot foot consists of a battery, the robot can make use of the weight of the battery for the roll-over motion. When the robot throws up the left leg and moves the left arm back and the right arm forward, it can get rotary moment aroundthe body. If the body starts turning, the right leg moves back and the left foot returns its position to lie on the face. This rollover motion changes the body orientation from face up to face down. It can be verified by the orientation sensor.After getting face down orientation, the robot moves the arms down to sit on two feet. This motion causes slip movement between hands and the ground. If the length of the arm is not enough to carry the center of gravity of the body onto feet, this sitting motion requires dynamic pushing motion by arms. The standing motion is controlled in order to keep the balance.7 Integration through Building Sensor-Based Transition NetIn order to integrate the basic actions described above, we adopted a method to describe a sensor-based transition network in which transition is considered according to sensor status. Figure 9 shows a state transition diagram of the robot which integrates basic actions: biped walking, rolling over, sitting, and standing up. This integration provides the robot with capability of keeping walking even when it falls down. The ordinary biped walk is composed by taking two states, Left-leg Fore and Right-leg Fore, successively.The poses in ‘Lie on the Back’ and ‘Lie on the Face’are as same as one in ‘Stand’. That is, the shape ofthe robot body is same but the orientation is different.The robot can detect whether the robot lies on the back or the face using the orientation sensor. When the robot detects falls down, it changes the state to ‘Lie on the Back’ or ‘Lie on the Front’ by moving to the neutral pose. If the robot gets up from ‘Lie on the Back’, the motion sequence is planned to execute Roll-over, Sit and Stand-up motions. If the state is ‘Lie on the Face’, it does not execute Roll-over but moves arms up to perform the sitting motion.8 Concluding RemarksThis paper has presented a two-armed bipedal robot whichcan perform statically biped walk, rolling over and standing up motions. The key to build such behaviors is the remote-brained approach. As the experiments have shown, wireless technologies permit robot bodies free movement. It also seems to change the way we conceptualize robotics. In our laboratory it has enabled the development of a new research environment, better suited to robotics and real-world AI.The robot presented here is a legged robot. As legged locomotion requires dynamic visual feedback control, its vision-based behaviors can prove the effectiveness of the vision system and the remote-brained system. Our vision system is based on high speed block matching function implemented with motion estimation LSI. The vision system provides the mechanical bodies with dynamic and adaptive capabilities in interaction with human. The mechanical dog has shown adaptive behaviors based on distance measurement by tracking. The mechanical ape has shown tracking and memory based visual functions and their integration in interactive behaviors.The research with a two-armed bipedal robot provides us with a new field in intelligent robotics research because of itsvariety of the possible behaviors created from the flexiblility of the body. The remote-brained approach will support learning-based behaviors in this research field. The next tasks in this research include how to learn from human actions and how to allow the robots to improve their own learned behaviors.References[1] I. Kate and H. Tsuik. The hydraulically powered biped walking machine with a high carrying capacity. In Proc. Of 4th Int. Sys. on External Control of Human Extremities,1972.[2] H. Miura and I. Shimoyama. Dynamic walk of a biped. International Journal of Robotics Research, Vol. 3, No. 2,pp. 60-74, 1984.[3] S. Kawamura, T. Kawamura, D. fijino, F. Miyazaki, and S. Arimoto. Realization of biped locomotion by motion pattern learning. Journal of the Robotics Society of Japan,Vol. 3, No. 3, pp. 177-187, 1985.[4] Jessica K. Hodgins and Marc H. Raibert.Biped gymnastics.International Journal of Robotics Research, Vol. 9,No. 2, pp. 115-132, 1990.[5] A. Takanishi, M. Ishida, Y. Yamazaki, and I. Kato. The realization of dynamic walking by the biped walking robotwl-lord. Journal of the Robotics Society of Japan, Vol. 3, No. 4, pp. 325-336, 1985.[6] R.B. McGhee and G.I. Iswandhi. Adaptive locomotion of a multilegged robot over rough terrain. IEEE Trans.On Systems, Man and Cybernetics,Vol.SMC-9,No.4,pp. 176-182,1979.[7] M. H. Raibert, Jr. H. B. Brown, and S. S. Murthy. 3-d balance using 2-d algorithms. Robotics Research : the First International Symposium on Robotics Research (ISRRI),pp. 279-301, 1983.[8] S. Hirose, M. Nose, H. Kikuchi, and Y. Umetani. Adaptive gait control of a quadruped walking vehicle. Robotics Research : the First International Symposium on Robotics Research (ISRRI), pp. 253-369, 1983.[9] R.B. McGhee, F. Ozguner, and S.J. Tsai. Rough terrain locomotion by a hexapod robot using a binocular ranging system. Robotics Research:the First International Symposium on Robotics Research (ISRR1),pp.228-251, 1984.[10] M. Inaba. Remote-Brained Robotics: Interfacing AI with Real World Behaviors. in Proceedings of the 6th International Symposium 1993; Robotics Research: The SixthInternational Symposium,pp.335-344.International Foundation for Robotics Research, 1993.[11] M. Inaba, S. Kagami, K. Sakakki, F. Kanehiro, and H. In-oue.Vision-Based Multisensor Integration in Remote- Brained Robots. In 1994 IEEE International Conference on Multisensor Fusion and Integration fo Intelligent Systems,pp. 747-754, 1994.[I2] M. Inaba, T. Kamada, and H. Inoue. Rope Handling by Mobile Hand-Eye Robots. In Proceedings of International Conference on Advanced Robotics ICAR’93,pp. 121-126,1993.[13] H. Inoue, T. Tachikawa, and M. Inaba. Robot vision system with a correlation chip for real-time tracking, optical flow and depth map generation. In Proceedings of the 1992 IEEE International Conference on Robotics and Automation,pp. 1621-1626. 1992.[14] SGS-THOMSON Microelectronics. STI3220 motion estimation processor (tentative data). In Image Processing Data Book, pp. 115-138. SGS-THOMSON Microelectronics, 1990.[15] Masayuki Inaba, Satoshi Kagami, and Hirochika Inoue. Real time vision-based control in sumo playing robot. InProceedings of the 1993 JSME International Conference on Advanced Mechatronics, pp.854-859,1993.中文译文：可以行走、翻身并站立的有两手和两足的机器人摘要在实践中把注意力集中在灵活性和智能反应，更重要的是创想，不是一个不会倒下的机器人，而是一个倒下来可以站起来的机器人。
机械手臂外文文献翻译、中英文翻译、外文翻译
外文出处：《Manufacturing Engineering and Technology—Machining》附件1：外文原文ManipulatorRobot developed in recent decades as high-tech automated production equipment. I ndustrial robot is an important branch of industrial robots. It features can be program med to perform tasks in a variety of expectations, in both structure and performance a dvantages of their own people and machines, in particular, reflects the people's intellig ence and adaptability. The accuracy of robot operations and a variety of environments the ability to complete the work in the field of national economy and there are broad p rospects for development. With the development of industrial automation, there has be en CNC machining center, it is in reducing labor intensity, while greatly improved lab or productivity. However, the upper and lower common in CNC machining processes material, usually still use manual or traditional relay-controlled semi-automatic device . The former time-consuming and labor intensive, inefficient; the latter due to design c omplexity, require more relays, wiring complexity, vulnerability to body vibration inte rference, while the existence of poor reliability, fault more maintenance problems and other issues. Programmable Logic Controller PLC-controlled robot control system for materials up and down movement is simple, circuit design is reasonable, with a stron g anti-jamming capability, ensuring the system's reliability, reduced maintenance rate, and improve work efficiency. Robot technology related to mechanics, mechanics, elec trical hydraulic technology, automatic control technology, sensor technology and com puter technology and other fields of science, is a cross-disciplinary integrated technol ogy.First, an overview of industrial manipulatorRobot is a kind of positioning control can be automated and can be re-programmed to change in multi-functional machine, which has multiple degrees of freedom can be used to carry an object in order to complete the work in different environments. Low wages in China, plastic products industry, although still a labor-intensive, mechanical hand use has become increasingly popular. Electronics and automotive industries thatEurope and the United States multinational companies very early in their factories in China, the introduction of automated production. But now the changes are those found in industrial-intensive South China, East China's coastal areas, local plastic processin g plants have also emerged in mechanical watches began to become increasingly inter ested in, because they have to face a high turnover rate of workers, as well as for the workers to pay work-related injuries fee challenges.With the rapid development of China's industrial production, especially the reform and opening up after the rapid increase in the degree of automation to achieve the wor kpiece handling, steering, transmission or operation of brazing, spray gun, wrenches a nd other tools for processing and assembly operations since, which has more and mor e attracted our attention. Robot is to imitate the manual part of the action, according to a given program, track and requirements for automatic capture, handling or operation of the automatic mechanical devices.In real life, you will find this a problem. In the machine shop, the processing of part s loading time is not annoying, and labor productivity is not high, the cost of producti on major, and sometimes man-made incidents will occur, resulting in processing were injured. Think about what could replace it with the processing time of a tour as long a s there are a few people, and can operate 24 hours saturated human right? The answer is yes, but the robot can come to replace it.Production of mechanical hand can increase the automation level of production and labor productivity; can reduce labor intensity, ensuring product quality, to achieve saf e production; particularly in the high-temperature, high pressure, low temperature, lo w pressure, dust, explosive, toxic and radioactive gases such as poor environment can replace the normal working people. Here I would like to think of designing a robot to be used in actual production.Why would a robot designed to provide a pneumatic power: pneumatic robot refers to the compressed air as power source-driven robot. With pressure-driven and other en ergy-driven comparison have the following advantages: 1. Air inexhaustible, used late r discharged into the atmosphere, does not require recycling and disposal, do not pollu te the environment. (Concept of environmental protection) 2. Air stick is small, the pipeline pressure loss is small (typically less than asphalt gas path pressure drop of one-thousandth), to facilitate long-distance transport. 3. Compressed air of the working pre ssure is low (usually 4 to 8 kg / per square centimeter), and therefore moving the mate rial components and manufacturing accuracy requirements can be lowered. 4. With th e hydraulic transmission, compared to its faster action and reaction, which is one of th e advantages pneumatic outstanding. 5. The air cleaner media, it will not degenerate, n ot easy to plug the pipeline. But there are also places where it fly in the ointment: 1. A s the compressibility of air, resulting in poor aerodynamic stability of the work, resulti ng in the implementing agencies as the precision of the velocity and not easily control led. 2. As the use of low atmospheric pressure, the output power can not be too large; i n order to increase the output power is bound to the structure of the entire pneumatic s ystem size increased.With pneumatic drive and compare with other energy sources drive has the followin g advantages:Air inexhaustible, used later discharged into the atmosphere, without recycling and disposal, do not pollute the environment. Accidental or a small amount of leakage wo uld not be a serious impact on production. Viscosity of air is small, the pipeline pressu re loss also is very small, easy long-distance transport.The lower working pressure of compressed air, pneumatic components and therefor e the material and manufacturing accuracy requirements can be lowered. In general, re ciprocating thrust in 1 to 2 tons pneumatic economy is better.Compared with the hydraulic transmission, and its faster action and reaction, which is one of the outstanding merits of pneumatic.Clean air medium, it will not degenerate, not easy to plug the pipeline. It can be saf ely used in flammable, explosive and the dust big occasions. Also easy to realize auto matic overload protection.Second, the composition, mechanical handRobot in the form of a variety of forms, some relatively simple, some more complic ated, but the basic form is the same as the composition of the , Usually by the implem enting agencies, transmission systems, control systems and auxiliary devices composed.1.Implementing agenciesManipulator executing agency by the hands, wrists, arms, pillars. Hands are crawlin g institutions, is used to clamp and release the workpiece, and similar to human finger s, to complete the staffing of similar actions. Wrist and fingers and the arm connecting the components can be up and down, left, and rotary movement. A simple mechanical hand can not wrist. Pillars used to support the arm can also be made mobile as needed .2. TransmissionThe actuator to be achieved by the transmission system. Sub-transmission system c ommonly used manipulator mechanical transmission, hydraulic transmission, pneuma tic and electric power transmission and other drive several forms.3. Control SystemManipulator control system's main role is to control the robot according to certain p rocedures, direction, position, speed of action, a simple mechanical hand is generally not set up a dedicated control system, using only trip switches, relays, control valves a nd circuits can be achieved dynamic drive system control, so that implementing agenc ies according to the requirements of action. Action will have to use complex program mable robot controller, the micro-computer control.Three, mechanical hand classification and characteristicsRobots are generally divided into three categories: the first is the general machinery does not require manual hand. It is an independent not affiliated with a particular host device. It can be programmed according to the needs of the task to complete the oper ation of the provisions. It is characterized with ordinary mechanical performance, also has general machinery, memory, intelligence ternary machinery. The second category is the need to manually do it, called the operation of aircraft. It originated in the atom, military industry, first through the operation of machines to complete a particular job, and later developed to operate using radio signals to carry out detecting machines suc h as the Moon. Used in industrial manipulator also fall into this category. The third cat egory is dedicated manipulator, the main subsidiary of the automatic machines or automatic lines, to solve the machine up and down the workpiece material and delivery. T his mechanical hand in foreign countries known as the "Mechanical Hand", which is t he host of services, from the host-driven; exception of a few outside the working proc edures are generally fixed, and therefore special.Main features:First, mechanical hand (the upper and lower material robot, assembly robot, handlin g robot, stacking robot, help robot, vacuum handling machines, vacuum suction crane, labor-saving spreader, pneumatic balancer, etc.).Second, cantilever cranes (cantilever crane, electric chain hoist crane, air balance th e hanging, etc.)Third, rail-type transport system (hanging rail, light rail, single girder cranes, doubl e-beam crane)Four, industrial machinery, application of handManipulator in the mechanization and automation of the production process develo ped a new type of device. In recent years, as electronic technology, especially comput er extensive use of robot development and production of high-tech fields has become a rapidly developed a new technology, which further promoted the development of ro bot, allowing robot to better achieved with the combination of mechanization and auto mation.Although the robot is not as flexible as staff, but it has to the continuous duplication of work and labor, I do not know fatigue, not afraid of danger, the power snatch weig ht characteristics when compared with manual large, therefore, mechanical hand has b een of great importance to many sectors, and increasingly has been applied widely, for example:(1) Machining the workpiece loading and unloading, especially in the automatic lat he, combination machine tool use is more common.(2) In the assembly operations are widely used in the electronics industry, it can be used to assemble printed circuit boards, in the machinery industry It can be used to ass emble parts and components.(3) The working conditions may be poor, monotonous, repetitive easy to sub-fatigue working environment to replace human labor.(4) May be in dangerous situations, such as military goods handling, dangerous go ods and hazardous materials removal and so on..(5) Universe and ocean development.(6), military engineering and biomedical research and testing.Help mechanical hands: also known as the balancer, balance suspended, labor-saving spreader, manual Transfer machine is a kind of weightlessness of manual load system, a novel, time-saving technology for material handling operations booster equipment, belonging to kinds of non-standard design of series products. Customer application ne eds, creating customized cases. Manual operation of a simulation of the automatic ma chinery, it can be a fixed program draws ﹑ handling objects or perform household to ols to accomplish certain specific actions. Application of robot can replace the people engaged in monotonous ﹑ repetitive or heavy manual labor, the mechanization and a utomation of production, instead of people in hazardous environments manual operati on, improving working conditions and ensure personal safety. The late 20th century, 4 0, the United States atomic energy experiments, the first use of radioactive material ha ndling robot, human robot in a safe room to manipulate various operations and experi mentation. 50 years later, manipulator and gradually extended to industrial production sector, for the temperatures, polluted areas, and loading and unloading to take place t he work piece material, but also as an auxiliary device in automatic machine tools, ma chine tools, automatic production lines and processing center applications, the comple tion of the upper and lower material, or From the library take place knife knife and so on according to fixed procedures for the replacement operation. Robot body mainly b y the hand and sports institutions. Agencies with the use of hands and operation of obj ects of different occasions, often there are clamping ﹑ support and adsorption type of care. Movement organs are generally hydraulic pneumatic ﹑﹑ electrical device dri vers. Manipulator can be achieved independently retractable ﹑ rotation and lifting m ovements, generally 2 to 3 degrees of freedom. Robots are widely used in metallurgic al industry, machinery manufacture, light industry and atomic energy sectors.Can mimic some of the staff and arm motor function, a fixd procedure for the capture, handling objects or operating tools, automatic operation device. It can replace hum an labor in order to achieve the production of heavy mechanization and automation th at can operate in hazardous environments to protect the personal safety, which is wide ly used in machinery manufacturing, metallurgy, electronics, light industry and nuclea r power sectors. Mechanical hand tools or other equipment commonly used for additio nal devices, such as the automatic machines or automatic production line handling an d transmission of the workpiece, the replacement of cutting tools in machining centers , etc. generally do not have a separate control device. Some operating devices require direct manipulation by humans; such as the atomic energy sector performs household hazardous materials used in the master-slave manipulator is also often referred to as m echanical hand.Manipulator mainly by hand and sports institutions. Task of hand is holding the wor kpiece (or tool) components, according to grasping objects by shape, size, weight, mat erial and operational requirements of a variety of structural forms, such as clamp type, type and adsorption-based care such as holding. Sports organizations, so that the com pletion of a variety of hand rotation (swing), mobile or compound movements to achie ve the required action, to change the location of objects by grasping and posture. Robot is the automated production of a kind used in the process of crawling and mo ving piece features automatic device, which is mechanized and automated production process developed a new type of device. In recent years, as electronic technology, esp ecially computer extensive use of robot development and production of high-tech fiel ds has become a rapidly developed a new technology, which further promoted the dev elopment of robot, allowing robot to better achieved with the combination of mechani zation and automation. Robot can replace humans completed the risk of duplication of boring work, to reduce human labor intensity and improve labor productivity. Manipu lator has been applied more and more widely, in the machinery industry, it can be use d for parts assembly, work piece handling, loading and unloading, particularly in the a utomation of CNC machine tools, modular machine tools more commonly used. At pr esent, the robot has developed into a FMS flexible manufacturing systems and flexibl e manufacturing cell in an important component of the FMC. The machine tool equipment and machinery in hand together constitute a flexible manufacturing system or a f lexible manufacturing cell, it was adapted to small and medium volume production, y ou can save a huge amount of the work piece conveyor device, compact, and adaptabl e. When the work piece changes, flexible production system is very easy to change wi ll help enterprises to continuously update the marketable variety, improve product qua lity, and better adapt to market competition. At present, China's industrial robot techno logy and its engineering application level and comparable to foreign countries there is a certain distance, application and industrialization of the size of the low level of robo t research and development of a direct impact on raising the level of automation in Ch ina, from the economy, technical considerations are very necessary. Therefore, the stu dy of mechanical hand design is very meaningful.附件1：外文资料翻译译文机械手机械手是近几十年发展起来的一种高科技自动化生产设备。
机器人类外文文献翻译穿越深渊的机器人中英文翻译、外文翻译
英文原文The Abyss Transit System- James Cameron commissions the making of robots for a return to theTitanicBy Gary StixAt the beginning of the movie that made Leonardo DiCaprio a megastar, a camera-toting unmanned robot ventured into a cavernous hole in the wreck that sits on the bottom of the Atlantic, 12,640 feet from the surface. The 500-pound vehicle, christened Snoop Dog, could move only about 30 feet along a lower deck, hampered by its bulky two-inch-diameter tether hitched to a submarine that waited above. The amount of thrust needed to move its chunky frame stirred up a thick cloud. “The vehicle very quickly silted out the entire place and made imaging impossible,” director James Cameron recalls.But the eerie vista revealed by Snoop Dog on that 1995 expedition made Cameron hunger for more. He vowed to return one day with technology that could negotiate anyplace within the Titanic's interior.In the past six months two documentaries—one for IMAX movie theaters called Ghosts of the Abyss, the other, Expedition: Bismarck, for the DiscoveryChannel—demonstrated the fruits of a three-year effort that Cameron financed with $1.8 million of his own money to make this vision materialize. The payoff was two 70-pound robots, named after Blues Brothers Jake and Elwood, that had the full run of two of the world's most famous wrecks, the Titanic and the Bismarck, which they visited on separate expeditions.The person who took Jake and Elwood from dream to robot is Mike Cameron, James's brother, an aerospace engineer who once designed missiles and who also possesses a diverse background as a helicopter pilot, stunt photographer and stuntman. (Remember the corpse in the movie The Abyss, from whose mouth a crab emerges?) Giving the remotely operated vehicles freedom of movement required that they be much smaller than Snoop Dog and that the tether's width be tapered dramatically so as not to catch on vertical ship beams.Mike Cameron took inspiration from the wire-guided torpedoes used by the military that can travel for many miles. His team created vehicles operable to more than 20,000 feet (enough to reach as much as 85 percent of the ocean floor). The dimensions of the front of the robot are 16 inches high by 17 inches across, small enough to fit in a B deck window of the Titanic. The bots have an internal battery so that they do not need to be powered through a tether. Instead the tether—fifty-thousandths of an inch in diameter—contains optical fibers that relaycontrol signals from a manned submersible vehicle hovering outside and that also send video images in the other direction. The tether pays out from the robot, a design that prevents it from snagging on objects in the wreck.James Cameron thought the project would be a straightforward engineering task, not much harder than designing a new camera system. “This turned out to be a whole different order of magnitude,” he says. “There was no commercial off-the-shelf hardware that wo uld work in the vehicles. Everything had to be built from scratch.” If the team had known this early on, he added, “we wouldn't have bothered.” Water pressure on the cable that carried the optical fibers could create microscopic bends in the data pipe, completely cutting off the control signals from the submersibles. Dark Matter in Valencia, Calif. (Mike Cameron's company), had to devise a fluid-filled sheath around the fiber to displace the minuscule air pockets in the cable that could lead to the microbending.To save weight, the frame—similar to a monocoque body of a race car—was made up of small glass hollow spheres contained in an epoxy matrix. The thruster contained a large-diameter, slowly rotating blade with nozzles that diffused the propulsive flow, minimizing the churning that would otherwise disturb the caked silt.A high-resolution video camera, along with an infrared camera for navigation, was placed in the front of the craft along with three light-emitting-diode arrays for fill lighting and two quartz halogen lamps for spotlighting.The winter of 2001 marked a critical juncture. It was six months before dives to the Titanic could be safely attempted, and James had to determine whether to proceed or wait another year. “Mike was really, really negative on the idea, but I decided to go for it,” the director says. He felt he couldn't afford to wait longer and thought that a fixed deadline would focus the engineering staff at Dark Matter. Forhis part, Mike was contending with an unending series of design challenges. “It was such an overwhelming set of problems that I had very little confidence that certain parts would be solvable in the time we had,” Mike says.A few weeks before the dives commenced in the summer of 2001, the robots' lithium sulfur dioxode-based batteries caught fire while being tested in a pressure tank, destroying what was to have been a third robot. Mike wanted to delay the dives, but James found a supplier of another type of lithium battery and pressed ahead.At the dive site, Jake and Elwood took starring roles with their 2,000-foot tethers, exploring for the first time in about 90 years remote parts of the ships, including the engine room, the firemen's mess hall and the cabins of first-class passengers—even focusing in on a bowler hat, a brass headboard and an intact, upright glass decanter. The images lack the resolution and novel quality of the high-definition, three-dimensional IMAX images, the other major technological innovation of Ghostsof the Abyss. Jake and Elwood's discoveries, however, draw the viewers' interest because of what they convey of the Titanic's mystique. “You actually feel like you're out there in the wreck,” Mike says. He remembers his brother piloting the robots with the helicopter stick that had been installed in the Russian submersible from which the robots were launched. “Jim ended up being a cowboy pilot,” Mike says. “He was far more aggressive with the system than I was.”One scene in Ghosts of the Abyss reveals the tension that sometimes erupted between the brothers. James contemplates moving one of the robots through a cabin window that is still partially occluded by a shard of glass that could damage the vehicle or cut the data tether. When James declares that he is going to take Jake in, moviegoers can hear Mike pleading with his brother not to do it, ultimately relenting once the bot has negotiated the opening.The decision to install a new type of battery at the last minute came to haunt the expedition; Elwood's lithium-polymer battery ignited while in the bowels of the ship. James manipulated the remaining robot into the Titanic to perform a rescue operation by hooking a cord to the grill of the dead bot and towing it out. At the surface—on the deck of the Russian scientific vessel the Keldysh, from which the two submarines carrying Jake and Elwood to the Titanic were launched—Mike rebuilt Elwood with a backup battery. During the next dive, the robot caught fire again while it was still mounted on the submarine, endangering the crew. Finally, Mike worked for an 18-hour stretch to adapt a lead-acid gel battery used for devices onboard the mother ship into a power source for Elwood, enabling the expedition to continue.The bots, now fitted with a new, nonflammable battery that Mike designed, may find service beyond motion pictures. The U.S. Navy has funded Dark Matter to help it assess the technology for underwater recovery operations of ships or aircraft. The bots also have potential for scientific exploration of deep-sea trenches. After traveling to the Titanic and the Bismarck, the team went on to probe mid-Atlantic hydrothermal vents, discovering mollusks in a place where scientists had never encountered them before. As adventure aficionados, the brothers speculate that a descendant of Jake and Elwood might even be toted on a mission to Europa, one of Jupiter's moons, to investigate the waters that are suspected to exist below its icy shell. The Cameron siblings, who tinkered with home-built rafts and rockets as children in Ontario near Niagara Falls, hope to be around long enough to witness their robotic twins go from the bottom of the ocean to the depths of space.中文译文穿越深渊的机器--新型的机器人可在数百公尺深的水底残骸间自由穿梭游览作者╱斯蒂克斯( Gary Stix )曾一举捧红超级巨星李奥纳多狄卡皮欧的电影「铁达尼号」中，片头是一台无人驾驶的遥控装置，携带着摄影机深入大西洋，在3852公尺深的铁达尼号残骸里冒险的画面。
机器人外文文献翻译、中英文翻译
外文资料robotThe industrial robot is a tool that is used in the manufacturing environment to increase productivity. It can be used to do routine and tedious assembly line jobs，or it can perform jobs that might be hazardous to the human worker . For example ，one of the first industrial robot was used to replace the nuclear fuel rods in nuclear power plants. A human doing this job might be exposed to harmful amounts of radiation. The industrial robot can also operate on the assembly line，putting together small components，such as placing electronic components on a printed circuit board. Thus，the human worker can be relieved of the routine operation of this tedious task. Robots can also be programmed to defuse bombs，to serve the handicapped，and to perform functions in numerous applications in our society.The robot can be thought of as a machine that will move an end-of-tool ，sensor ，and/or gripper to a preprogrammed location. When the robot arrives at this location，it will perform some sort of task .This task could be welding，sealing，machine loading ，machine unloading，or a host of assembly jobs. Generally，this work can be accomplished without the involvement of a human being，except for programming and for turning the system on and off.The basic terminology of robotic systems is introduced in the following:1. A robot is a reprogrammable ，multifunctional manipulator designed to move parts，material，tool，or special devices through variable programmed motions for the performance of a variety of different task. This basic definition leads to other definitions，presented in the following paragraphs，that give acomplete picture of a robotic system.2. Preprogrammed locations are paths that the robot must follow to accomplish work，At some of these locations，the robot will stop and perform some operation ，such as assembly of parts，spray painting ，or welding .These preprogrammed locations are stored in the robot’s memory and are recalled later for continuousoperation.Furthermore，these preprogrammed locations，as well as other program data，can be changed later as the work requirements change.Thus，with regard to this programming feature，an industrial robot is very much like a computer ，where data can be stoned and later recalled and edited.3. The manipulator is the arm of the robot .It allows the robot to bend，reach，and twist.This movement is provided by the manipulator’s axes，also called the degrees of freedom of the robot .A robot can have from 3 to 16 axes.The term degrees of freedom will always relate to the number of axes found on a robot.4. The tooling and frippers are not part the robotic system itself;rather，they are attachments that fit on the end of the robot’s arm. These attachments connected to the end of the robot’s arm allow the robot to lift parts，spot-weld ，paint，arc-weld，drill，deburr，and do a variety of tasks，depending on what is required of the robot.5. The robotic system can control the work cell of the operating robot.The work cell of the robot is the total environment in which the robot must perform itstask.Included within this cell may be the controller ，the robot manipulator ，a work table ，safety features，or a conveyor.All the equipment that is required in order for the robot to do its job is included in the work cell .In addition，signals from outside devices can communicate with the robot to tell the robot when it should parts，pick up parts，or unload parts to a conveyor.The robotic system has three basic components: the manipulator，the controller，and the power source.A.ManipulatorThe manipulator ，which does the physical work of the robotic system，consists of two sections:the mechanical section and the attached appendage.The manipulator also has a base to which the appendages are attached.Fig.1 illustrates the connectionof the base and the appendage of a robot.图1.Basic components of a robot’s manipulatorThe base of the manipulator is usually fixed to the floor of the work area. Sometimes，though，the base may be movable. In this case，the base is attached to either a rail or a track，allowing the manipulator to be moved from one location to anther.As mentioned previously ，the appendage extends from the base of the robot. The appendage is the arm of the robot. It can be either a straight ，movable arm or a jointed arm. The jointed arm is also known as an articulated arm.The appendages of the robot manipulator give the manipulator its various axes of motion. These axes are attached to a fixed base ，which，in turn，is secured to a mounting. This mounting ensures that the manipulator will in one location.At the end of the arm ，a wrist（see Fig 2）is connected. The wrist is made up of additional axes and a wrist flange. The wrist flange allows the robot user to connect different tooling to the wrist for different jobs.图2.Elements of a work cell from the topThe manipulator’s axes allow it to perform work within a certain area. The area is called the work cell of the robot ，and its size corresponds to the size of the manipulator.（Fid2）illustrates the work cell of a typical assembly ro bot.As the robot’s physical size increases，the size of the work cell must also increase.The movement of the manipulator is controlled by actuator，or drive systems.The actuator，or drive systems，allows the various axes to move within the work cell. The drive system can use electric，hydraulic，or pneumatic power.The energy developed by the drive system is converted to mechanical power by various mechanical power systems.The drive systems are coupled through mechanical linkages.These linkages，in turn，drive the different axes of the robot.The mechanical linkages may be composed of chain，gear，and ball screws.B.ControllerThe controller in the robotic system is the heart of the operation .The controller stores preprogrammed information for later recall，controls peripheral devices，and communicates with computers within the plant for constant updates in production.The controller is used to control the robot manipulator’s movements as well as to control peripheral components within the work cell. The user can program the movements of the manipulator into the controller through the use of a hard-held teach pendant.This information is stored in the memory of the controller for later recall.The controller stores all program data for the robotic system.It can store several differentprograms，and any of these programs can be edited.The controller is also required to communicate with peripheral equipment within the work cell. For example，the controller has an input line that identifies when a machining operation is completed.When the machine cycle is completed，the input line turn on telling the controller to position the manipulator so that it can pick up the finished part.Then ，a new part is picked up by the manipulator and placed into the machine.Next，the controller signals the machine to start operation.The controller can be made from mechanically operated drums that step through a sequence of events.This type of controller operates with a very simple robotic system.The controllers found on the majority of robotic systems are more complex devices and represent state-of-the-art eletronoics.That is，they are microprocessor-operated.these microprocessors are either 8-bit，16-bit，or 32-bit processors.this power allows the controller to be very flexible in its operation.The controller can send electric signals over communication lines that allow it to talk with the various axes of the manipulator. This two-way communication between the robot manipulator and the controller maintains a constant update of the end the operation of the system.The controller also controls any tooling placed on the end of the robot’s wrist.The controller also has the job of communicating with the different plant computers. The communication link establishes the robot as part a computer-assisted manufacturing （CAM）system.As the basic definition stated，the robot is a reprogrammable，multifunctional manipulator.Therefore，the controller must contain some of memory stage. The microprocessor-based systems operates in conjunction with solid-state devices.These memory devices may be magnetic bubbles，random-access memory，floppy disks，or magnetic tape.Each memory storage device stores program information fir or for editing.C.power supplyThe power supply is the unit that supplies power to the controller and the manipulator. The type of power are delivered to the robotic system. One type of power is the AC power for operation of the controller. The other type of power isused for driving the various axes of the manipulator. For example，if the robot manipulator is controlled by hydraulic or pneumatic drives，control signals are sent to these devices causing motion of the robot.For each robotic system，power is required to operate the manipulator .This power can be developed from either a hydraulic power source，a pneumatic power source，or an electric power source.There power sources are part of the total components of the robotic work cell.中文翻译机器人工业机器人是在生产环境中用以提高生产效率的工具，它能做常规乏味的装配线工作，或能做那些对于工人来说是危险的工作，例如，第一代工业机器人是用来在核电站中更换核燃料棒，如果人去做这项工作，将会遭受有害放射线的辐射。
机器人外文翻译外文翻译、中英文翻译、外文文献翻译
外文翻译机器人The robot性质: □毕业设计□毕业论文教学院：机电工程学院系别：机械设计制造及其自动化学生学号：学生姓名：专业班级：指导教师：职称：起止日期：机器人1.机器人的作用机器人是高级整合控制论、机械电子、计算机、材料和仿生学的产物。
在工业、医学、农业、建筑业甚至军事等领域中均有重要用途。
现在，国际上对机器人的概念已经逐渐趋近一致。
一般说来，人们都可以接受这种说法，即机器人是靠自身动力和控制能力来实现各种功能的一种机器。
联合国标准化组织采纳了美国机器人协会给机器人下的定义：“一种可编程和多功能的，用来搬运材料、零件、工具的操作机；或是为了执行不同的任务而具有可改变和可编程动作的专门系统。
2.能力评价标准机器人能力的评价标准包括：智能，指感觉和感知，包括记忆、运算、比较、鉴别、判断、决策、学习和逻辑推理等；机能，指变通性、通用性或空间占有性等；物理能，指力、速度、连续运行能力、可靠性、联用性、寿命等。
因此，可以说机器人是具有生物功能的三维空间坐标机器。
3.机器人的组成机器人一般由执行机构、驱动装置、检测装置和控制系统等组成。
执行机构即机器人本体，其臂部一般采用空间开链连杆机构，其中的运动副（转动副或移动副）常称为关节，关节个数通常即为机器人的自由度数。
根据关节配置型式和运动坐标形式的不同，机器人执行机构可分为直角坐标式、圆柱坐标式、极坐标式和关节坐标式等类型。
出于拟人化的考虑，常将机器人本体的有关部位分别称为基座、腰部、臂部、腕部、手部（夹持器或末端执行器）和行走部（对于移动机器人）等。
驱动装置是驱使执行机构运动的机构，按照控制系统发出的指令信号，借助于动力元件使机器人进行动作。
它输入的是电信号，输出的是线、角位移量。
机器人使用的驱动装置主要是电力驱动装置，如步进电机、伺服电机等，此外也有采用液压、气动等驱动装置。
检测装置的作用是实时检测机器人的运动及工作情况，根据需要反馈给控制系统，与设定信息进行比较后，对执行机构进行调整，以保证机器人的动作符合预定的要求。
关于现代工业机械手外文文献翻译@中英文翻译@外文翻译
附录About Modenr Industrial Manipulayor Robot is a type of mechantronics equipment which synthesizes the last research achievement of engine and precision engine, micro-electronics and computer, automation control and drive, sensor and message dispose and artificial intelligence and so on. With the development of economic and the demand for automation control, robot technology is developed quickly and all types of the robots products are come into being. The practicality use of robot not only solves the problems which are difficult to operate for human being, but also advances the industrial automation program. Modern industrial robots are true marvels of engineering. A robot the size of a person can easily carry a load over one hundred pounds and move it very quickly with a repeatability of 0.006inches. Furthermore these robots can do that 24hours a day for years on end with no failures whatsoever. Though they are reprogrammable, in many applications they are programmed once and then repeat that exact same task for years.At present, the research and development of robot involves several kinds of technology and the robot system configuration is so complex that the cost at large is high which to a certain extent limit the robot abroad use. To development economic practicality and high reliability robot system will be value to robot social application and economy development. With he rapidprogress with the control economy and expanding of the modern cities, the let of sewage is increasing quickly; with the development of modern technology and the enhancement of consciousness about environment reserve, more and more people realized the importance and urgent of sewage disposal. Active bacteria method is an effective technique for sewage disposal. The abundance requirement for lacunaris plastic makes it is a consequent for plastic producing with automation and high productivity. Therefore, it is very necessary to design a manipulator that can automatically fulfill the plastic holding. With the analysis of the problems in the design of the plastic holding manipulator and synthesizing the robot research and development condition in recent years, a economic scheme is concluded on the basis of the analysis of mechanical configuration, transform system, drive device and control system and guided by the idea of the characteristic and complex of mechanical configuration, electronic, software and hardware. In this article, the mechanical configuration combines the character of direction coordinate which can improve the stability and operation flexibility of the system. The main function of the transmission mechanism is to transmit power to implement department and complete the necessary movement. In this transmission structure, the screw transmission mechanism transmits the rotary motion into linear motion. Worm gear can give vary transmission ratio. Both of the transmission mechanisms have a characteristic of compact structure. The design of drive system often is limited by the environment condition and the factor of costand technical lever. The step motor can receive digital signal directly and has the ability to response outer environment immediately and has no accumulation error, which often is used in driving system. In this driving system, open-loop control system is composed of stepping motor, which can satisfy the demand not only for control precision but also for the target of economic and practicality. On this basis, the analysis of stepping motor in power calculating and style selecting is also given. The analysis of kinematics and dynamics for object holding manipulator is given in completing the design of mechanical structure and drive system.Current industrial approaches to robot arm control treat each joint of the robot arm as a simple joint servomechanism. The servomechanism approach models the varying dynamics of a manipulator inadequately because it neglects the motion and configuration of the whole arm mechanism. These changes in the parameters of the controlled system sometimes are significant enough to render conventional feedback control strategies ineffective. The result is reduced servo response speed and damping, limiting the precision and speed of the end-effecter and making it appropriate only for limited-precision tasks. Manipulators controlled in this manner move at slow speeds with unnecessary vibrations. Any significant performance gain in this and other areas of robot arm control require the consideration of more efficient dynamic models, sophisticated control approaches, and the use of dedicated computer architectures and parallel processing techniques.In the industrial production and other fields, people often endangered by such factors as high temperature, corrode, poisonous gas and so forth at work, which have increased labor intensity and even jeopardized the life sometimes. The corresponding problems are solved since the robot arm comes out. The arms can catch, put and carry objects, and its movements are flexible and diversified. It applies to medium and small-scale automated production in which production varieties can be switched. And it is widely used on soft automatic line. The robot arms are generally made by withstand high temperatures, resist corrosion of materials to adapt to the harsh environment. So they reduced the labor intensity of the workers significantly and raised work efficiency. The robot arm is an important component of industrial robot, and it can be called industrial robots on many occasions. Industrial robot is set machinery, electronics, control, computers, sensors, artificial intelligence and other advanced technologies in the integration of multidisciplinary important modern manufacturing equipment. Widely using industrial robots, not only can improve product quality and production, but also is of great significance for physical security protection, improvement of the environment for labor, reducing labor intensity, improvement of labor productivity, raw material consumption savings and lowering production costs.There are such mechanical components as ball footbridge, slides, air control mechanical hand and so on in the design. A programmable controller, a programming device, stepping motors, stepping motors drives, direct currentmotors, sensors, switch power supply, an electromagnetism valve and control desk are used in electrical connection.Robot is the automated production of a kind used in the pr ocess of crawling and moving piece features automatic device, wh ich is mechanized and automated production process developed a n ew type of device. In recent years, as electronic technology, e specially computer extensive use of robot development and product ion of hightech fields has become a rapidly developed a new te chnology, which further promoted the development of robot, allowi ng robot to better achieved with the combination of mechanizatio n and automation. Robot can replace humans completed the risk o f duplication of boring work, to reduce human labor intensity a nd improve labor productivity. Manipulator has been applied more and more widely, in the machinery industry, it can be used f or parts assembly, work piece handling, loading and unloading, p articularly in the automation of CNC machine tools, modular mach ine tools more commonly used. At present, the robot has develop ed into a FMS flexible manufacturing systems and flexible manufa cturing cell in an important component of the FMC. The machine tool equipment and machinery in hand together constitute a fle xible manufacturing system or a flexible manufacturing cell, it was adapted to small and medium volume production, you can savea huge amount of the work piece conveyor device, compact, and adaptable. When the work piece changes, flexible production sys tem is very easy to change will help enterprises to continuousl y update the marketable variety, improve product quality, and be tter adapt to market competition. At present, China's industrial robot technology and its engineering application level and comp arable to foreign countries there is a certain distance, applica tion and industrialization of the size of the low level of rob ot research and development of a direct impact on raising the level of automation in China, from the economy, technical consid erations are very necessary. Therefore, the study of mechanical hand design is very meaningful.关于现代工业机械手机器人是典型的机电一体化装置，它综合运用了机械与精密机械、微电子与计算机、自动控制与驱动、传感器与信息处理以及人工智能等多学科的最新研究成果，随着经济技术的发展和各行各业对自动化程度要求的提高，机器人技术得到了迅速发展，出现了各种各样的机器人产品。
工业机器人的介绍外文文献翻译、中英文翻译、外文翻译
外文原文Introduction to Industrial RobotsIndustrial robets became a reality in the early 1960’s when Joseph Engelberger and George Devol teamed up to form a robotics company they called “Unimation”.Engelberger and Devol were not the first to dream of machines that could perform the unskilled, repetitive jobs in manufacturing. The first use of the word “robots” was by the Czechoslovakian philosopher and playwright Karel Capek in his play R.U.R.(Rossum’s Universal Robot). The word “robot” in Czech means “worker” or “slave.” The play was written in 1922.In Capek’s play , Rossum and his son discover the chemical formula for artificial protoplasm. Protoplasm forms the very basis of life.With their compound,Rossum and his son set out to make a robot.Rossum and his son spend 20 years forming the protoplasm into a robot. After 20 years the Rossums look at what they have created and say, “It’s absurd to spend twenty years making a man if we can’t make him quicker than nature, you might as w ell shut up shop.”The young Rossum goes back to work eliminating organs he considers unnecessary for the ideal worker. The young Rossum says, “A man is something that feels happy , plays piano ,likes going for a walk, and in fact wants to do a whole lot of things that are unnecessary … but a working machine must not play piano, must not feel happy, must not do a whole lot of other things. Everything that doesn’t contribute directly to the progress of work should be eliminated.”A half century later, engi neers began building Rossum’s robot, not out of artificial protoplasm, but of silicon, hydraulics, pneumatics, and electric motors. Robots that were dreamed of by Capek in 1922, that work but do not feel, that perform unhuman or subhuman, jobs in manufacturing plants, are available and are in operation around the world.The modern robot lacks feeling and emotions just as Rossum’s son thought it should. It can only respond to simple “yes/no” questions. The moderrn robot is normally bolted to the floor. It has one arm and one hand. It is deaf, blind, and dumb. In spite of all of these handicaps, the modern robot performs its assigned task hour after hour without boredom or complaint.A robot is not simply another automated machine. Automation began during the industrial revolution with machines that performed jobs that formerly had been done by human workers. Such a machine, however , can do only the specific job for which it was designed, whereas a robot can perform a variety of jobs.A robot must have an arm. The arm must be able to duplicate the movements of a human worker in loading and unloading other automated machines, spraying paint, welding, and performing hundreds of other jobs that cannot be easily done with conventional automated machines.DEFINITION OF A ROBOTThe Robot Industries Association(RIA) has published a definition for robots in an attempt to clarify which machines are simply automated machines and which machines are truly robots. The RIA definition is as follows:“A robot is a reprogrammabl e multifunctional manipulator designed to move material, parts, tools, or specialized devices through variable programmed motions for the performance of a variety of tasks.”This definition, which is more extensive than the one in the RIA glossary at the end of this book, is an excellent definition of a robot. We will look at this definition, one phrase at a time, so as to understand which machines are in fact robots and which machines are little more than specialized automation.First, a robot is a “reprogrammable multifunctional manipulator.” In this phrase RIA tells us that a robot can be taught (“reprogrammed”) to do more than one job by changing the informaion stored in its memory. A robot can be reprogrammed to load and unload machines, weld, and do ma ny other jobs (“multifunctional”). A robot is a“manipulator”. A manipulator is an arm( or hand ) that can pick up or move things. At this point we know that a robot is an arm that can be taught to do different jobs.The definition goes on to say that a ro bot is “designed to move material, parts, tools, or specialized devices.” Material includes wood,steel, plastic, cardboard… anything that is used in the manufacture of a product.A robot can also handle parts that have been manufactured. For example, a robot can load a piece of steel into an automatic lathe and unload a finished part out of the lathe.In addition to handling material and parts, a robot can be fitted with tools such as grinders, buffers, screwdrivers, and welding torches to perform useful work.Robots can also be fitted with specialized instruments or devices to do special jobs in a manufacturing plant. Robots can be fitted with television cameras for inspection of parts or products. They can be fitted with lasers to accurately mearure the size of parts being manufactured.The RIA definition closes with the phrase,”…through variable programmed motions for the performance of a variety of tasks.” This phrase emphasizes the fact that a robot can do many different jobs in a manufacturing plant. The variety of jobs that a robot can do is limited only by the creativity of the application engineer.JOBS FOR ROBOTSJobs performed by robots can be divided into two major categories:hazardous jobs and repetitive jobs.Hazardous JobsMany applications of robots are in jobs that are hazardous to humans. Such jobs may be considered hazardous because of toxic fumes, the weight of the material being handled, the temperature of the material being handled, the danger of working near rotating or press machinery, or environments containing high levels of radiation. Repetitive JobsIn addition to taking over hazardous jobs, robots are well suited to doingextremely repetitive jobs that must be done in manufacturing plants.many jobs in manufacturing plants require a person to act more like a machine than like a human. The job may be to pick a piece up from here and place it there. The same job is done hundreds of times each day. The job requires little or no judgment and little or no skill. This is not said as a criticism of the person who does the job , but is intended simply to point out that many of these jobs exist in industry and must be done to complete the manufacture of products. A robot can be placed at such a work station and can perform the job admirably without complaining or experiencing the fatigue and boredom normally associated with such a job.Although robots eliminate some jobs in industry, they normally eliminate jobs that humans should never have been asked to do. Machines should perform as machines doing machine jobs, and humans should be placed in jobs that require the use of their ability,creativity, and special skills.POTENTIAL FOR INCREASED PRODUCTIVITYIn addition to removing people from jobs they should not have been placed in, robots offer companies the opportunity of achieving increased productivity. When robots are placed in repetitive jobs they continue to operate at their programmed pace without fatigue. Robots do not take either scheduled or unscheduled breaks from the job. The increase in productivity can result in at least 25% more good parts being produced in an eight-hour shift. This increase in productivity increases the company's profits, which can be reinvested in additional plants and equipment. This increase in productivity results in more jobs in other departments in the plant. With more parts being produced, additional people are needed to deliver the raw materials to the plant, to complete the assembly of the finished products, to sell the finished products, and to deliver the products to their destinations.ROBOT SPEEDAlthough robots increase productivity in a manufacturing plant, they are notexceptionally fast. At present, robots normally operate at or near the speed of a human operator. Every major move of a robot normally takes approximately one second. For a robot to pick up a piece of steel from a conveyor and load it into a lathe may require ten different moves taking as much as ten seconds. A human operator can do the same job in the same amount of time . The increase in productivity is a result of the consistency of operation. As the human operator repeats the same job over and over during the workday, he or she begins to slow down. The robot continues to operate at its programmed speed and therefore completes more parts during the workday.Custom-built automated machines can be built to do the same jobs that robots do. An automated machine can do the same loading operation in less than half the time required by a robot or a human operator. The problem with designing a special machine is that such a machine can perform only the specific job for which it was built. If any change is made in the job, the machine must be completely rebuilt, or the machine must be scrapped and a new machine designed and built. A robot, on the other hand, could be reprogrammed and could start doing the new job the same day.Custom-built automated machines still have their place in industry. If a company knows that a job will not change for many years, the faster custom-built machine is still a good choice.Other jobs in factories cannot be done easily with custom-built machinery. For these applications a robot may be a good choice. An example of such an application is spray painting. One company made cabinets for the electronics industry. They made cabinets of many different sizes, all of which needed painting. It was determined that it was not economical for the company to build special spray painting machines for each of the different sizes of enclosures that were being built. Until robots were developed, the company had no choice but to spray the various enclosures by hand.Spray painting is a hazardous job , because the fumes from many paints are both toxic and explosive. A robot is now doing the job of spraying paint on the enclosures.A robot has been “taught” to spray all the different sizes of enclosures that the company builds. In addition, the robot can operate in the toxic environment of the spray booth without any concern for the long-term effect the fumes might have on aperson working in the booth.FLEXIBLE AUTOMATIONRobots have another advantage: they can be taught to do different jobs in the manufacturing plant. If a robot was originally purchased to load and unload a punch press and the job is no longer needed due to a change in product design, the robot can be moved to another job in the plant. For example, the robot could be moved to the end of the assembly operation and be used to unload the finished enclosures from a conveyor and load them onto a pallet for shipment.ACCURACY AND REPEATABILITYOne very important characteristic of any robot is the accuracy with which it can perform its task. When the robot is programmed to perform a specific task, it is led to specific points and programmed to remember the locations of those points. After programming has been completed, the robot is switched to “run” and the program is executed. Unfortunately, the robot will not go to the exact location of any programmed point. For example, the robot may miss the exact point by 0.025 in. If 0.025 in. is the greatest error by which the robot misses any point- during the first execution of the program, the robot is said to have an accuracy of 0.025 in.In addition to accuracy , we are also concerned with the robot’s repeatability. The repeatability of a robot is a measure of how closely it returns to its programmed points every time the program is executed. Say , for example, that the robot misses a programmed point by 0.025 in. the first time the program is executed and that, during the next execution of the program, the robot misses the point it reached during the previous cycle by 0.010 in. Although the robot is a total of 0.035 in. from the original programmed point, its accuracy is 0.025 in. and its repeatability is 0.010 in.THE MAJOR PARTS OF A ROBOTThe major parts of a robot are the manipulator, the power supply, and the controller.The manipulator is used to pick up material, parts, or special tools used in manufacturing. The power supply suppplies the power to move the manipulator. The controller controls the power supply so that the manipulator can be taught to perform its task.外文翻译工业机器人的介绍20世纪60年代当约瑟夫和乔治合作创立了名为Unimation的机器公司，工业机器人便成为了一个事实。
步行机器人中英文对照外文翻译文献
步行机器人中英文对照外文翻译文献(文档含英文原文和中文翻译)图1 远程脑系统的硬件配置图2 两组机器人的身体结构图3 传感器的两个水银定位开关图4 层次分类图5 步行步态该输入处理器是作为参考程序块和一个图像搜索窗口形象该大小的搜索窗口取决于参考块的大小通常高达16 * 16且匹配。
该处理器计算价值块在搜索窗口，还找到最佳匹配块，这就是其中的最低当目标平移时块匹配是非常有力的。
然而，普通的块匹配方法当它旋转时无法跟踪目标。
为了克服这一困难，我们开发了一种新方法，跟随真正旋转目标的图6 双足步行图6 双足步行图7 双足步行实验图8 一系列滚动和站立运动通过集成传感器网络转型的综合为了使上述描述的基本动作成为一体，我们通过一种方法来描述一种被认为是根据传感器状况的网络转型。
图9显示了综合了基本动作机器人的状态转移图：两足行走，滚动，坐着和站立。
这种一体化提供了机器人保持行走甚至跌倒时的problems and advance the study of vision-based behaviors, we have adopted a new approach through building remote-brained robots. The body and the brain are connected by wireless links by using wireless cameras and remote-controlled actuators.As a robot body does not need computers on-board,it becomes easier to build a lightweight body with many DOFS in actuation.In this research, we developed a two-armed bipedal robot using the remote-brained robot environment and made it to perform balancing based on vision and getting up through cooperating arms and legs. The system and experimental results are described below.2 The Remote-Brained SystemThe remote-brained robot does not bring its own brain within the body. It leaves the brain in the mother environment and communicates with it by radio links. This allows us to build a robot with a free body and a heavy brain. The connection link between the body and the brain defines the interface between software and hardware. Bodies are designed to suit each research project and task. This enables us advance in performing research with a variety of real robot systems[10].A major advantage of remote-brained robots is that the robot can have a large and heavy brain based on super parallel computers. Although hardware technology for vision has advanced and produced powerful compact vision systems, the size of the hardware is still large. Wireless connection between the camera and the vision processor has been a research tool. The remote-brained approach allows us to progress in the study of a variety of experimental issues in vision-based robotics.Another advantage of remote-brained approach is that the robot bodies can be lightweight. This opens up the possibility of working with legged mobile robots. AsFigure 4 shows some of the classes in the programming environent for remote-brained robot written in Euslisp. The hierachy in the classes provides us with rich facilities for extending development of various robots.4 Vision-Based BalancingThe robot can stand up on two legs. As it can change the gravity center of its body by controling the ankle angles, it can perform static bipedal walks. During static walking the robot has to control its body balance if the ground is not flat and stable.In order to perform vision-based balancing it is re-quired to have high speed vision system to keep ob-serving moving schene. We have developed a tracking vision board using a correlation chip[l3]. The vision board consists of a transputer augmented with a special LSI chip(MEP[14] : Motion Estimation Processor) which performs local image block matching.The inputs to the processor MEP are an image as a reference block and an image for a search window.The size of the reference blsearch window depends on the size of the reference block is usually up to 32 by 32 pixels so that it can include 16 * 16 possible matches. The processor calculates 256 values of SAD (sum of absolute difference) between the reference block and 256 blocks in the search window and also finds the best matching block, that is, the one which has the minimum SAD value.Clock is up to 16 by 16 pixels.The size of the search window depends on the size of the reference block is usually up to 32 by 32 pixels so that it can include 16 * 16 possible matches. The processor calculates 256 values of SAD (sum of absolute difference) between the reference block and 256 blocks in the search window and also finds the best matching block, that is, the one which has the minimum SAD value.Block matching is very powerful when the target moves only in translation. However, the ordinary block matching method cannot track the target when it rotates. In order to overcome this difficulty, we developed a new method which follows up the candidate templates to real rotation of the target. The rotated template method first generates all the rotated target images in advance, and several adequate candidates of the reference template are selected and matched is tracking the scene in the front view. It remembers the vertical orientation of an object as the reference for visual tracking and generates several rotated images of the reference image. If the vision tracks the reference object using the rotated images, it can measures the body rotation. In order to keep the body balance, the robot feedback controls its body rotation to control the center of the body gravity. The rotational visual tracker[l5] can track the image at video rate.5 Biped WalkingIf a bipedal robot can control the center of gravity freely, it can perform biped walk. As the robot shown in Figure 2 has the degrees to left and right directions at the ankle position, it can perform bipedal walking in static way.The motion sequence of one cycle in biped walking consists of eight phases as shown in Figure 6. One step consists of four phases; move-gravity-center-on-foot,lift-leg, move-forward-leg, place-leg. As the body is described in solid model, the robot can generate a body configuration for move-gravity-center-on-foot according to the parameter of the hight of the gravity center. After this movement, the robot can lift the other leg and move it forward. In lifting leg, the robot has to control the configuration in order to keep the center of gravity above the supporting foot. As the stability in balance depends on the hight of the gravity center, the robot selects suitable angles of the knees.Figure 7 shows a sequence of experiments of the robot in biped walking6 Rolling Over and Standing UpFigure 8 shows the sequence of rolling over, sitting and standing up. This motion requires coordination between arms and legs.As the robot foot consists of a battery, the robot can make use of the weight of the battery for the roll-over motion. When the robot throws up the left leg and moves the left arm back and the right arm forward, it can get rotary moment around the body. If the body starts turning, the right leg moves back and the left foot returns its position to lie on the face. This rollover motion changes the body orientation from face up to face down. It canbe verified by the orientation sensor.After getting face down orientation, the robot moves the arms down to sit on two feet. This motion causes slip movement between hands and the ground. If the length of the arm is not enough to carry the center of gravity of the body onto feet, this sitting motion requires dynamic pushing motion by arms. The standing motion is controlled in order to keep the balance.7 Integration through Building Sensor-Based Transition NetIn order to integrate the basic actions described above, we adopted a method to describe a sensor-based transition network in which transition is considered according to sensor status. Figure 9 shows a state transition diagram of the robot which integrates basic actions: biped walking, rolling over, sitting, and standing up. This integration provides the robot with capability of keeping walking even when it falls down.The ordinary biped walk is composed by taking two states, Left-leg Fore and Right-leg Fore, successively.The poses in ‘Lie on the Back’ and ‘Lie on the Face’are as same as one in ‘Stand’. That is, the shape ofthe robot body is same but the orientation is different.The robot can detect whether the robot lies on the back or the face using the orientation sensor. When the robot detects falls down, it changes the state to ‘Lie on the Back’ or ‘Lie on the Front’ by moving to the neutral pose. If the robot gets up from ‘Lie on the Back’, the motion sequence is planned to exe cute Roll-over, Sit and Stand-up motions. If the state is ‘Lie on the Face’, it does not execute Roll-over but moves arms up to perform the sitting motion.8 Concluding RemarksThis paper has presented a two-armed bipedal robot which can perform statically biped walk, rolling over and standing up motions. The key to build such behaviors is the remote-brained approach. As the experiments have shown, wireless technologies permit robot bodies free movement. It also seems to change the way we conceptualize robotics. In our laboratory it has enabled the development of a new research environment, better suited to robotics and real-world AI.The robot presented here is a legged robot. As legged locomotion requires dynamic visual feedback control, its vision-based behaviors can prove the effectiveness of the vision system and the remote-brained system. Our vision system is based on high speed block matching function implemented with motion estimation LSI. The vision system provides the mechanical bodies with dynamic and adaptive capabilities in interaction with human. The mechanical dog has shown adaptive behaviors based on distance。
机器人外文翻译(中英文翻译)
外文翻译机器人The robot性质: □毕业设计□毕业论文教学院：机电工程学院系别：机械设计制造及其自动化学生学号：学生姓名：专业班级：指导教师：职称：起止日期：机器人1.机器人的作用机器人是高级整合控制论、机械电子、计算机、材料和仿生学的产物。
在工业、医学、农业、建筑业甚至军事等领域中均有重要用途。
现在，国际上对机器人的概念已经逐渐趋近一致。
一般说来，人们都可以接受这种说法，即机器人是靠自身动力和控制能力来实现各种功能的一种机器。
联合国标准化组织采纳了美国机器人协会给机器人下的定义：“一种可编程和多功能的，用来搬运材料、零件、工具的操作机；或是为了执行不同的任务而具有可改变和可编程动作的专门系统。
2.能力评价标准机器人能力的评价标准包括：智能，指感觉和感知，包括记忆、运算、比较、鉴别、判断、决策、学习和逻辑推理等；机能，指变通性、通用性或空间占有性等；物理能，指力、速度、连续运行能力、可靠性、联用性、寿命等。
因此，可以说机器人是具有生物功能的三维空间坐标机器。
3.机器人的组成机器人一般由执行机构、驱动装置、检测装置和控制系统等组成。
执行机构即机器人本体，其臂部一般采用空间开链连杆机构，其中的运动副（转动副或移动副）常称为关节，关节个数通常即为机器人的自由度数。
根据关节配置型式和运动坐标形式的不同，机器人执行机构可分为直角坐标式、圆柱坐标式、极坐标式和关节坐标式等类型。
出于拟人化的考虑，常将机器人本体的有关部位分别称为基座、腰部、臂部、腕部、手部（夹持器或末端执行器）和行走部（对于移动机器人）等。
驱动装置是驱使执行机构运动的机构，按照控制系统发出的指令信号，借助于动力元件使机器人进行动作。
它输入的是电信号，输出的是线、角位移量。
机器人使用的驱动装置主要是电力驱动装置，如步进电机、伺服电机等，此外也有采用液压、气动等驱动装置。
检测装置的作用是实时检测机器人的运动及工作情况，根据需要反馈给控制系统，与设定信息进行比较后，对执行机构进行调整，以保证机器人的动作符合预定的要求。
双足步行机器人相关翻译
本科毕业论文外文文献及译文文献、资料题目：Ｗalking Coｎtrol alｇorithm oｆBipｅd Huｍaｎoｉd Roｂｏｔ文献、资料来源：期刊文献、资料发表（出版）日期：１999.６。
3院（部）：理学院专业：光信息科学与技术班级：光信112姓名：王若宇学号: 201１1211３5指导教师:赵俊卿翻译日期：20１５。
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协作移动机器人-前因和方向外文文献翻译、中英文翻译、外文翻译
Cooperative Mobile Robotics: Antecedents and DirectionsY. UNY CAOComputer Science Department, University of California, Los Angeles, CA 90024-1596ALEX S. FUKUNAGAJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109-8099ANDREW B. KAHNGComputer Science Department, University of California, Los Angeles, CA 90024-1596Editors: R.C. Arkin and G.A. BekeyAbstract. There has been increased research interest in systems composed of multiple autonomous mobile robots exhibiting cooperative behavior. Groups of mobile robots are constructed, with an aim to studying such issues as group architecture, resource conflict, origin of cooperation, learning, and geometric problems. As yet, few applications of cooperative robotics have been reported, and supporting theory is still in its formative stages. In this paper, we give a critical survey of existing works and discuss open problems in this field, emphasizing the various theoretical issues that arise in the study of cooperative robotics. We describe the intellectual heritages that have guided early research, as well as possible additions to the set of existing motivations.Keywords: cooperative robotics, swarm intelligence, distributed robotics, artificial intelligence, mobile robots, multiagent systems1. PreliminariesThere has been much recent activity toward achieving systems of multiple mobile robots engaged in collective behavior. Such systems are of interest for several reasons:•tasks may be inherently too complex (or im-possible) for a single robot to accomplish, or performance benefits can be gained from using multiple robots;•building and using several simple robots can be easier, cheaper, more flexible and more fault-tolerant than having a single powerful robot foreach separate task; and•the constructive, synthetic approach inherent in cooperative mobile robotics can possibly∗This is an expanded version of a paper which originally appeared in the proceedings of the 1995 IEEE/RSJ IROS conference. yield insights into fundamental problems in the social sciences (organization theory, economics, cognitive psychology), and life sciences (theoretical biology, animal ethology).The study of multiple-robot systems naturally extends research on single-robot systems, butis also a discipline unto itself: multiple-robot systems can accomplish tasks that no single robot can accomplish, since ultimately a single robot, no matter how capable, is spatially limited. Multiple-robot systems are also different from other distributed systems because of their implicit “real-world” environment, which is presumably more difficult to model and reason about than traditional components of distributed system environments (i.e., computers, databases, networks).The term collective behavior generically denotes any behavior of agents in a system having more than one agent. the subject of the present survey, is a subclass of collective behavior that is characterized by cooperation. Webster’s dictionary [118] defines “cooperate” as “to associate with anoth er or others for mutual, often economic, benefit”. Explicit definitions of cooperation in the robotics literature, while surprisingly sparse, include:1. “joint collaborative behavior that is directed toward some goal in which there is a common interest or reward” [22];2. “a form of interaction, usually based on communication” [108]; and3. “[joining] together for doing something that creates a progressive result such as increasing performance or saving time” [137].These definitions show the wide range of possible motivating perspectives. For example, definitions such as (1) typically lead to the study of task decomposition, task allocation, and other dis-tributed artificial intelligence (DAI) issues (e.g., learning, rationality). Definitions along the lines of (2) reflect a concern with requirements for information or other resources, and may be accompanied by studies of related issues such as correctness and fault-tolerance. Finally, definition (3) reflects a concern with quantified measures of cooperation, such as speedup in time to complete a task. Thus, in these definitions we see three fundamental seeds: the task, the mechanism of cooperation, and system performance.We define cooperative behavior as follows: Given some task specified by a designer, a multiple-robot system displays cooperative behavior if, due to some underlying mechanism (i.e., the “mechanism of cooperation”), there is an increase in the total utility of the system. Intuitively, cooperative behavior entails some type of performance gain over naive collective behavior. The mechanism of cooperation may lie in the imposition by the designer of a control or communication structure, in aspects of the task specification, in the interaction dynamics of agent behaviors, etc.In this paper, we survey the intellectual heritage and major research directions of the field of cooperative robotics. For this survey of cooperative robotics to remain tractable, we restrict our discussion to works involving mobile robots or simulations of mobile robots, where a mobile robot is taken to be an autonomous, physically independent, mobile robot. In particular, we concentrated on fundamental theoretical issues that impinge on cooperative robotics. Thus, the following related subjects were outside the scope of this work:•coordination of multiple manipulators, articulated arms, or multi-fingered hands, etc.•human-robot cooperative systems, and user-interface issues that arise with multiple-robot systems [184] [8] [124] [1].•the competitive subclass of coll ective behavior, which includes pursuit-evasion [139], [120] and one-on-one competitive games [12]. Note that a cooperative team strategy for, e.g., work on the robot soccer league recently started in Japan[87] would lie within our present scope.•emerging technologies such as nanotechnology [48] and Micro Electro-Mechanical Systems[117] that are likely to be very important to co-operative robotics are beyond the scope of this paper.Even with these restrictions, we find that over the past 8 years (1987-1995) alone, well over 200papers have been published in this field of cooperative (mobile) robotics, encompassing theories from such diverse disciplines as artificial intelligence, game theory/economics, theoretical biology, distributed computing/control, animal ethology and artificial life.We are aware of two previous works that have surveyed or taxonomized the literature. [13] is abroad, relatively succinct survey whose scope encompasses distributed autonomous robotic systems(i.e., not restricted to mobile robots). [50] focuses on several well-known “swarm” architectures (e.g., SWARM and Mataric’s Behavior-based architecture –see Section 2.1) and proposes a taxonomy to characterize these architectures. The scope and intent of our work differs significantly from these, in that (1) we extensively survey the field of co-operative mobile robotics, and (2) we provide a taxonomical organization of the literature based on problems and solutions that have arisen in the field (as opposed to a selected group of architectures). In addition, we survey much new material that has appeared since these earlier works were published.Towards a Picture of Cooperative RoboticsIn the mid-1940’s Grey Walter, along with Wiener and Shannon, studied turtle-like robots equipped wit h light and touch sensors; these simple robots exhibited “complex social behavior” in responding to each other’s movements [46]. Coordination and interactions of multiple intelligent agents have been actively studied in the field of distributed artificial intelligence (DAI) since the early 1970’s[28], but the DAI field concerned itself mainly with problems involving software agents. In the late 1980’s, the robotics research community be-came very active in cooperative robotics, beginning with projects such as CEBOT [59], SWARM[25], ACTRESS [16], GOFER [35], and the work at Brussels [151]. These early projects were done primarily in simulation, and, while the early work on CEBOT, ACTRESS and GOFER have all had physical implementations (with≤3 robots), in some sense these implementations were presented by way of proving the simulation results. Thus, several more recent works (cf. [91], [111], [131])are significant for establishing an emphasis on the actual physical implementation of cooperative robotic systems. Many of the recent cooperative robotic systems, in contrast to the earlier works, are based on a behavior-based approach (cf. [30]).Various perspectives on autonomy and on the connection between intelligence and environment are strongly associated with the behavior-based approach [31], but are not intrinsic to multiple-robot systems and thus lie beyond our present scope. Also note that a recent incarnation of CEBOT, which has been implemented on physical robots, is based on a behavior-based control architecture[34].The rapid progress of cooperative robotics since the late 1980’s has been an interplay of systems, theories and problems: to solve a given problem, systems are envisioned, simulated and built; theories of cooperation are brought from other fields; and new problems are identified (prompting further systems and theories). Since so much of this progress is recent, it is not easy to discern deep intellectual heritages from within the field. More apparent are the intellectualheritages from other fields, as well as the canonical task domains which have driven research. Three examples of the latter are:•Traffic Control. When multiple agents move within a common environment, they typically attempt to avoid collisions. Fundamentally, this may be viewed as a problem of resource conflict, which may be resolved by introducing, e.g., traffic rules, priorities, or communication architectures. From another perspective, path planning must be performed taking into con-sideration other robots and the global environment; this multiple-robot path planning is an intrinsically geometric problem in configuration space-time. Note that prioritization and communication protocols – as well as the internal modeling of other robots – all reflect possible variants of the group architecture of the robots. For example, traffic rules are commonly used to reduce planning cost for avoiding collision and deadlock in a real-world environment, such as a network of roads. (Interestingly, behavior-based approaches identify collision avoidance as one of the most basic behaviors [30], and achieving a collision-avoidance behavior is the natural solution to collision avoidance among multiple robots. However, in reported experiments that use the behavior-based approach, robots are never restricted to road networks.) •Box-Pushing/Cooperative Manipulation. Many works have addressed the box-pushing (or couch-pushing) problem, for widely varying reasons. The focus in [134] is on task allocation, fault-tolerance and (reinforcement) learning. By contrast, [45] studies two boxpushing protocols in terms of their intrinsic communication and hardware requirements, via the concept of information invariants. Cooperative manipulation of large objects is particularly interesting in that cooperation can be achieved without the robots even knowing of each others’ existence [147], [159]. Other works in the class of box-pushing/object manipulation include [175] [153] [82] [33] [91] [94] [92][114] [145] [72] [146].•Foraging. In foraging, a group of robots must pick up objects scattered in the environment; this is evocative of toxic waste cleanup, harvesting, search and rescue, etc. The foraging task is one of the canonical testbeds for cooperative robotics [32] [151] [10] [67] [102] [49] [108] [9][24]. The task is interesting because (1) it can be performed by each robot independently (i.e., the issue is whether multiple robots achieve a performance gain), and (2) as discussed in Section 3.2, the task is also interesting due to motivations related to the biological inspirations behind cooperative robot systems. There are some conceptual overlaps with the related task of materials handling in a manufacturing work-cell [47]. A wide variety of techniques have been applied, ranging from simple stigmergy (essentially random movements that result in the fortuitous collection of objects [24] to more complex algorithms in which robots form chains along which objects are passed to the goal [49].[24] defines stigmergy as “the production of a certain behaviour in agents as a consequence of the effects produced in the local environment by previous behaviour”. This is actually a form of “cooperation without communication”, which has been the stated object of several for-aging solutions since the corresponding formulations become nearly trivial if communication is used. On the other hand, that stigmergy may not satisfy our definition of cooperation given above, since there is no performance improvement over the “naive algorithm” –in this particular case, the proposed stigmergic algorithm is the naive algorithm. Again, group architecture and learning are major research themes in addressing this problem.Other interesting task domains that have received attention in the literature includemulti-robot security systems [53], landmine detection and clearance [54], robotic structural support systems (i.e., keeping structures stable in case of, say ,an earthquake) [107], map making [149], and assembly of objects using multiple robots [175].Organization of PaperWith respect to our above definition of cooperative behavior, we find that the great majority of the cooperative robotics literature centers on the mechanism of cooperation (i.e., few works study a task without also claiming some novel approach to achieving cooperation). Thus, our study has led to the synthesis of five “Research Axes” which we believe comprise the major themes of investigation to date into the underlying mechanism of cooperation.Section 2 of this paper describes these axes, which are: 2.1 Group Architecture, 2.2 Resource Conflict, 2.3 Origin of Cooperation, 2.4 Learning, and 2.5 Geometric Problems. In Section 3,we present more synthetic reviews of cooperative robotics: Section 3.1 discusses constraints arising from technological limitations; and Section 3.2discusses possible lacunae in existing work (e.g., formalisms for measuring performance of a cooperative robot system), then reviews three fields which we believe must strongly influence future work. We conclude in Section 4 with a list of key research challenges facing the field.2. Research AxesSeeking a mechanism of cooperation may be rephrased as the “cooperative behavior design problem”: Given a group of robots, an environment, and a task, how should cooperative behavior arise? In some sense, every work in cooperative robotics has addressed facets of this problem, and the major research axes of the field follow from elements of this problem. (Note that certain basic robot interactions are not task-performing interactions per se, but are rather basic primitives upon which task-performing interactions can be built, e.g., following ([39], [45] and many others) or flocking [140], [108]. It might be argued that these interactions entail “control and coordination” tasks rather than “cooperation” tasks, but o ur treatment does not make such a distinction).First, the realization of cooperative behavior must rely on some infrastructure, the group architecture. This encompasses such concepts as robot heterogeneity/homogeneity, the ability of a given robot to recognize and model other robots, and communication structure. Second, for multiple robots to inhabit a shared environment, manipulate objects in the environment, and possibly communicate with each other, a mechanism is needed to resolve resource conflicts. The third research axis, origins of cooperation, refers to how cooperative behavior is actually motivated and achieved. Here, we do not discuss instances where cooperation has been “explicitly engineered” into the robots’ behavior since this is the default approach. Instead, we are more interested in biological parallels (e.g., to social insect behavior), game-theoretic justifications for cooperation, and concepts of emergence. Because adaptability and flexibility are essential traits in a task-solving group of robots, we view learning as a fourth key to achieving cooperative behavior. One important mechanism in generating cooperation, namely,task decomposition and allocation, is not considered a research axis since (i) very few works in cooperative robotics have centered on task decomposition and allocation (with the notable exceptions of [126], [106], [134]), (ii) cooperative robot tasks (foraging, box-pushing) in the literature are simple enough that decomposition and allocation are not required in the solution, and (iii) the use of decomposition and allocation depends almost entirely on the group architectures(e.g. whether it is centralized or decentralized).Note that there is also a related, geometric problem of optimizing the allocation of tasks spatially. This has been recently studied in the context of the division of the search of a work area by multiple robots [97]. Whereas the first four axes are related to the generation of cooperative behavior, our fifth and final axis –geometric problems–covers research issues that are tied to the embed-ding of robot tasks in a two- or three-dimensional world. These issues include multi-agent path planning, moving to formation, and pattern generation.2.1. Group ArchitectureThe architecture of a computing sys tem has been defined as “the part of the system that remains unchanged unless an external agent changes it”[165]. The group architecture of a cooperative robotic system provides the infrastructure upon which collective behaviors are implemented, and determines the capabilities and limitations of the system. We now briefly discuss some of the key architectural features of a group architecture for mobile robots: centralization/decentralization, differentiation, communications, and the ability to model other agents. We then describe several representative systems that have addressed these specific problems.Centralization/Decentralization The most fundamental decision that is made when defining a group architecture is whether the system is centralized or decentralized, and if it is decentralized, whether the system is hierarchical or distributed. Centralized architectures are characterized by a single control agent. Decentralized architectures lack such an agent. There are two types of decentralized architectures: distributed architectures in which all agents are equal with respect to control, and hierarchical architectures which are locally centralized. Currently, the dominant paradigm is the decentralized approach.The behavior of decentralized systems is of-ten described using such terms as “emergence” and “self-organization.” It is widely claimed that decentralized architectures (e.g., [24], [10], [152],[108]) have several inherent advantages over centralized architectures, including fault tolerance, natural exploitation of parallelism, reliability, and scalability. However, we are not aware of any published empirical or theoretical comparison that supports these claims directly. Such a comparison would be interesting, particularly in scenarios where the team of robots is relatively small(e.g., two robots pushing a box), and it is not clear whether the scaling properties of decentralization offset the coordinative advantage of centralized systems.In practice, many systems do not conform toa strict centralized/decentralized dichotomy, e.g., many largely decentralized architectures utilize “leader” agents. We are not aware of any in-stances of systems that are completely centralized, although there are some hybrid centralized/decentralized architectures wherein there is a central planner that exerts high-levelcontrol over mostly autonomous agents [126], [106], [3], [36].Differentiation We define a group of robots to be homogeneous if the capabilities of the individual robots are identical, and heterogeneous otherwise. In general, heterogeneity introduces complexity since task allocation becomes more difficult, and agents have a greater need to model other individuals in the group. [134] has introduced the concept of task coverage, which measures the ability of a given team member to achieve a given task. This parameter is an index of the demand for cooperation: when task coverage is high, tasks can be accomplished without much cooperation, but otherwise, cooperation is necessary. Task coverage is maximal in homogeneous groups, and decreases as groups become more heterogeneous (i.e., in the limit only one agent in the group can perform any given task).The literature is currently dominated by works that assume homogeneous groups of robots. How-ever, some notable architectures can handle het-erogeneity, e.g., ACTRESS and ALLIANCE (see Section 2.1 below). In heterogeneous groups, task allocation may be determined by individual capabilities, but in homogeneous systems, agents may need to differentiate into distinct roles that are either known at design-time, or arise dynamically at run-time.Communication Structures The communication structure of a group determines the possible modes of inter-agent interaction. We characterize three major types of interactions that can be sup-ported. ([50] proposes a more detailed taxonomy of communication structures). Interaction via environmentThe simplest, most limited type of interaction occurs when the environment itself is the communication medium (in effect, a shared memory),and there is no explicit communication or interaction between agents. This modality has also been called “cooperation without communication” by some researchers. Systems that depend on this form of interaction include [67], [24], [10], [151],[159], [160], [147].Interaction via sensing Corresponding to arms-length relationships inorganization theory [75], interaction via sensing refers to local interactions that occur between agents as a result of agents sensing one another, but without explicit communication. This type of interaction requires the ability of agents to distinguish between other agents in the group and other objects in the environment, which is called “kin recognition” in some literatures [108]. Interaction via sensing is indispensable for modeling of other agents (see Section 2.1.4 below). Because of hard-ware limitations, interaction via sensing has often been emulated using radio or infrared communications. However, several recent works attempt to implement true interaction via sensing, based on vision [95], [96], [154]. Collective behaviors that can use this kind of interaction include flocking and pattern formation (keeping in formation with nearest neighbors).Interaction via communicationsThe third form of interaction involves explicit communication with other agents, by either directed or broadcast intentional messages (i.e. the recipient(s) of the message may be either known or unknown). Because architectures that enable this form of communication are similar tocommunication networks, many standard issues from the field of networks arise, including the design of network topologies and communications protocols. For ex-ample, in [168] a media access protocol (similar to that of Ethernet) is used for inter-robot communication. In [78], robots with limited communication range communicate to each other using the “hello-call” protocol, by which they establish “chains” in order to extend their effective communication ranges. [61] describes methods for communicating to many (“zillions”) robots, including a variety of schemes ranging from broadcast channels (where a message is sent to all other robots in the system) to modulated retroreflection (where a master sends out a laser signal to slaves and interprets the response by the nature of the re-flection). [174] describes and simulates a wireless SMA/CD ( Carrier Sense Multiple Access with Collision Detection ) protocol for the distributed robotic systems.There are also communication mechanisms designed specially for multiple-robot systems. For example, [171] proposes the “sign-board” as a communication mechanism for distributed robotic systems. [7] gives a communication protocol modeled after diffusion, wherein local communication similar to chemical communication mechanisms in animals is used. The communication is engineered to decay away at a preset rate. Similar communications mechanisms are studied in [102], [49], [67].Additional work on communication can be found in [185], which analyzes optimal group sizes for local communications and communication delays. In a related vein, [186], [187] analyzes optimal local communication ranges in broadcast communication.Modeling of Other Agents Modeling the intentions, beliefs, actions, capabilities, and states of other agents can lead to more effective cooperation between robots. Communications requirements can also be lowered if each agent has the capability to model other agents. Note that the modeling of other agents entails more than implicit communication via the environment or perception: modeling requires that the modeler has some representation of another agent, and that this representation can be used to make inferences about the actions of the other agent.In cooperative robotics, agent modeling has been explored most extensively in the context of manipulating a large object. Many solutions have exploited the fact that the object can serve as a common medium by which the agents can model each other.The second of two box-pushing protocols in[45] can achieve “cooperation without commun ication” since the object being manipulated also functions as a “communication channel” that is shared by the robot agents; other works capitalize on the same concept to derive distributed control laws which rely only on local measures of force, torque, orientation, or distance, i.e., no explicit communication is necessary (cf. [153] [73]).In a two-robot bar carrying task, Fukuda and Sekiyama’s agents [60] each uses a probabilistic model of the other agent. When a risk threshold is exceeded, an agent communicates with its partner to maintain coordination. In [43], [44], the theory of information invariants is used to show that extra hardware capabilities can be added in order to infer the actions of the other agent, thus reducing communication requirements. This is in contrast to [147], where the robots achieve box pushing but are not aware of each other at all. For a more com-plex task involving the placement of five desks in[154], a homogeneous group of four robots share a ceiling camera to get positional information, but do not communicate with each other. Each robot relies on modeling of otheragents to detect conflicts of paths and placements of desks, and to change plans accordingly.Representative Architectures All systems implement some group architecture. We now de-scribe several particularly well-defined representative architectures, along with works done within each of their frameworks. It is interesting to note that these architectures encompass the entire spectrum from traditional AI to highly decentralized approaches.CEBOTCEBOT (Cellular roBOTics System) is a decentralized, hierarchical architecture inspired by the cellular organization of biological entities (cf.[59] [57], [162] [161] [56]). The system is dynamically reconfigurable in tha t basic autonomous “cells” (robots), which can be physically coupled to other cells, dynamically reconfigure their structure to an “optimal” configuration in response to changing environments. In the CEBOT hierarchy there are “master cells” that coordinate subtasks and communicate with other master cells. A solution to the problem of electing these master cells was discussed in [164]. Formation of structured cellular modules from a population of initially separated cells was studied in [162]. Communications requirements have been studied extensively with respect to the CEBOT architecture, and various methods have been proposed that seek to reduce communication requirements by making individual cells more intelligent (e.g., enabling them to model the behavior of other cells). [60] studies the problem of modeling the behavior of other cells, while [85], [86] present a control method that calculates the goal of a cell based on its previous goal and on its master’s goal. [58] gives a means of estimating the amount of information exchanged be-tween cells, and [163] gives a heuristic for finding master cells for a binary communication tree. Anew behavior selection mechanism is introduced in [34], based on two matrices, the priority matrix and the interest relation matrix, with a learning algorithm used to adjust the priority matrix. Recently, a Micro Autonomous Robotic System(MARS) has been built consisting of robots of 20cubic mm and equipped with infrared communications [121].ACTRESSThe ACTRESS (ACTor-based Robot and Equipments Synthetic System) project [16], [80],[15] is inspired by the Universal Modular AC-TOR Formalism [76]. In the ACTRESS system,“robotors”, including 3 robots and 3 workstations(one as interface to human operator, one as im-age processor and one as global environment man-ager), form a heterogeneous group trying to per-form tasks such as object pushing [14] that cannot be accomplished by any of the individual robotors alone [79], [156]. Communication protocols at different abstraction levels [115] provide a means upon which “group cast” and negotiation mechanisms based on Contract Net [150] and multistage negotiation protocols are built [18]. Various is-sues are studied, such as efficient communications between robots and environment managers [17],collision avoidance [19].SWARM。
欠驱动机器人 外文文献
One of the most sophisticated forms of legged motion is that of biped locomotion. From a dynamic systems point of view, human locomotion stands out among other forms of biped locomotion chiefly due to the fact that during a significant part of the human walking cycle the moving body is not in the static equilibrium. At the INRIA lab of Grenoble, France, we have started working on the development of an anthropomorphic biped walker. The envisioned prototype will have elementary adaptation capability on an unforeseen uneven terrain. The purpose of the project is not limited to the realization of a complex machine, the construction and control of which nevertheless pose formidable engineering challenge. We also intend to initiate a synergy between robotics and human gait study. Human locomotion, despite being well studied and enjoying a rich database, is not well understood and a robotic simulcrum potentially can be very useful. In order to gain a better understanding of the inherently non-linear dynamics of a full-fledged walking machine we have found it instructive to first explore the behavior of a particularly simple walker model.
机器人外文翻译(文献翻译_中英文翻译)
外文翻译外文资料：RobotsFirst, I explain the background robots, robot technology development. It should be said it is a common scientific and technological development of a comprehensive results, for the socio-economic development of a significant impact on a science and technology. It attributed the development of all countries in the Second World War to strengthen the economic input on strengthening the country's economic development. But they also demand the development of the productive forces the inevitable result of human development itself is the inevitable result then with the development of humanity, people constantly discuss the natural process, in understanding and reconstructing the natural process, people need to be able to liberate a slave. So this is the slave people to be able to replace the complex and engaged in heavy manual labor, People do not realize right up to the world's understanding and transformation of this technology as well as people in the development process of an objective need. Robots are three stages of development, in other words, we are accustomed to regarding robots are divided into three categories. is a first-generation robots, also known as teach-type robot, it is through a computer, to control over one of a mechanical degrees of freedom Through teaching and information stored procedures, working hours to read out information, and then issued a directive so the robot can repeat according to the people at that time said the results show this kind of movement again, For example, the car spot welding robots, only to put this spot welding process, after teaching, and it is always a repeat of a work It has the external environment is no perception that the force manipulation of the size of the work piece there does not exist, welding 0S It does not know, then this fact from the first generation robot, it will exist this shortcoming, it in the 20th century, the late 1970s, people started to study the second-generation robot, called Robot with the feeling that This feeling with the robot is similar in function of a certain feeling, forinstance, force and touch, slipping, visual, hearing and who is analogous to that with all kinds of feelings, say in a robot grasping objects, In fact, it can be the size of feeling out, it can through visual, to be able to feel and identify its shape, size, color Grasping an egg, it adopted a acumen, aware of its power and the size of the slide. Third-generation robots, we were a robotics ideal pursued by the most advanced stage, called intelligent robots, So long as tell it what to do, not how to tell it to do, it will be able to complete the campaign, thinking and perception of this man-machine communication function and function Well, this current development or relative is in a smart part of the concept and meaning But the real significance of the integrity of this intelligent robot did not actually exist, but as we continued the development of science and technology, the concept of intelligent increasingly rich, it grows ever wider connotations.Now, I would like to briefly outline some of the industrial robot situation. So far, the industrial robot is the most mature and widely used category of a robot, now the world's total sales of 1.1 million Taiwan, which is the 1999 statistics, however, 1.1 million in Taiwan have been using the equipment is 75 million, this volume is not small. Overall, the Japanese industrial robots in this one, is the first of the robots to become the Kingdom, the United States have developed rapidly. Newly installed in several areas of Taiwan, which already exceeds Japan, China has only just begun to enter the stage of industrialization, has developed a variety of industrial robot prototype and small batch has been used in production.Spot welding robot is the auto production line, improve production efficiency and raise the quality of welding car, reduce the labor intensity of a robot. It is characterized by two pairs of robots for spot welding of steel plate, bearing a great need for the welding tongs, general in dozens of kilograms or more, then its speed in meters per second a 5-2 meter of such high-speed movement. So it is generally five to six degrees of freedom, load 30 to 120 kilograms, the great space, probably expected that the work of a spherical space, a high velocity, the concept of freedom, that is to say, Movement is relatively independent of the number of components, the equivalent of our body, waist is a rotary degree of freedom We have to be able to hold his arm, Arm can be bent, then this three degrees of freedom, Meanwhile there is a wristposture adjustment to the use of the three autonomy, the general robot has six degrees of freedom. We will be able to space the three locations, three postures, the robot fully achieved, and of course we have less than six degrees of freedom. Have more than six degrees of freedom robot, in different occasions the need to configure.The second category of service robots, with the development of industrialization, especially in the past decade, Robot development in the areas of application are continuously expanding, and now a very important characteristic, as we all know, Robot has gradually shifted from manufacturing to non-manufacturing and service industries, we are talking about the car manufacturer belonging to the manufacturing industry, However, the services sector including cleaning, refueling, rescue, rescue, relief, etc. These belong to the non-manufacturing industries and service industries, so here is compared with the industrial robot, it is a very important difference. It is primarily a mobile platform, it can move to sports, there are some arms operate, also installed some as a force sensor and visual sensors, ultrasonic ranging sensors, etc. It’s surrounding environment for the conduct of identification, to determine its campaign to complete some work, this is service robot’s one of the basic characteristics.For example, domestic robot is mainly embodied in the example of some of the carpets and flooring it to the regular cleaning and vacuuming. The robot it is very meaningful, it has sensors, it can furniture and people can identify, It automatically according to a law put to the ground under the road all cleaned up. This is also the home of some robot performance.The medical robots, nearly five years of relatively rapid development of new application areas. If people in the course of an operation, doctors surgery, is a fatigue, and the other manually operated accuracy is limited. Some universities in Germany, which, facing the spine, lumbar disc disease, the identification, can automatically use the robot-aided positioning, operation and surgery Like the United States have been more than 1,000 cases of human eyeball robot surgery, the robot, also including remote-controlled approach, the right of such gastrointestinal surgery, we see on the television inside. a manipulator, about the thickness fingers such a manipulator, inserted through the abdominal viscera, people on the screen operating the machines hand, it also used the method of laser lesion laser treatment, this is the case, peoplewould not have a very big damage to the human body.In reality, this right as a human liberation is a very good robots, medical robots it is very complex, while it is fully automated to complete all the work, there are difficulties, and generally are people to participate. This is America, the development of such a surgery Lin Bai an example, through the screen, through a remote control operator to control another manipulator, through the realization of the right abdominal surgery A few years ago our country the exhibition, the United States has been successful in achieving the right to the heart valve surgery and bypass surgery. This robot has in the area, caused a great sensation, but also, AESOP's surgical robot, In fact, it through some equipment to some of the lesions inspections, through a manipulator can be achieved on some parts of the operation Also including remotely operated manipulator, and many doctors are able to participate in the robot under surgery Robot doctor to include doctors with pliers, tweezers or a knife to replace the nurses, while lighting automatically to the doctor's movements linked, the doctor hands off, lighting went off, This is very good, a doctor's assistant.Robot is mankind's right-hand man; friendly coexistence can be a reliable friend. In future, we will see and there will be a robot space inside, as a mutual aide and friend. Robots will create the jobs issue. We believe that there would not be a "robot appointment of workers being laid off" situation, because people with the development of society, In fact the people from the heavy physical and dangerous environment liberated, so that people have a better position to work, to create a better spiritual wealth and cultural wealth.译文资料：机器人首先我介绍一下机器人产生的背景，机器人技术的发展，它应该说是一个科学技术发展共同的一个综合性的结果，同时，为社会经济发展产生了一个重大影响的一门科学技术，它的发展归功于在第二次世界大战中各国加强了经济的投入，就加强了本国的经济的发展。
机器人外文翻译外文文献英文文献采用模糊逻辑控制使自主机器人避障设计
Autonomous robot obstacle avoidance using a fuzzy logic control schemeWilliam MartinSubmitted on December 4, 2009CS311 - Final Project1. INTRODUCTIONOne of the considerable hurdles to overcome, when trying to describe areal-world control scheme with first-order logic, is the strong ambiguity found in both semantics and evaluations. Although one option is to utilize probability theory in order to come up with a more realistic model, this still relies on obtaining information about an agent's environment with some amount of precision. However, fuzzy logic allows an agent to exploit inexactness in its collected data by allowing for a level of tolerance. This can be especially important when high precision or accuracy in a measurement is quite costly. For example, ultrasonic and infrared range sensors allow for fast and cost effective distance measurements with varying uncertainty. The proposed applications for fuzzy logic range from controlling robotic hands with six degrees of freedom1 to filtering noise from a digital signal.2 Due to its easy implementation, fuzzy logic control has been popular for industrial applications when advanced differential equations become either computationally expensive or offer no known solution. This project is an attempt to take advantage of these fuzzy logic simplifications in order to implement simple obstacle avoidance for a mobile robot. 2. PHYSICAL ROBOT IMPLEMENTATION2.1. Chassis and sensorsThe robotic vehicle's chassis was constructed from an Excalibur EI-MSD2003 remote control toy tank. The device was stripped of all electronics, gears, and extraneous parts in order to work with just the empty case and two DC motors for the tank treads. However, this left a somewhat uneven surface to work on, so high-density polyethylene (HDPE) rods were used to fill in empty spaces. Since HDPE has a rather low surface energy, which is not ideal for bonding with other materials, a propanetorch was used to raise surface temperature and improve bonding with an epoxy adhesive.Three Sharp GP2D12 infrared sensors, which have a range of 10 to 80 cm, were used for distance measurements. In order to mount these appropriately, a 2.5 by 15 cm piece of aluminum was bent into three even pieces at 135 degree angles. This allows for the IR sensors to take three different measurements at 45 degree angles (right, middle, and left distances). This sensor mount was then attached to an HDPE rod with mounting tape and the rod was glued to the tank base with epoxy. Since the minimum distance that can be reliably measured with these sensors is 10 cm, the sensors were placed about 9 cm from the front of the vehicle. This allowed measurements to be taken very close to the front of the robot.2.2. ElectronicsIn order to control the speed of each motor, pulse-width modulation (PWM) was used to drive two L2722 op amps in open loop mode (Fig. 1). The high input resistance of these ICs allow for the motors to be powered with very little power draw from the PWM circuitry. In order to isolate the motor's power supply from the rest of the electronics, a 9.6 V NiCad battery was used separately from a standard 9 V that demand on the op amps led to a small amount of overheating during continuous operation. This was remedied by adding small heat sinks and a fan to the forcibly disperse heat.Fig. 1. The control circuit used for driving each DC motor. Note that the PWM signal was between 0 and 5 V.2.3. MicrocontrollerComputation was handled by an Arduino Duemilanove board with anATmega328 microcontroller. The board has low power requirements and modifications. In addition, it has a large number of prototyping of the control circuit and based on the Wiring language. This board provided an easy and low-cost platform to build the robot around.3. FUZZY CONTROL SCHEME FORIn order to apply fuzzy logic to the robot to interpret measured distances. While the final algorithm depended critically on the geometry of the robot itself and how it operates, some basic guidelines were followed. Similar research projects provided both simulation results and ideas for implementing fuzzy control.3,4,53.1. Membership functionsThree sets of membership functions were created to express degrees of membership for distances, translational speeds, and rotational speeds. This made for a total of two input membership functions and eight output membership functions (Fig.2). Triangle and trapezoidal functions were used exclusively since they are quick to compute and easy to modify. Keeping computation time to a minimum was essential so that many sets of data could be analyzed every second (approximately one every 40 milliseconds). The distance membership functions allowed the distances from the IR sensors to be quickly "fuzzified," while the eight speed membership functions converted fuzzy values back into crisp values.3.2.Rule baseOnce the input data was fuzzified, the eight defined fuzzy logic rules (Table I) were executed in order to assign fuzzy values for translational speed and rotation. This resulted in multiple values for the each of the fuzzy output components. It was then necessary to take the maximum of these values as the fuzzy value for each component. Finally, these fuzzy output values were "defuzzified" using themax-product technique and the result was used to update each of the motor speeds.(a)(b)(c)rotational speed. These functions were adapted from similar work done in reference 3.4. RESULTSThe fuzzy control scheme allowed for the robot to quickly respond to obstacles itcould detect in its environment. This allowed it to follow walls and bend aroundcorners decently without hitting any obstacles. However, since the IR sensors'measurements depended on the geometry of surrounding objects, there were times when the robot could not detect obstacles. For example, when the IR beam hit a surface with oblique incidence, it would reflect away from the sensor and not register as an object. In addition, the limited number of rules used may have limited the dynamics of the robot's responses. Some articles suggest as many as forty rules6 should be used, while others tend to present between ten and twenty. Since this project did not explore complex kinematics or computational simulations of the robot, it is difficult to determineexactly how many rules should be used. However, for the purposes of testing fuzzy logic as a navigational aide, the eight rules were sufficient. Despite the many problems that IR and similar ultrasonic sensors have with reliably obtaining distances, the robustness of fuzzy logic was frequently able to prevent the robot from running into obstacles.5. CONCLUSIONThere are several easy improvements that could be made to future iterations of this project in order to improve the robot's performance. The most dramatic would be to implement the IR or ultrasonic sensors on a servo so that they could each scan a full 180 degrees. However, this type of overhaul may undermine some of fuzzy logic's helpful simplicity. Another helpful tactic would be to use a few types of sensors so that data could be taken at multiple ranges. The IR sensors used in this experiment had a minimum distance of 10 cm, so anything in front of this could not be reliably detected. Similarly, the sensors had a maximum distance of 80 cm so it was difficult to react to objects far away. Ultrasonic sensors do offer significantly increased ranges at a slightly increased cost and response time. Lastly, defining more membership functions could help improve the rule base by creating more fine tuned responses. However, this would again increase the complexity of the system.Thus, this project has successfully implemented a simple fuzzy control scheme for adjusting the heading and speed of a mobile robot. While it is difficult to determine whether this is a worthwhile application without heavily researching other methods, it is quite apparent that fuzzy logic affords a certain level of simplicity in thedesign of a system. Furthermore, it is a novel approach to dealing with high levels of uncertainty in real-world environments.6. REFERENCES1 Ed. M. Jamshidi, N. Vadiee, and T. Ross, Fuzzy logic and control: software and hardware applications, (Prentice Hall: Englewood Cliffs, NJ) 292-328.2 Ibid, 232-261.3 W. L. Xu, S. K. Tso, and Y. H. Fung, "Fuzzy reactive control of a mobile robot incorporating a real/virtual target switching strategy," Robotics and Autonomous Systems, 23(3), 171-186 (1998).4 V. Peri and D. Simon, “Fuzzy logic control for an autonomous robot,” 2005 Annual Meeting of the North American Fuzzy Information Processing Society, 337-342 (2005).5 A. Martinez, E. Tunstel, and M. Jamshidi, "Fuzzy-logic based collision-avoidance for a mobile robot," Robotica, 12(6) 521–527 (1994).6 W. L. Xu, S. K. Tso, and Y. H. Fung, "Fuzzy reactive control of a mobile robot incorporating a real/virtual target switching strategy," Robotics and Autonomous Systems, 23(3), 171-186 (1998).采用模糊逻辑控制使自主机器人避障设计威廉马丁提交于2009年12月4日CS311 -最终项目1 引言其中一个很大的障碍需要克服，当试图用控制逻辑一阶来描述一个真实世界设计在发现在这两个语义评价中是个强大的模糊区。
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步行机器人中英文对照外文翻译文献(文档含英文原文和中文翻译)图1 远程脑系统的硬件配置图2 两组机器人的身体结构图3 传感器的两个水银定位开关图4 层次分类图5 步行步态该输入处理器是作为参考程序块和一个图像搜索窗口形象该大小的搜索窗口取决于参考块的大小通常高达16 * 16且匹配。
该处理器计算价值块在搜索窗口，还找到最佳匹配块，这就是其中的最低当目标平移时块匹配是非常有力的。
然而，普通的块匹配方法当它旋转时无法跟踪目标。
为了克服这一困难，我们开发了一种新方法，跟随真正旋转目标的图6 双足步行图6 双足步行图7 双足步行实验图8 一系列滚动和站立运动通过集成传感器网络转型的综合为了使上述描述的基本动作成为一体，我们通过一种方法来描述一种被认为是根据传感器状况的网络转型。
图9显示了综合了基本动作机器人的状态转移图：两足行走，滚动，坐着和站立。
这种一体化提供了机器人保持行走甚至跌倒时的problems and advance the study of vision-based behaviors, we have adopted a new approach through building remote-brained robots. The body and the brain are connected by wireless links by using wireless cameras and remote-controlled actuators.As a robot body does not need computers on-board,it becomes easier to build a lightweight body with many DOFS in actuation.In this research, we developed a two-armed bipedal robot using the remote-brained robot environment and made it to perform balancing based on vision and getting up through cooperating arms and legs. The system and experimental results are described below.2 The Remote-Brained SystemThe remote-brained robot does not bring its own brain within the body. It leaves the brain in the mother environment and communicates with it by radio links. This allows us to build a robot with a free body and a heavy brain. The connection link between the body and the brain defines the interface between software and hardware. Bodies are designed to suit each research project and task. This enables us advance in performing research with a variety of real robot systems[10].A major advantage of remote-brained robots is that the robot can have a large and heavy brain based on super parallel computers. Although hardware technology for vision has advanced and produced powerful compact vision systems, the size of the hardware is still large. Wireless connection between the camera and the vision processor has been a research tool. The remote-brained approach allows us to progress in the study of a variety of experimental issues in vision-based robotics.Another advantage of remote-brained approach is that the robot bodies can be lightweight. This opens up the possibility of working with legged mobile robots. AsFigure 4 shows some of the classes in the programming environent for remote-brained robot written in Euslisp. The hierachy in the classes provides us with rich facilities for extending development of various robots.4 Vision-Based BalancingThe robot can stand up on two legs. As it can change the gravity center of its body by controling the ankle angles, it can perform static bipedal walks. During static walking the robot has to control its body balance if the ground is not flat and stable.In order to perform vision-based balancing it is re-quired to have high speed vision system to keep ob-serving moving schene. We have developed a tracking vision board using a correlation chip[l3]. The vision board consists of a transputer augmented with a special LSI chip(MEP[14] : Motion Estimation Processor) which performs local image block matching.The inputs to the processor MEP are an image as a reference block and an image for a search window.The size of the reference blsearch window depends on the size of the reference block is usually up to 32 by 32 pixels so that it can include 16 * 16 possible matches. The processor calculates 256 values of SAD (sum of absolute difference) between the reference block and 256 blocks in the search window and also finds the best matching block, that is, the one which has the minimum SAD value.Clock is up to 16 by 16 pixels.The size of the search window depends on the size of the reference block is usually up to 32 by 32 pixels so that it can include 16 * 16 possible matches. The processor calculates 256 values of SAD (sum of absolute difference) between the reference block and 256 blocks in the search window and also finds the best matching block, that is, the one which has the minimum SAD value.Block matching is very powerful when the target moves only in translation. However, the ordinary block matching method cannot track the target when it rotates. In order to overcome this difficulty, we developed a new method which follows up the candidate templates to real rotation of the target. The rotated template method first generates all the rotated target images in advance, and several adequate candidates of the reference template are selected and matched is tracking the scene in the front view. It remembers the vertical orientation of an object as the reference for visual tracking and generates several rotated images of the reference image. If the vision tracks the reference object using the rotated images, it can measures the body rotation. In order to keep the body balance, the robot feedback controls its body rotation to control the center of the body gravity. The rotational visual tracker[l5] can track the image at video rate.5 Biped WalkingIf a bipedal robot can control the center of gravity freely, it can perform biped walk. As the robot shown in Figure 2 has the degrees to left and right directions at the ankle position, it can perform bipedal walking in static way.The motion sequence of one cycle in biped walking consists of eight phases as shown in Figure 6. One step consists of four phases; move-gravity-center-on-foot,lift-leg, move-forward-leg, place-leg. As the body is described in solid model, the robot can generate a body configuration for move-gravity-center-on-foot according to the parameter of the hight of the gravity center. After this movement, the robot can lift the other leg and move it forward. In lifting leg, the robot has to control the configuration in order to keep the center of gravity above the supporting foot. As the stability in balance depends on the hight of the gravity center, the robot selects suitable angles of the knees.Figure 7 shows a sequence of experiments of the robot in biped walking6 Rolling Over and Standing UpFigure 8 shows the sequence of rolling over, sitting and standing up. This motion requires coordination between arms and legs.As the robot foot consists of a battery, the robot can make use of the weight of the battery for the roll-over motion. When the robot throws up the left leg and moves the left arm back and the right arm forward, it can get rotary moment around the body. If the body starts turning, the right leg moves back and the left foot returns its position to lie on the face. This rollover motion changes the body orientation from face up to face down. It canbe verified by the orientation sensor.After getting face down orientation, the robot moves the arms down to sit on two feet. This motion causes slip movement between hands and the ground. If the length of the arm is not enough to carry the center of gravity of the body onto feet, this sitting motion requires dynamic pushing motion by arms. The standing motion is controlled in order to keep the balance.7 Integration through Building Sensor-Based Transition NetIn order to integrate the basic actions described above, we adopted a method to describe a sensor-based transition network in which transition is considered according to sensor status. Figure 9 shows a state transition diagram of the robot which integrates basic actions: biped walking, rolling over, sitting, and standing up. This integration provides the robot with capability of keeping walking even when it falls down.The ordinary biped walk is composed by taking two states, Left-leg Fore and Right-leg Fore, successively.The poses in ‘Lie on the Back’ and ‘Lie on the Face’are as same as one in ‘Stand’. That is, the shape ofthe robot body is same but the orientation is different.The robot can detect whether the robot lies on the back or the face using the orientation sensor. When the robot detects falls down, it changes the state to ‘Lie on the Back’ or ‘Lie on the Front’ by moving to the neutral pose. If the robot gets up from ‘Lie on the Back’, the motion sequence is planned to exe cute Roll-over, Sit and Stand-up motions. If the state is ‘Lie on the Face’, it does not execute Roll-over but moves arms up to perform the sitting motion.8 Concluding RemarksThis paper has presented a two-armed bipedal robot which can perform statically biped walk, rolling over and standing up motions. The key to build such behaviors is the remote-brained approach. As the experiments have shown, wireless technologies permit robot bodies free movement. It also seems to change the way we conceptualize robotics. In our laboratory it has enabled the development of a new research environment, better suited to robotics and real-world AI.The robot presented here is a legged robot. As legged locomotion requires dynamic visual feedback control, its vision-based behaviors can prove the effectiveness of the vision system and the remote-brained system. Our vision system is based on high speed block matching function implemented with motion estimation LSI. The vision system provides the mechanical bodies with dynamic and adaptive capabilities in interaction with human. The mechanical dog has shown adaptive behaviors based on distance。