A Bio-Inspired Sensory-Motor Neural Model for a Neuro-Robotic Manipulation Platform
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A Bio-Inspired Sensory-Motor Neural Model for a
Neuro-Robotic Manipulation Platform Gioel Asuni∗,Giancarlo Teti∗,Cecilia Laschi∗,Eugenio Guglielmelli§and Paolo Dario∗
∗ARTS Lab(Advanced Robotics Technology and System Laboratory)
Scuola Superiore Sant’Anna,Piazza Martiri della Libert`a33,56127Pisa,Italy
Email:{asuni,teti,cecilia,dario}@arts.sssup.it
§Laboratory of Biomedical Robotics&EMC
Universit`a Campus Bio-Medico,via Longoni83,00155Rome,Italy
Email:e.guglielmelli@unicampus.it
Abstract—This paper presents a neural model for visuo-motor coordination of a redundant robotic manipulator in reaching tasks.The model was developed for,and experimentally validated on,a neurobotic platform for manipulation.The proposed ap-proach is based on a biologically-inspired model,which replicates the human brain capability of creating associations between motor and sensory data,by learning.The model is implemented here by self-organizing neural maps.During learning,the system creates relations between the motor data associated to endoge-nous movements performed by the robotic arm and the sensory consequences of such motor actions,i.e.thefinal position of the end effector.The learnt relations are stored in the neural map structure and are then used,after learning,for generating motor commands aimed at reaching a given point in3D space.The approach proposed here allows to solve the inverse kinematics and joint redundancy problems for different robotic arms,with good accuracy and robustness.In order to validate this,the same implementation has been tested on a PUMA robot,too. Experimental trials confirmed the system capability to control the end effector position and also to manage the redundancy of the robotic manipulator in reaching the3D target point even with additional constraints,such as one or more clamped joints,tools of variable lengths,or no visual feedback,without additional learning phases.
I.I NTRODUCTION
Biologically-inspired approaches are widely adopted in ro-botics,for the development of bio-mimetic components,as well as new control models,for biomorphic robotic platforms [1].In these approaches,biology represents an inspiration source,which dramatically affects and contributes to the design phase.The advances of robotics technology,related in part to the adoption of such bio-inspired approaches in robot design,are opening new opportunities for the application of robotics in biological research as well.For instance,the development of biomimetic robotic systems and anthropomor-phic robots(or humanoids)undoubtedly provides insight into the animals they are inspired from.In a wider general line, building a bioinspired robot helps to better understand the relying biology.Humanoids can then be seen as a tool in the study of humans,especially in neuroscience,but also in neurophysiology,physiology,and psychology.In addition to this,humanoids,and biomorphic robots in general,can be used for validating the biological models they implement and for carrying out experiments that may be difficult or impossible with human beings or animals.
Therefore,the interaction between biological science and robotics becomes two-fold[2],[3]:on one hand,biology provides the knowledge of the human system needed to build humanoid robots(or human-like components)[4];on the other hand,anthropomorphic robots represent a helpful platform for experimental validation of theories and hypotheses formulated by scientists[5].This second line of research is referred to as Neuro-Robotics[6].Neuro-robotic systems are designed by a biomechatronic approach,in order to have biomorphic features,to the extent that they significantly replicate human properties in focused neuroscience experiments.
The biomechatronic design approach and the neuro-robotics design goal make neurorobotic platforms complex,sophisti-cated in the sensory-motor functions,and intrinsically prone to being adaptable,flexible,and evolutionary,as biological systems are.Controlling this kind of systems is not just a problem of robot control but a problem of complex sensory-motor coordination.But at the same time,the neuro-robotic application provides roboticists with biological models that can be adopted for realizing such complex sensory-motor coordination.
The authors developed a neuro-robotic platform for grasping and manipulation(ARTS humanoid)[7],which mimics human mechanisms of perception and action,and can implement neuro-physiological models of sensory-motor coordination. The resulting system is composed of sensors and actuators replicating some level of anthropomorphism,in the physical structure and/or in the functionality.
The ARTS humanoid is a1-link trunk which supports one arm/hand system and a neck/head system(see Fig.5). The2-dof trunk is part of the arm(DEXTER arm,by S.M. Scienzia Machinale srl,Pisa,Italy)which has in total8 dofs,and integrates the4motors of the three-fingered hand on the forearm.The hand has anthropomorphic dimensions and weight[8].Eachfinger consists of3underactuated dofs driven by a single cable allowingflexion/extension.In total the hand has10dofs,6of which are underactuated.The perception system of the hand includes proprioceptive and exteroceptive sensory systems[9],and in particular:9position