基于仿生眼的无人机视觉跟踪云台摄像机控制系统(英文)

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Abstract - Firstly, the characteristics of UAV visual tracking system were analysed, secondly the three-dimensional oculomotor control system model of biomimetic eye was developed based on the oculomotor neural paths. Then a new UAV visual tracking system was established. The on-board pantilt camera control system based on biomimetic eye can compensate the deflection caused by the UAV rotation and the movement of ground relative to the UAV. The pan-tilt camera can simulate human eye movements including smooth pursuit, VOR and OKR, and the control pattern of camera motor is velocity control, thus it can track the ground moving target continuously, smoothly, clearly and stably like human eye. Finally the experimental results were presented.
camera view and the tracking is not smooth. Therefore, the better control method needs to be used to enhance the system performance. Bionics studies simulating the principles of biologic system principles to build advanced technology systems or enable the artificial technology systems have some characteristics or functions of biologic system [6]. In this paper, the on-board pan-tilt control system based on biomimetic eye is mainly researched, and then a new UAV visual tracking system is present.
II. CHARACTERISTICS OF TRACKING SYSTEM
Index Terms - biomimetic eye; oculomotor control; pan-tilt camera control; UAV; visual tracking.
I. INTRODUCTION
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The UAV visual tracking system is a real-time control system that the unmanned aerial vehicle (UAV) automatically adjust its flight attitude, the rolling angle and pitching angle of the pan-tilt camera using the image data from the on-board camera so that the tracked ground moving target can be maintained its position in the middle of the image, the tracking image and the position data are transmitted to the ground command center simultaneously. It has broad application prospect in the military attack, the anti-terrorist & anti-riot, and the civil aspect, thus it is given their great attentions by many countries in the world. The UAV visual tracking system relates to many knowledge such as the image processing, the computer vision, the flight mechanics, the automatic control, the machinery, the electronics and so on, so it is a complex system. In the domestic and foreign existing research, its research focus is always concentrated in the aspect of image processing [1-5], which mainly is the method of moving target detection and image matching, the computation of target dimensional position, and the algorithm of predictive tracking. However, the attitude change of UAV is compensated only through applying the image processing method such as affine transformation algorithm, the compensating scope is very small, and the speed of calculation is slow. The pan-tilt camera control only uses the negative feedback control or the switch control, and the control pattern of camera motor is position control, so that the tracking speed of the on-board camera is very slow, the target may easily run away from the
Hairong Zou, Zhenbang Gong, Shaorong Xie and Wei Ding Department ofPrecision Mechanical Automation
Shanghai University No. 149, Yanchang Rd., Shanghai 200072, China
Proceedings of the 2006 IEEE International Conference on Robotics and Biomimetics December 17 - 20, 2006, Kunming, China
A Pan-tilt Camera Control System of UAV Visual Tracking Based on Biomimetic Eye
In the UAV visual tracking system, the UAV, the onboard camera and the ground target are all in motion. Therefore, the system has the following characteristics. Firstly, UAV is inherently unstable and capable of exhibiting high acceleration rates, in addition there are the engine vibration and the wind, thus the image from the onboard camera is very unstable. Moreover, the image can't be processed using normal spatio-temporal filtering of the camera image sequence for estimation of local motion. Next, the system demands high-performance real-time processing. But UAV has limited on-board power and payload capacity, so that it limits the usage of the on-board hardware. Thus, the new appropriate hardware must be designed; meanwhile, the adaptive robust algorithm must be introduced. The vision and the control system must be compact, efficient, and lightweight for effective on-board integration. Thirdly, the on-board camera is always in motion, the distance and direction between the on-board camera and ground moving target change constantly, so the existing target recognition and tracking method, which fit for the image from the static camera, is no longer suitable. It is insufficient to only control the camera for UAV visual tracking system. The rolling angle and pitching angle of the on-board camera are requested to be extremely accurate. Once the angle has a tiny deflection, the target may be lost. Moreover, the flight attitude seriously influences the view of the on-board camera. The stable tracking must coordinate to ontrol the flight attitude of UAV and the movement of the onboard camera.