基于任务函数方法的机器人视觉伺服特性研究

为实现在统一的理论框架下对机器人视觉伺服基础特性进行细致深入的研究,本文基于任务函数方法,建立了广义的视觉伺服系统模型.在此模型基础之上,重点研究了基于位置的视觉伺服(PBVS)与基于图像的视觉伺服(IBVS)方法在笛卡尔空间和图像空间的动态特性.仿真结果表明,在相同的比较框架结构下,PBVS方法同样对摄像机标定误差具有鲁棒性.二者虽然在动态系统的稳定性、收敛性方面相类似,但是在笛卡尔空间和图像空间的动态性能上却有很大的差别.对于PBvS方法,笛卡尔轨迹可以保证最短路径,但是对应的图像轨迹是不可控的,可能会发生逃离视线的问题;对于IBVS方法,图像空间虽然能保证最短路径,但是由于缺乏笛卡尔空间的直接控制,在处理大范围旋转伺服的情况时,会发生诸如摄像机退化的笛卡尔轨迹偏移现象.

Study of visual servo-performance of robots based on task function

To study the visual servo-performance of a robot on a common theoretical basis, a generalized visual servosystem model is proposed based on the task function method. The dynamic performance of the position-based visual servoing(PBVS) and the image-based visual servoing(IBVS) in the Cartesian space and the image spaces are investigated respectively based on this model. Simulation results show that both the PBVS method and the IBVS method are robust to the camera calibration errors; and are comparable in stability and convergence. However, their dynamic performances are greatly different. For the PBVS method, the shortest Cartesian trajectory can be achieved, but the camera field of view may be lost because the corresponding image trajectories are not controlled. On the other hand, for the IBVS method, the shortest image trajectory can be achieved, but the Cartesian trajectory will deviate from the shortest one due to the lack of direct control in Cartesian space. Especially, when the servo system performs a large rotation with respect to the camera frame, even the camera retreat may occur.