Visual tracking of robots in uncalibrated environments

This paper presents a new adaptive controller for visual tracking control of a robot manipulator in 3D general motion with a fixed camera whose intrinsic and extrinsic parameters are uncalibrated. In addition to camera parameters, the feature positions in 3D space are also assumed unknown. Based on the fact that the unknown parameters appears linearly in the closed-loop dynamics of the system if the depth-independent interaction matrix is adopted to map the image errors onto the joint space of the manipulator, we developed a new adaptive algorithm to estimated the unknown parameters on-line. With a full consideration of dynamic responses of the robot manipulator, we employ the Lyapunov method to prove asymptotic convergence of the image errors. Experimental results are used to demonstrate the performance of the proposed approach.