Vision-based robotic tracking of moving object with dynamic uncertainty

This paper presents a new controller for locking a moving object in 3-D space at a particular position (for example the center) on the image plane of a camera mounted on a robot by actively moving the camera. The controller is designed to cope with both unknown robot dynamics parameters and unknown motion of the object. Based on the fact that the unknown position of the moving object appears linearly in the closed-loop dynamics of the system if the depth-independent image Jacobian is used, we developed a nonlinear observer to estimate the 3-D motion of the object on-line and an adaptive algorithm to estimate the robot dynamic parameters. With a full consideration of dynamic responses of the robot, we employed the Lyapunov method to prove asymptotic convergence of the image errors. Experimental results are presented to support the approach in this paper.