Adaptive Jacobian Tracking Control of Robots based on Visual Task-space Information

Most research so far on trajectory tracking control of robot has assumed that the kinematics of the robot is known exactly. This paper extends our recent work on adaptive Jacobian tracking control by deriving a new algorithm for trajectory tracking of robots with uncertain kinematics and dynamics. The algorithm requires only to measure the end-effector position in visual space, besides the robot’s joint angles and joint velocities. Experimental results are presented to illustrate the performance of the proposed controllers. In the experiments, we demonstrate that the robot’s shadow can be used to control the robot.