LEARNING CONTROL FOR ROBOT TASKS UNDER GEOMETRIC END-POINT CONSTRAINTS

A learning control scheme for a class of robot manipulators whose endp oint is moving under geometrical constraints on a surface is proposed. In this scheme, the input torque command is composed of two different signals updated separately at every trial by different ways. One is u pdated by the angular velocity error vector which is projected to the tangent plane of the constraint surface in joint space. The other is u pdated by the magnitude of contact force error at the manipulator endp oint. Not only the uniform boundedness of position and velocity trajec tory errors but also the uniform convergence of position and velocity trajectories to their desired ones with repeating practices are proved theoretically. In addition, it is shown that the contact force itself converges to the desired one in the sense of L(2)-norm with repeating practices. Computer simulation results by using a 3 DOF manipulator a re presented to demonstrate the effectiveness-of the proposed method a nd to examine the speed of convergence of force trajectories besides p osition and velocity trajectories.