Adaptive Manipulator Control: Parameter Convergence and Task-Space Strategies

Abstract

Earlier work (Slotine and Li, 1986) shows that using state feedback to directly modify a manipulator's energy function, rather than its fully expanded dynamics, represents a powerful approach to robot control, and, in particular, yields a simple globally convergent adaptive algorithm for trajectory control problems. The approach is demonstrated experimentally in (Slotine and Li, 1987) on a high-speed, semi-direct-drive manipulator. An important practical feature of the algorithm is that is does not require measurements or estimates of the manipulator's joint accelerations. This paper studies richness conditions on the desired trajectories for the unknown parameters to converge to their exact values. It also discusses formulations of the algorithm directly in task-space, and applications to the external motion control of unknown passive mechanisms.