Performance in Adaptive Manipulator Control

TLDR

Adaptive controller designs can combine high speed and precision while simplifying programming by maintaining performance amid large load or task variations. The article investigates the performance of a computationally efficient adaptive manipulator controller by developing a recursive implementation for open and closed kinematic chains and minimal parametrization rules. The recursive implementation operates in Cartesian space, exploits kinematic redundancies, and supports adaptive compliant motion control. Experimental results on a four‑degree‑of‑freedom articulated robot arm demonstrate the controller’s global tracking convergence and suggest broad applicability beyond load‑adaptation tasks.

Abstract

Effective adaptive controller designs potentially combine high speed and high precision in robot manipulation and further more can considerably simplify high-level programming by providing consistent performance in the face of large varia tions in loads or tasks. A simple, globally tracking-conver gent, direct adaptive manipulator controller has previously been developed and experimentally demonstrated. In this article, we further explore the performance issues linked to a computationally effective implementation. Specifically, we develop a recursive implementation applicable to both open and closed kinematic chains, as well as rules for obtaining minimal parametrizations. We also discuss implementations of the algorithm directly in Cartesian space, the exploitation of kinematic redundancies, and applications to adaptive compliant motion control. These developments are illustrated experimentally on a four-degrees-of-freedom articulated robot arm and suggest a wide range of application well beyond adaptation to grasped loads.