Title :
Robots repositioning by learning
Author :
Lucibello, Pasquale
Author_Institution :
Dipartimento di Inf. e Sistemistica, La Sapienza Univ., Rome, Italy
Abstract :
Learning algorithms have been introduced by other authors for dealing with trajectory tracking and hybrid force control of rigid robots. In some instances, however, instead of trajectory tracking, repositioning is required. This task cannot be robustly implemented by trajectory tracking. In this paper the authors introduce finite memory algorithms for moving rigid robots between equilibrium points
Keywords :
convergence; learning (artificial intelligence); position control; robots; equilibrium points; finite memory algorithms; hybrid force control; learning algorithms; repositioning; rigid robots; trajectory tracking; Acceleration; Actuators; Equations; Error correction; Force control; Kinematics; Orbital robotics; Robots; Robustness; Trajectory;
Conference_Titel :
Decision and Control, 1993., Proceedings of the 32nd IEEE Conference on
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-1298-8
DOI :
10.1109/CDC.1993.325678
