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Design and implementation of an inductive learning control system for a manipulator gripper

Published online by Cambridge University Press:  09 March 2009

D. Fontaine
Affiliation:
Laboratoire de Robotique de Paris, CNRS, Université de Paris 6, ENSAM, Tour 66, 4 Place Jussieu, 75252 Paris Cedex 05(France)
P. Bidaud
Affiliation:
Laboratoire de Robotique de Paris, CNRS, Université de Paris 6, ENSAM, Tour 66, 4 Place Jussieu, 75252 Paris Cedex 05(France)

Summary

This paper presents an advanced control system for an active compliant device. This device, a manipulator-gripper, was designed to achieve stable grasp of objects with various shapes and to impart compliant fine motions to the grasped object. In the control system of this end-effector, we introduced autonomous reasoning capabilities. Fine motion strategies, needed for mating or grasping, use inductive learning from experiments to achieve uncertainty and error recovery. An overview of the articulated gripper's structure is provided for a better understanding of the programming environment we propose. For solving the problem of synthesis programs for fine motion planning we introduce declarative programming facilities in the controller through a time-sensitive mini-prolog. The paper gives some details on the implementation of this mini-prolog. We develop a heuristic procedure to obtain an implicit local model of contacts in complex assembly tasks. Finally, a specific example of this approach – a peg-in-hole operation– –is outlined.

Type
Article
Copyright
Copyright © Cambridge University Press 1994

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