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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  and
P. Bidaud
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)
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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.

Keywords

Robot gripperControl systemCompliant devicePeg-in-hole
Type
Article
Information
Robotica , Volume 12 , Issue 2 , March 1994 , pp. 187 - 192
Copyright
Copyright © Cambridge University Press 1994

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References

1.Kerr, J.R., “An analysis of mutli-fingered hands” Ph.D. Thesis (Stanford University, 12., 1984).Google Scholar
2.Ji, Z. and Roth, B., “Direct computation of grasping forces for three-finger tip-prehension grasp” J. Mechanisms, Transmissions and Automation in Design 110, No. 4, 405–413 (12., 1988).CrossRefGoogle Scholar
3.Romdhane, L. and Duffy, L., “Kinestatic Analysis of multi-fingered hands”, Int. J. Robotics Research 9, 3–18 (1990).CrossRefGoogle Scholar
4.Podhorodeski, R.P., Goldenberg, A.A. and Fenton, R.G., “Analytical bases for contact forces leading to internal forces for point friction contact grasps” Conf. on Applied Mechanism and Robotics, Cincinnati 122–127 (11. 1990).Google Scholar
5.Erdmann, M., “Using Back projection for Motion Planning with uncertanty” Int. J. Robotics Research 5, No. 1, 19–45 (1986).CrossRefGoogle Scholar
6.Lozano-Perez, T., Mason, M.T. and Taylor, R.H., “Automatic synthesis of fine-motion strategies for robots” Int. J. of Robotics Research 3, No. 1, 3–24 (1984).CrossRefGoogle Scholar
7.Laugier, C., “Traitement des incertitudes en programration automatique des robots” Rapport de Recherche No. 933. INRIA (12., 1988).Google Scholar
8.Brooks, R.A., “Symbolic Error Analysis and Robot Planning”, Int. J. Robotics Research 4, 29–68 (1982).CrossRefGoogle Scholar
9.Dufay, B. and Latombe, J.C., “An approach to Automatic Robot Programming Based on Inductive Learning” Int. J. Robotics Research 3, No. 4, 3–20 (1984).CrossRefGoogle Scholar
10.Xiao, J. and Voltz, R.A., “Design and motion constraints of part mating planning in the presence of uncertainties” Proc. IEEE Conf. Robotics and Automation (1988) pp. 1260–1268.Google Scholar
11.Bidaud, P. et al., “Application of a manipulator-gripper in an assembly cell”, Proc IEEE Conf. on Robotics and Automation, (1987) pp. 2021–2032.Google Scholar
12.Englemore, R. and Morgan, T., Blackboards Systems (Addison-Wesley, Reading, MA, 1988).Google Scholar
13.Caneghem, M. Van, L'Anatomie de Prolog (Intereditions, Paris86).Google Scholar
14.Bidaud, P. and Fontaine, D., “Programming and control of a two-hand assembly system” Int. J. Robotics and Computer Integrated Manufacturing 6, 89 (1987).Google Scholar
15.NIlsson, N., Principles of Artificial Intelligence (Tioga Publishing Company, Palo Alto, California 1980).Google Scholar