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A fuzzy intelligent organiser for control of robotic assembly operations

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2 Author(s)
Changman Son ; Sch. of Electr. Eng., Georgia Inst. of Technol., Atlanta, GA, USA ; G. Vachtsevanos

A fuzzy intelligent organizing control strategy, based on a fuzzy rule base and derived from measured force/moment data, for a quasi-static assembly operation is presented. Fuzzy set theory is implemented as an expert system to constitute the organizer of a robotic system for micro-tasking (part mating) purposes. A distance metric is employed to measure the uncertainty (fuzziness) of the fuzzy set as it is related to specific control actions. A learning algorithm based on the probability of a fuzzy event is introduced. The top organizing level determines the most appropriate pair of control values with minimum fuzziness and feeds this to the lower level of the system to carry out the specified task. Simulation results show the effectiveness of the proposed approach

Published in:

Decision and Control, 1993., Proceedings of the 32nd IEEE Conference on

Date of Conference:

15-17 Dec 1993