A fuzzy intelligent organiser for control of robotic assembly operations

Author

Son, Changman ; Vachtsevanos, George

Author_Institution

Sch. of Electr. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

fYear

1993

fDate

15-17 Dec 1993

Firstpage

1765

Abstract

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

Keywords

assembling; fuzzy control; fuzzy set theory; industrial robots; intelligent control; knowledge based systems; learning (artificial intelligence); robots; uncertainty handling; distance metric; expert system; force/moment data; fuzzy event probability; fuzzy intelligent organiser; fuzzy rule base; fuzzy set theory; learning algorithm; quasi-static assembly operation; robotic assembly operations; uncertainty; Expert systems; Force control; Force measurement; Fuzzy control; Fuzzy set theory; Intelligent control; Intelligent robots; Organizing; Robot control; Robotic assembly;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

San Antonio, TX

Print_ISBN

0-7803-1298-8

Type

conf

DOI

10.1109/CDC.1993.325492

Filename

325492