A fuzzy expert organizer for control of robotic part assembly

Author

Son, Changman ; Vachtsevanos, George

Author_Institution

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

fYear

1993

fDate

1-3 Dec 1993

Firstpage

97

Lastpage

102

Abstract

A fuzzy intelligent organizing control strategy, based on a fuzzy rule-base and derived from measured force/moment data, for a robotic device performing quasi-static assembly tasks 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) as it is related to specific control actions. A learning algorithm based on the probability of a fuzzy event and a distance metric is introduced. The top organizing level determines the most appropriate n-tuple control values with minimum fuzziness and downlinks them to the lower level of the system which carries out the specified task. Experimental results show the effectiveness of the proposed approach

Keywords

assembling; expert systems; fuzzy control; fuzzy set theory; intelligent control; probability; robots; uncertainty handling; distance metric; expert system; fuzziness; fuzzy event probability; fuzzy expert organizer; fuzzy intelligent organizing control; fuzzy rule base; fuzzy set theory; learning algorithm; part mating; robotic part assembly; uncertainty; Force control; Force measurement; Fuzzy control; Fuzzy set theory; Intelligent control; Intelligent robots; Organizing; Performance evaluation; Robot control; Robotic assembly;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Fuzzy Control and Intelligent Systems, 1993., IFIS '93., Third International Conference on

Conference_Location

Houston, TX

Print_ISBN

0-7803-1485-9

Type

conf

DOI

10.1109/IFIS.1993.324206

Filename

324206