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Precedence knowledge acquisition for generating robot assembly sequences

C. L. Philip Chen

Year
2003
Citations
2

Abstract

An approach for obtaining precedence knowledge of n parts for generating all the feasible assembly sequences to construct a mechanical object is presented. Generally, to generate all the assembly sequences, the precedence-logical forms are obtained from the answers regarding the relation between pairs of parts consecutively asked about a design engineer, and the assembly sequences are deduced by logic induction. Previous work has shown that the question-answer pattern requires 2l operations (where l is total number of the liaisons and bound between n-l and (n/sup 2/-n)/2). The author proposes an efficient method and pattern-matching operation to obtain precedence relationships of parts. This approach results in only l questions to be answered to obtain such knowledge. For a special case with one-fixture assembly system, the question-answer format only requires n questions to be answered, resulting in a reduction of order of complexity. Detailed algorithms, analysis, and examples are presented to show the effectiveness of the proposed scheme.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Keywords

Computer scienceConstruct (python library)Relation (database)Object (grammar)RobotMatching (statistics)Scheme (mathematics)Artificial intelligenceTheoretical computer scienceAlgorithm

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