A knowledge based planning system for mechanical assembly usign robots

  • Authors:

  • Kai-Hsiung Chang;William G. Wee

  • Affiliations:

  • Department of Electrical and Computer Engineering, ML #30, University of Cincinnati, Cincinnati, Oh;Department of Electrical and Computer Engineering, ML #30, University of Cincinnati, Cincinnati, Oh

  • Venue:
  • DAC '85 Proceedings of the 22nd ACM/IEEE Design Automation Conference
  • Year:
  • 1985

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Abstract

This paper describes an approach to generate task level plans for mechanical assembly using robots. The system generates assembly plans by inferring from the knowledge base of workpiece structures, assembly rules, and robot operations. The novel feature of the system is its goal (workpiece) structure analysis. The goal structure analysis is capable of producing a correctly ordered sequence of subgoals such that the interactions among the subgoals will not interfere with achieving the goal. A plan generator then follows the analysis information to select the appropriate robot operations to formulate the final plan without much searching and reasoning. We believe that this goal-analyzing approach is much closer to human-like planning model than other interaction-resolving planning systems.