An SPN-Neural Planning Methodology for Coordination of two Robotic Hands with Constrained Placement

  • Authors:

  • Nikolaos Bourbakis;Anya Tascillo

  • Affiliations:

  • Binghamton University, School of Engr., Center for Intelligent Systems, Binghamton NY 13902, U.S.A.;Ford Corporation, Computer Science Research Lab, Detroit, MI, U.S.A.

  • Venue:
  • Journal of Intelligent and Robotic Systems
  • Year:
  • 1997

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Abstract

This paper presents a planning methodology based on Stochastic Petri Nets (SPNs) and Neural nets for coordination of two robotic arms working in a space with constrained placement. The SPN planning method generates a global plan based on the states of the elements of the Universe of Discourse. The plan includes all the possible conflict-free planning paths to achieve the goals under constraints, such as specific locations on which objects have to be placed, order of placement, etc. An associated neural network is used to search the vectors of markings generated by the SPN reachability graph for the appropriate selection of plans. Moreover, it preserves all the interesting features of the SPN model, such as synchronization, parallelism, concurrency and timing of events. The coordination of two robotic arms is used as an illustrative example for the proposed planning method, in a UD space where the location of objects placement are restricted.