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Dynamic Motion Planning using a distributed representation

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Abstract

Methods for dynamic motion planning are presented which take into account not only geometric environmental constraints but also physical constraints on motion. The approach uses a distributed representation which allows parallel implementation of the using a cellular strength-diffusion method in the search for the motion in space-time. We consider three cases: (1) no knowledge of the motion of the obstacles is assumed so that the planning is purely reactive; (2) full knowledge of the moving obstacles is available so that the planner can deliver an optimal motion; and (3) an interleaved algorithm in which the ability to predict a short time ahead (based on an assumption of simple linear motion of the obstacles) is exploited. This last algorithm emphasizes the importance of the interaction between the planner and the environment via sensors. We conclude that to plan motion in a dynamic environment in which uncertainties abound, the only sensible strategy is to constantly sense the world and plan the motion accordingly.

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Authors and Affiliations

  1. Department of Mechanical and Aerospace Engineering, Carleton University, K1S 5B6, Ottawa, Canada

    Chang Shu

  2. School of Cognitive and Computing Science, University of Sussex, BN1 9QH, Brighton, UK

    Hilary Buxton

Authors
  1. Chang Shu
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  2. Hilary Buxton
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Additional information

The experimental work reported here was carried out while the authors were at Department of Computer Science, Queen Mary and Westfield College, University of London.

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Shu, C., Buxton, H. Dynamic Motion Planning using a distributed representation. J Intell Robot Syst 14, 241–261 (1995). https://doi.org/10.1007/BF01258351

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  • DOI: https://doi.org/10.1007/BF01258351

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