Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Heuristics for Motion Planning Based on Learning in Similar Environments

  • Ogay, Dmitriy (Department of Computer Science & Engineering, Graduate School, Korea University of Technology and Education) ;
  • Kim, Eun-Gyung (School of Computer Science & Engineering, Korea University of Technology and Education)
  • Received : 2013.12.03
  • Accepted : 2014.02.17
  • Published : 2014.06.30
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Abstract

This paper discusses computer-generated heuristics for motion planning. Planning with many degrees of freedom is a challenging task, because the complexity of most planning algorithms grows exponentially with the number of dimensions of the problem. A well-designed heuristic may greatly improve the performance of a planning algorithm in terms of the computation time. However, in recent years, with increasingly challenging high-dimensional planning problems, the design of good heuristics has itself become a complicated task. In this paper, we present an approach to algorithmically develop a heuristic for motion planning, which increases the efficiency of a planner in similar environments. To implement the idea, we generalize modern motion planning algorithms to an extent, where a heuristic is represented as a set of random variables. Distributions of the variables are then analyzed with computer learning methods. The analysis results are then utilized to generate a heuristic. During the experiments, the proposed approach is applied to several planning tasks with different algorithms and is shown to improve performance.

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