About: Unsupervised Learning of Growing Roadmap in Multi-Goal Motion Planning Problem     Goto   Sponge   NotDistinct   Permalink

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Description
  • In this paper, we address the multi-goal motion planning problem in which it is required to determine an order of visits of a pre-specified set of goals together with the shortest trajectories connecting the goals. The considered problem is inspired by inspection planning missions, where multiple goals must be visited with a required precision. The problem combines challenges of the combinatorial traveling salesman problem with difficulties of the motion planning. The presented approach is based on unsupervised learning of the self-organizing map technique for the traveling salesman problem applied in the configuration space. This learning technique takes an advantage of acquiring information about exploring the configuration space into a topology of the map that is simultaneously exploited in determination of the multi-goal trajectory and further directions of motion planning roadmap expansion. Presented results indicate that the proposed approach is feasible and it is able to provide a solution of the multi-goal motion planning problem without a priori known sequence of the goals visits.
  • In this paper, we address the multi-goal motion planning problem in which it is required to determine an order of visits of a pre-specified set of goals together with the shortest trajectories connecting the goals. The considered problem is inspired by inspection planning missions, where multiple goals must be visited with a required precision. The problem combines challenges of the combinatorial traveling salesman problem with difficulties of the motion planning. The presented approach is based on unsupervised learning of the self-organizing map technique for the traveling salesman problem applied in the configuration space. This learning technique takes an advantage of acquiring information about exploring the configuration space into a topology of the map that is simultaneously exploited in determination of the multi-goal trajectory and further directions of motion planning roadmap expansion. Presented results indicate that the proposed approach is feasible and it is able to provide a solution of the multi-goal motion planning problem without a priori known sequence of the goals visits. (en)
Title
  • Unsupervised Learning of Growing Roadmap in Multi-Goal Motion Planning Problem
  • Unsupervised Learning of Growing Roadmap in Multi-Goal Motion Planning Problem (en)
skos:prefLabel
  • Unsupervised Learning of Growing Roadmap in Multi-Goal Motion Planning Problem
  • Unsupervised Learning of Growing Roadmap in Multi-Goal Motion Planning Problem (en)
skos:notation
  • RIV/68407700:21230/14:00224911!RIV15-MSM-21230___
http://linked.open...avai/riv/aktivita
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  • P(GP13-18316P), S
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  • 52044
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  • RIV/68407700:21230/14:00224911
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  • Motion planning; Traveling salesman problem (en)
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  • [08D1400E5BAB]
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  • Faigl, Jan
  • Vokřínek, Jiří
  • Vaněk, Petr
http://localhost/t...ganizacniJednotka
  • 21230
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