Shadoks Approach to Low-Makespan Coordinated Motion Planning (CG Challenge)

Authors Loïc Crombez , Guilherme D. da Fonseca , Yan Gerard , Aldo Gonzalez-Lorenzo , Pascal Lafourcade , Luc Libralesso



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Loïc Crombez
  • Université Clermont-Auvergne and LIMOS, France
Guilherme D. da Fonseca
  • Aix Marseille Université and LIS, France
Yan Gerard
  • Université Clermont-Auvergne and LIMOS, France
Aldo Gonzalez-Lorenzo
  • Aix Marseille Université and LIS, France
Pascal Lafourcade
  • Université Clermont-Auvergne and LIMOS, France
Luc Libralesso
  • Université Clermont-Auvergne and LIMOS, France

Acknowledgements

We would like to thank Hélène Toussaint, Raphaël Amato, Boris Lonjon, and William Guyot-Lénat from LIMOS, as well as the Qarma and TALEP teams and Manuel Bertrand from LIS, who continue to make the computational resources of the LIMOS and LIS clusters available to our research. We would also like to thank the challenge organizers and other competitors for their time, feedback, and making this whole event possible.

Cite As Get BibTex

Loïc Crombez, Guilherme D. da Fonseca, Yan Gerard, Aldo Gonzalez-Lorenzo, Pascal Lafourcade, and Luc Libralesso. Shadoks Approach to Low-Makespan Coordinated Motion Planning (CG Challenge). In 37th International Symposium on Computational Geometry (SoCG 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 189, pp. 63:1-63:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.SoCG.2021.63

Abstract

This paper describes the heuristics used by the Shadoks team for the CG:SHOP 2021 challenge on motion planning. Using the heuristics outlined in this paper, our team won first place with the best solution to 202 out of 203 instances and optimal solutions to at least 105 of them.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
  • Computing methodologies → Motion path planning
Keywords
  • heuristics
  • motion planning
  • digital geometry
  • shortest path

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References

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