License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.SoCG.2021.65
URN: urn:nbn:de:0030-drops-138649
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Yang, Hyeyun ; Vigneron, Antoine

A Simulated Annealing Approach to Coordinated Motion Planning (CG Challenge)

LIPIcs-SoCG-2021-65.pdf (0.7 MB)


The third computational geometry challenge was on a coordinated motion planning problem in which a collection of square robots need to move on the integer grid, from their given starting points to their target points, and without collision between robots, or between robots and a set of input obstacles. We designed and implemented an algorithm for this problem, which consists of three parts. First, we computed a feasible solution by placing middle-points outside of the minimum bounding box of the input positions of the robots and the obstacles, and moving each robot from its starting point to its target point through a middle-point. Second, we applied a simple local search approach where we repeatedly delete and insert again a random robot through an optimal path. It improves the quality of the solution, as the robots no longer need to go through the middle-points. Finally, we used simulated annealing to further improve this feasible solution. We used two different types of moves: We either tightened the whole trajectory of a robot, or we stretched it between two points by making the robot move through a third intermediate point generated at random.

BibTeX - Entry

  author =	{Yang, Hyeyun and Vigneron, Antoine},
  title =	{{A Simulated Annealing Approach to Coordinated Motion Planning}},
  booktitle =	{37th International Symposium on Computational Geometry (SoCG 2021)},
  pages =	{65:1--65:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-184-9},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{189},
  editor =	{Buchin, Kevin and Colin de Verdi\`{e}re, \'{E}ric},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{},
  URN =		{urn:nbn:de:0030-drops-138649},
  doi =		{10.4230/LIPIcs.SoCG.2021.65},
  annote =	{Keywords: Path planning, simulated annealing, local search}

Keywords: Path planning, simulated annealing, local search
Collection: 37th International Symposium on Computational Geometry (SoCG 2021)
Issue Date: 2021
Date of publication: 02.06.2021

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