Document Open Access Logo

Coordinated Motion Planning Through Randomized k-Opt (CG Challenge)

Authors Paul Liu , Jack Spalding-Jamieson, Brandon Zhang, Da Wei Zheng

PDF

File

Thumbnail PDF
PDF
LIPIcs.SoCG.2021.64.pdf
  • Filesize: 0.88 MB
  • 8 pages

Document Identifiers

Related Versions

Subject Classification

ACM Subject Classification
  • Computing methodologies → Motion path planning
  • Theory of computation → Computational geometry
Keywords
  • motion planning
  • randomized local search
  • path finding

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
    0
    Metadata Views

Abstract

This paper examines the approach taken by team gitastrophe in the CG:SHOP 2021 challenge. The challenge was to find a sequence of simultaneous moves of square robots between two given configurations that minimized either total distance travelled or makespan (total time). Our winning approach has two main components: an initialization phase that finds a good initial solution, and a k-opt local search phase which optimizes this solution. This led to a first place finish in the distance category and a third place finish in the makespan category.

Cite As Get BibTex

Paul Liu, Jack Spalding-Jamieson, Brandon Zhang, and Da Wei Zheng. Coordinated Motion Planning Through Randomized k-Opt (CG Challenge). In 37th International Symposium on Computational Geometry (SoCG 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 189, pp. 64:1-64:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.SoCG.2021.64

Author Details

Paul Liu
  • Department of Computer Science, Stanford University, CA, USA
Jack Spalding-Jamieson
  • Department of Computer Science, University of Waterloo, Canada
Brandon Zhang
  • Vancouver, Canada
Da Wei Zheng
  • Department of Computer Science, University of Illinois at Urbana-Champaign, IL, USA

Supplementary Materials

References

  1. Loïc Crombez, Guilherme D. da Fonseca, Yan Gerard, Aldo Gonzalez-Lorenzo, Pascal Lafourcade, and Luc Libralesso. Shadoks Approach to Low-Makespan Coordinated Motion Planning. In 37th International Symposium on Computational Geometry (SoCG 2021), volume 189 of LIPIcs, pages 63:1-63:9, 2021. URL: https://doi.org/10.4230/LIPIcs.SoCG.2021.63.
  2. Sándor Fekete, Phillip Keldenich, Dominik Krupke, and Joseph S. B. Mitchell. Computing Coordinated Motion Plans for Robot Swarms: The CG:SHOP Challenge 2021. CoRR, abs/2103.15381, 2021. URL: http://arxiv.org/abs/2103.15381.
  3. Hyeyun Yang and Antoine Vigneron. A Simulated Annealing Approach to Coordinated Motion Planning. In 37th International Symposium on Computational Geometry (SoCG 2021), volume 189 of LIPIcs, pages 65:1-65:9, 2021. URL: https://doi.org/10.4230/LIPIcs.SoCG.2021.65.
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2025 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact