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.2021.64
URN: urn:nbn:de:0030-drops-138635
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/13863/
Liu, Paul ;
Spalding-Jamieson, Jack ;
Zhang, Brandon ;
Zheng, Da Wei
Coordinated Motion Planning Through Randomized k-Opt (CG Challenge)
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.
BibTeX - Entry
@InProceedings{liu_et_al:LIPIcs.SoCG.2021.64,
author = {Liu, Paul and Spalding-Jamieson, Jack and Zhang, Brandon and Zheng, Da Wei},
title = {{Coordinated Motion Planning Through Randomized k-Opt}},
booktitle = {37th International Symposium on Computational Geometry (SoCG 2021)},
pages = {64:1--64:8},
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 = {https://drops.dagstuhl.de/opus/volltexte/2021/13863},
URN = {urn:nbn:de:0030-drops-138635},
doi = {10.4230/LIPIcs.SoCG.2021.64},
annote = {Keywords: motion planning, randomized local search, path finding}
}
