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

Authors :
Paul Liu and Jack Spalding-Jamieson and Brandon Zhang and Da Wei Zheng
Liu, Paul
Spalding-Jamieson, Jack
Zhang, Brandon
Zheng, Da Wei
Paul Liu and Jack Spalding-Jamieson and Brandon Zhang and Da Wei Zheng
Liu, Paul
Spalding-Jamieson, Jack
Zhang, Brandon
Zheng, Da Wei
Publication Year :
2021

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.

Details

Database :
OAIster
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1358728925
Document Type :
Electronic Resource
Full Text :
https://doi.org/10.4230.LIPIcs.SoCG.2021.64