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Coordinated Motion Planning Through Randomized k-Opt

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arxiv 2103.15062 v1 pith:D3W5KJRX submitted 2021-03-28 cs.CG cs.RO

Paul Liu , Jack Spalding-Jamieson , Brandon Zhang , Da Wei Zheng This is my paper · ORCID
classification cs.CGcs.RO
keywords approachcategorychallengedistancefinishmakespanphaseplace
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 4 Pith papers

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