首页 /研究 /Coordinated Motion Planning Through Randomized k-Opt (CG Challenge)
OTHER

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

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

发表年份
2021
引用次数
5
访问权限
开放获取

摘要

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.

关键词

InitializationJob shop schedulingMathematical optimizationSequence (biology)RobotSquare (algebra)Phase (matter)Computer scienceMotion (physics)Motion planning

相关论文

查看 OTHER 分类全部论文