Multi-train path finding

Dor Atzmon, Amit Diei, Daniel Rave

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

13 Scopus citations

Abstract

Multi-agent path finding (MAPF) is the problem of moving a set of agents from their individual start locations to their individual goal locations, without collisions. This problem has practical applications in video games, traffic control, robotics, and more. In MAPF we assume that agents occupy one location each time step. However, in real life some agents have different size or shape. Hence, a standard MAPF solution may be not suited in practice for some applications. In this paper, we describe a novel algorithm, based on the CBS algorithm, that finds a plan for moving a set of train-agents, i.e., agents that occupy a sequence of two or more locations, such as trains, buses, planes, or even snakes. We prove that our solution is optimal and show experimentally that indeed such a solution can be found. Finally, we explain how our solution can also apply to agents with any geometric shape.

Original languageEnglish
Title of host publicationProceedings of the 12th International Symposium on Combinatorial Search, SoCS 2019
EditorsPavel Surynek, William Yeoh
PublisherAAAI press
Pages125-129
Number of pages5
ISBN (Electronic)9781577358084
StatePublished - 1 Jan 2019
Event12th International Symposium on Combinatorial Search, SoCS 2019 - Napa, United States
Duration: 16 Jul 201917 Jul 2019

Publication series

NameProceedings of the 12th International Symposium on Combinatorial Search, SoCS 2019

Conference

Conference12th International Symposium on Combinatorial Search, SoCS 2019
Country/TerritoryUnited States
CityNapa
Period16/07/1917/07/19

ASJC Scopus subject areas

  • Computer Networks and Communications

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