Robust Multi-agent path finding

Dor Atzmon, Roni Stern, Ariel Felner, Glenn Wagner, Roman Bartak, Neng Fa Zhou

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

18 Scopus citations

Abstract

In the multi-agent path-finding (MAPF) problem, the task is to find a plan for moving a set of agents from their initial locations to their goals without collisions. Following this plan, however, may not be possible due to unexpected events that delay some of the agents. We explore the notion of k- robust MAPF, where the task is to find a plan that can be followed even if a limited number of such delays occur. k- robust MAPF is especially suitable for agents with a control mechanism that guarantees that each agent is within a limited number of steps away from its pre-defined plan. We propose sufficient and required conditions for finding a k-robust plan, and show how to convert several MAPF solvers to find such plans. Then, we show the benefit of using a k-robust plan during execution, and for finding plans that are likely to succeed.

Original languageEnglish
Title of host publicationProceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018
EditorsVadim Bulitko, Sabine Storandt
PublisherAAAI press
Pages2-9
Number of pages8
ISBN (Electronic)9781577358022
StatePublished - 1 Jan 2018
Event11th International Symposium on Combinatorial Search, SoCS 2018 - Stockholm, Sweden
Duration: 14 Jul 201815 Jul 2018

Publication series

NameProceedings of the 11th International Symposium on Combinatorial Search, SoCS 2018

Conference

Conference11th International Symposium on Combinatorial Search, SoCS 2018
Country/TerritorySweden
CityStockholm
Period14/07/1815/07/18

ASJC Scopus subject areas

  • Computer Networks and Communications

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