Enhancing Lifelong Multi-Agent Path-finding by Using Artificial Potential Fields

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

1 Scopus citations

Abstract

We explore the use of Artificial Potential Fields (APFs) to solve Lifelong Multi-Agent Path Finding (LMAPF) problems. In LMAPF, a team of agents must move to their goal locations without collisions, and new goals are generated upon arrival. We propose methods for incorporating APFs in a range of LMAPF algorithms, including Prioritized Planning and MAPF-LNS2. Experimental results show that using APF yields up to a 7-fold increase in overall system throughput for LMAPF.

Original languageEnglish
Title of host publicationProceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025
EditorsYevgeniy Vorobeychik, Sanmay Das, Ann Nowe
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages2711-2713
Number of pages3
ISBN (Electronic)9798400714269
StatePublished - 1 Jan 2025
Event24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025 - Detroit, United States
Duration: 19 May 202523 May 2025

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914

Conference

Conference24th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2025
Country/TerritoryUnited States
CityDetroit
Period19/05/2523/05/25

Keywords

  • Artificial Potential Fields
  • Multi-agent Pathfinding
  • Multi-robot Path Planning

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering

Fingerprint

Dive into the research topics of 'Enhancing Lifelong Multi-Agent Path-finding by Using Artificial Potential Fields'. Together they form a unique fingerprint.

Cite this