The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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Puzzle Heuristics: Efficient Lifelong Multi-Agent Pathfinding Algorithm for Large-scale Challenging Environments

퍼즐 휴리스틱스: 대규모 환경을 위한 효율적인 다중 에이전트 경로 탐색 알고리즘

  • Wonjong Lee (Dept. of Artificial Intelligence, Sogang University) ;
  • Joonyeol Sim (Dept. of Electronic Engineering, Sogang University) ;
  • Changjoo Nam (Dept. of Electronic Engineering, Sogang University)
  • 이원종 ;
  • 심준열 ;
  • 남창주
  • Received : 2024.04.19
  • Accepted : 2024.07.23
  • Published : 2024.08.30
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Abstract

This paper describes the solution method of Team AIRLAB used to participate in the League of Robot Runners Competition which tackles the problem of Lifelong Multi-agent Pathfinding (MAPF). In lifelong MAPF, multiple agents are tasked to navigate to their respective goal locations where new goals are consecutively revealed once they reach initial goals. The agents need to avoid collisions and deadlock situations while they navigate to perform tasks. Our method consists of (i) Puzzle Heuristics, (ii) MAPF-LNS2, and (iii) RHCR. The Puzzle Heuristics is our own algorithm that generates a compact heuristic table contributing to reduce memory consumption and computation time. MAPF-LNS2 and RHCR are state-of-the-art algorithms for MAPF. By combining these three algorithms, our method can improve the efficiency of paths for all agents significantly.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1C1C1008476).

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