Lifelong Multi-Agent Path Finding in A Dynamic Environment

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

9 Scopus Citations
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Author(s)

  • Qian Wan
  • Chonglin Gu
  • Sankui Sun
  • Mengxia Chen
  • Hejiao Huang

Detail(s)

Original languageEnglish
Title of host publication2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages875-882
ISBN (Electronic)9781538695821
ISBN (Print)9781538695838
Publication statusPublished - 2018
Externally publishedYes

Publication series

NameInternational Conference on Control, Automation, Robotics and Vision
PublisherIEEE
ISSN (Print)2474-2953

Conference

Title15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018
PlaceSingapore
Period18 - 21 November 2018

Abstract

In tradition, the problem of Multi-Agent Path Finding is to find paths for the agents without conflicts, and each agent execute one-shot task, a travel from a start position to its destination. However, making just one planning for the agents may not satisfy the requirement in dynamic environments such as logistics sorting center, where the paths of the agents may constantly need to be adjusted according to the incoming tasks. The challenging issue is to dynamically adjust the already planned paths while make planning for the agents ready to execute new incoming tasks. In this paper, we formulate it into Dynamic Multi-Agent Path Finding (DMAPF) problem, the goal of which is to minimize the cumulative cost of paths. To solve this problem, we propose an algorithm called Lifelong Planning Conflict-Based Search (LPCBS), which can efficiently and optimally make planning for the new incoming tasks while adjusting the already planned paths. Experiment results show that the LPCBS performs much better than the existing works in each planning. © 2018 IEEE.

Research Area(s)

  • Dynamic, Lifelong Planing, Multi-Agent Path Finding

Citation Format(s)

Lifelong Multi-Agent Path Finding in A Dynamic Environment. / Wan, Qian; Gu, Chonglin; Sun, Sankui; Chen, Mengxia; Huang, Hejiao; Jia, Xiaohua.

2018 15th International Conference on Control, Automation, Robotics and Vision, ICARCV 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 875-882 8581181 (International Conference on Control, Automation, Robotics and Vision).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review