An MFG Online Path Planning Algorithm Based on Upper and Lower Structure

Jinwei Liu; Wang Yao; Xiao Zhang

doi:10.1007/978-981-99-6498-7_31

An MFG Online Path Planning Algorithm Based on Upper and Lower Structure

Jinwei Liu
, Wang Yao
, Xiao Zhang^*

^*Corresponding author for this work

Beihang University
Zhongguancun Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

The collision-free path planning problem for multi-agent systems becomes increasingly complex as the number of agents increases. Mean-field game theory has proven effective for solving large-scale problems but is limited by the difficulty of solving higher-dimensional equations, which must fix beginnings and terminations. This paper proposes a new algorithm combining upper and lower layers to achieve online path planning. We utilize the mean field games process as the primary action of the lower layer, while the path planning of the grid method determines the global Markov process of the upper layer. By integrating the mean field games as an act of the global Markov process, we transfer the system’s state by considering the environment. Simulation experiments verify the feasibility of this approach, providing a new and effective means for online path planning of large-scale multi-agent systems.

Original language	English
Title of host publication	Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings
Editors	Huayong Yang, Jun Zou, Geng Yang, Xiaoping Ouyang, Honghai Liu, Zhouping Yin, Lianqing Liu, Zhiyong Wang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	355-366
Number of pages	12
ISBN (Print)	9789819964970
DOIs	https://doi.org/10.1007/978-981-99-6498-7_31
State	Published - 2023
Event	16th International Conference on Intelligent Robotics and Applications, ICIRA 2023 - Hangzhou, China Duration: 5 Jul 2023 → 7 Jul 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14273 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Intelligent Robotics and Applications, ICIRA 2023
Country/Territory	China
City	Hangzhou
Period	5/07/23 → 7/07/23

Keywords

Large-Scale Problems
Mean Field Games
Multi-agent System
Online Path Planning

Access to Document

10.1007/978-981-99-6498-7_31

Cite this

Liu, J., Yao, W., & Zhang, X. (2023). An MFG Online Path Planning Algorithm Based on Upper and Lower Structure. In H. Yang, J. Zou, G. Yang, X. Ouyang, H. Liu, Z. Yin, L. Liu, & Z. Wang (Eds.), Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings (pp. 355-366). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14273 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-99-6498-7_31

Liu, Jinwei ; Yao, Wang ; Zhang, Xiao. / An MFG Online Path Planning Algorithm Based on Upper and Lower Structure. Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. editor / Huayong Yang ; Jun Zou ; Geng Yang ; Xiaoping Ouyang ; Honghai Liu ; Zhouping Yin ; Lianqing Liu ; Zhiyong Wang. Springer Science and Business Media Deutschland GmbH, 2023. pp. 355-366 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "The collision-free path planning problem for multi-agent systems becomes increasingly complex as the number of agents increases. Mean-field game theory has proven effective for solving large-scale problems but is limited by the difficulty of solving higher-dimensional equations, which must fix beginnings and terminations. This paper proposes a new algorithm combining upper and lower layers to achieve online path planning. We utilize the mean field games process as the primary action of the lower layer, while the path planning of the grid method determines the global Markov process of the upper layer. By integrating the mean field games as an act of the global Markov process, we transfer the system{\textquoteright}s state by considering the environment. Simulation experiments verify the feasibility of this approach, providing a new and effective means for online path planning of large-scale multi-agent systems.",

keywords = "Large-Scale Problems, Mean Field Games, Multi-agent System, Online Path Planning",

author = "Jinwei Liu and Wang Yao and Xiao Zhang",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.; 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023 ; Conference date: 05-07-2023 Through 07-07-2023",

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editor = "Huayong Yang and Jun Zou and Geng Yang and Xiaoping Ouyang and Honghai Liu and Zhouping Yin and Lianqing Liu and Zhiyong Wang",

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Liu, J, Yao, W & Zhang, X 2023, An MFG Online Path Planning Algorithm Based on Upper and Lower Structure. in H Yang, J Zou, G Yang, X Ouyang, H Liu, Z Yin, L Liu & Z Wang (eds), Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14273 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 355-366, 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023, Hangzhou, China, 5/07/23. https://doi.org/10.1007/978-981-99-6498-7_31

An MFG Online Path Planning Algorithm Based on Upper and Lower Structure. / Liu, Jinwei; Yao, Wang ; Zhang, Xiao.
Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. ed. / Huayong Yang; Jun Zou; Geng Yang; Xiaoping Ouyang; Honghai Liu; Zhouping Yin; Lianqing Liu; Zhiyong Wang. Springer Science and Business Media Deutschland GmbH, 2023. p. 355-366 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14273 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2023

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N2 - The collision-free path planning problem for multi-agent systems becomes increasingly complex as the number of agents increases. Mean-field game theory has proven effective for solving large-scale problems but is limited by the difficulty of solving higher-dimensional equations, which must fix beginnings and terminations. This paper proposes a new algorithm combining upper and lower layers to achieve online path planning. We utilize the mean field games process as the primary action of the lower layer, while the path planning of the grid method determines the global Markov process of the upper layer. By integrating the mean field games as an act of the global Markov process, we transfer the system’s state by considering the environment. Simulation experiments verify the feasibility of this approach, providing a new and effective means for online path planning of large-scale multi-agent systems.

AB - The collision-free path planning problem for multi-agent systems becomes increasingly complex as the number of agents increases. Mean-field game theory has proven effective for solving large-scale problems but is limited by the difficulty of solving higher-dimensional equations, which must fix beginnings and terminations. This paper proposes a new algorithm combining upper and lower layers to achieve online path planning. We utilize the mean field games process as the primary action of the lower layer, while the path planning of the grid method determines the global Markov process of the upper layer. By integrating the mean field games as an act of the global Markov process, we transfer the system’s state by considering the environment. Simulation experiments verify the feasibility of this approach, providing a new and effective means for online path planning of large-scale multi-agent systems.

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A2 - Wang, Zhiyong

PB - Springer Science and Business Media Deutschland GmbH

T2 - 16th International Conference on Intelligent Robotics and Applications, ICIRA 2023

Y2 - 5 July 2023 through 7 July 2023

ER -

Liu J, Yao W , Zhang X. An MFG Online Path Planning Algorithm Based on Upper and Lower Structure. In Yang H, Zou J, Yang G, Ouyang X, Liu H, Yin Z, Liu L, Wang Z, editors, Intelligent Robotics and Applications - 16th International Conference, ICIRA 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 355-366. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-981-99-6498-7_31