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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 9
2737-2744

Hard attention reinforcement model for swarm robotics inspired by fish school emergence behavior

Liu Leia,b
Ge Zhenyeb
Lin Jiea
Tao Yub
Sun Junjiea
a. School of Management, b. School of Optoelectronics, University of Shanghai for Science & Technology, Shanghai 200093, China
DOI: 10.19734/j.issn.1001-3695.2023.12.0625

Abstract

The biological swarm motion model enables the emergence of order in robot collectives, but controlling the natural swarm order formed by robots is challenging. To address this issue, this paper proposed the fish school hard attention model to analyze interaction behaviors in experimental fish school data. This model utilized structures such as an encoder network, graph attention network, information aggregation network, pre-decoding network and a final decoding network to capture crucial information about the focal individuals important neighbors. Subsequently, it employed deep deterministic policy gradient techniques to design trajectory reinforcement networks and safety reinforcement networks to achieve artificial control of the swarm. Results from multi-agent simulations and experiments with swarm robotics demonstrate that the proposed method can realize artificial trajectory and safety control of collectives. The utilization of high-attention neighborhood information for resolving reinforcement learning challenges in collective motion provides a novel approach. The proposed control model exhibits substantial potential applications in areas such as collaborative aerial operations of drone swarms, intelligent agricultural machinery operations, and multi-robot material handling in logistics and warehousing.

Foundation Support

上海市自然科学基金资助项目(22ZR1443300)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.12.0625
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 9
Section: Algorithm Research & Explore
Pages: 2737-2744
Serial Number: 1001-3695(2024)09-024-2737-08

Publish History

[2024-03-19] Accepted Paper
[2024-09-05] Printed Article

Cite This Article

刘磊, 葛振业, 林杰, 等. 基于鱼群涌现行为启发的集群机器人硬注意力强化模型 [J]. 计算机应用研究, 2024, 41 (9): 2737-2744. (Liu Lei, Ge Zhenye, Lin Jie, et al. Hard attention reinforcement model for swarm robotics inspired by fish school emergence behavior [J]. Application Research of Computers, 2024, 41 (9): 2737-2744. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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