App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 7

Autonomous cooperative search-and-rescue method for UAV swarms with exploration–rescue trade-off

Xu Zhoua,b
Li Guanxionga,b
Deng Xiaogangb
a. College of Computer Science, b. National Key Laboratory of Fundamental Algorithms and Models for Engineering Simulation, Sichuan University, Chengdu 610065, China
DOI: 10.19734/j.issn.1001-3695.2025.12.0459

Abstract

To enhance the autonomous cooperative decision-making capability of UAV swarms when performing search-and-rescue tasks in unknown and complex environments, this paper proposes a multi-agent cooperative decision-making method that integrates a dual-layer Gaussian Markov Random Field (GMRF) representation with a surprise-based representation enhancement mechanism. Specifically, this paper constructs a dual-layer GMRF model consisting of an environmental structure layer and a signal distribution layer to provide the UAV swarm with spatially correlated environmental representations. Furthermore, this paper introduces a surprise mechanism based on value-function gradient sensitivity to adaptively enhance observational features, thereby strengthening the perception of decision-critical states. Based on this design, this paper develops a multi-agent reinforcement learning (MARL) framework named Sur-QMIX by extending QMIX to address the trade-off between search and rescue objectives, enabling UAVs to adaptively balance exploration and rescue execution. Experimental results demonstrate that, in GMRF-encoded environments, the proposed Sur-QMIX achieves significant performance gains in medium- and high-difficulty scenarios. Specifically, it reduces the search completion steps by up to 27.3% and the cooperative rescue time by up to 41.2% compared with the best competing methods, while also achieving the best first rescue time in most scenarios and exhibiting strong scalability.

Foundation Support

国家自然科学基金资助项目(12202297)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.12.0459
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 7

Publish History

[2026-03-25] Accepted Paper

Cite This Article

徐洲, 李冠雄, 邓小刚. 面向探索—救援权衡的无人机集群自主协同搜救方法 [J]. 计算机应用研究, 2026, 43 (7). (2026-03-27). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0459. (Xu Zhou, Li Guanxiong, Deng Xiaogang. Autonomous cooperative search-and-rescue method for UAV swarms with exploration–rescue trade-off [J]. Application Research of Computers, 2026, 43 (7). (2026-03-27). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0459. )

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.

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