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| Resilience Optimization Method for Unmanned Swarms Based on Abnormal Individual Identification |
| ZHOU Xinxin1，2， WANG Kunyun3， WEI Qiang1，2，4，
CHEN Zhijie1，2，4， LIU Tao5 |
| 1. Wuhan Digital Engineering Research Institute， Wuhan 430205， Hubei， China；
2. Hubei Provincial Key Laboratory of Data Intelligence， Wuhan 430205， Hubei， China；
3. Shanghai Electro-Mechanical Engineering Institute， Shanghai 201109， China；
4. School of Automation and Intelligent Sensing， Shanghai Jiao Tong University， Shanghai 200240， China；
5. School of Mechanical Engineering， Xihua University， Chengdu 610039， Sichuan， China |
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Abstract To address the issue of individual abnormal behaviors degrading swarm resilience in denied environments, this paper proposes a resilience optimization method for unmanned swarms based on abnormal individual identification, which effectively enhances swarm resilience. Firstly, the mechanism of individual abnormal behaviors in unmanned swarms is analyzed, revealing the efficacy of abnormal individual identification and isolation in improving swarm resilience. Secondly, considering the strong correlation in inter-individual positioning when the swarm reaches a steady state, a correlation-based abnormal individual identification method is proposed. On this basis, a resilience optimization method for unmanned swarms is constructed. Finally, comparative experiments between the optimized model and the original model under different swarm scales, behavioral models, and failure ratios demonstrate the feasibility and effectiveness of the proposed method.
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Received: 30 January 2026
Published: 10 July 2026
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2026, Vol. 9 
