A soft resource optimization method based on autonomous coordination of unmanned swarms system driven by resilience

Hongxu Li, Yuanfu Zhong and Xuebin Zhuang

Reliability Engineering and System Safety, 2024, vol. 249, issue C

Abstract: The resilience improvement of unmanned swarm systems endows them with enhanced survivability and mission execution capability in complex environments. However, the current methods for improving resilience in unmanned swarm systems face challenges such as high time costs, difficult implementation, and weak anti-interference ability. Therefore, a soft resource optimization method based on the autonomous collaboration of unmanned swarm systems is proposed in this paper. Firstly, a research framework illustrates the complete cycle of resilience improvement processes in distributed unmanned swarm systems. Secondly, a soft resource optimization model is developed based on autonomous collaboration among distributed unmanned swarm systems, providing detailed insights into autonomous collaboration in complex environments. Finally, simulation experiments are conducted to validate the advantages of the proposed soft resource optimization method. The experimental results show that compared with the centralized control, the soft resource optimization method through autonomous coordination not only improves the resilience, but also improves the running speed by 99.8%. In addition, a pre-analysis of resilience threats is also carried out to facilitate proactive implementation of resilience improvement measures for unmanned swarm systems by engineers in the simulation experiment.

Keywords: Resilience improvement; Unmanned swarm system; Autonomous coordination; Soft resource optimization; Resilience threat pre-analysis (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:249:y:2024:i:c:s0951832024003004

DOI: 10.1016/j.ress.2024.110227

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