Heterogeneous Multi-UAV Mission Reallocation Based on Improved Consensus-Based Bundle Algorithm

Drones Pub Date : 2024-07-25 DOI:10.3390/drones8080345
W. Bi, Junyi Shen, Jiuli Zhou, An Zhang
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Abstract

In dynamic complex environments, it is inevitable for UAVs to be damaged due to their confrontational nature. The challenge to minimize the adverse effects of the damage and reallocate the mission is vital for achieving the operational goal. This paper proposes a distributed Multi-UAV mission reallocation method in the case of UAV damage based on the improved consensus-based bundle algorithm (CBBA). Firstly, a dynamic optimization model for Multi-UAV mission reallocation is established based on an improved resource update model. Secondly, a distributed damage inspection method based on the heartbeat hold mechanism is proposed for real-time monitoring of UAV conditions, which could enable the rapid response to UAV damage events. Furthermore, the CBBA is improved by introducing a timeliness parameter to adjust the bidding strategy and optimizing the mission selection strategy based on the time-order priority insertion principle to generate mission reallocation plans quickly. Through numerical examples, the results show that the proposed method can effectively reallocate Multi-UAV missions under damage events and has superior performance compared with original the CBBA, the particle swarm optimization (PSO) algorithm, and the performance impact (PI) algorithm. The proposed method has a faster solving speed, while the obtained solution has higher mission reallocation effectiveness.
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基于改进的基于共识的捆绑算法的异构多无人机任务再分配
在复杂的动态环境中,无人机因其对抗性不可避免地会受到损伤。如何最大限度地减少损坏带来的不利影响并重新分配任务对于实现作战目标至关重要。本文基于改进的基于共识的捆绑算法(CBBA),提出了一种无人机受损情况下的分布式多无人机任务重新分配方法。首先,基于改进的资源更新模型,建立了多无人机任务重新分配的动态优化模型。其次,提出了一种基于心跳保持机制的分布式损伤检测方法,用于实时监测无人机状况,从而实现对无人机损伤事件的快速响应。此外,还改进了 CBBA,引入时间性参数来调整竞标策略,并根据时序优先插入原则优化任务选择策略,快速生成任务再分配方案。通过数值示例,结果表明所提出的方法能有效地重新分配损坏事件下的多无人机任务,与原有的 CBBA 算法、粒子群优化(PSO)算法和性能影响(PI)算法相比具有更优越的性能。所提出的方法具有更快的求解速度,同时所获得的解决方案具有更高的任务重新分配效率。
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