Scholarlink

<p>The multiple unmanned aerial vehicle's (multi-UAV's) collaborative task allocation problem with complex constraints has received significant attention in recent years. This paper focuses on the efficient task allocation method for the search and rescue scenario with complex timing and resource constraints. First, the considered scenario is formulated, and a hybrid task allocation method considering complex constraints (HTACC) is proposed by integrating decentralized and distributed algorithm. Specifically, a constraint rule is designed to non-dominated sort all unallocated tasks. And, based on the resource constraints and timing constraints in a distributed manner, a bidding strategy is proposed for each UAV to bid for current task. On this basis, the centralized commander investigates an improved NSGA-III to select a UAV alliance that fulfills the constraints based on the received bids to cooperatively complete the task. Finally, the effectiveness and superiority of the proposed HTACC method are verified through experimental simulations. The results show that HTACC can obtain a better Pareto frontier compared to other algorithms. In addition, HTACC can obtain task schedules within 24.25&#xa0;s, and the average resource utilization rate is as high as 47.72% in a large-scale scenario of 45 tasks with 100 UAVs.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A hybrid task allocation approach for multi-UAV systems with complex constraints: a market-based bidding strategy and improved NSGA-III optimization

  • 期刊论文

  • 发表日期：

    2025年2月26日

查看全文
  • Mi Yang,
  • Baichuan Zhang,
  • Zhifu Shi,
  • Jiguang Li

摘要

The multiple unmanned aerial vehicle's (multi-UAV's) collaborative task allocation problem with complex constraints has received significant attention in recent years. This paper focuses on the efficient task allocation method for the search and rescue scenario with complex timing and resource constraints. First, the considered scenario is formulated, and a hybrid task allocation method considering complex constraints (HTACC) is proposed by integrating decentralized and distributed algorithm. Specifically, a constraint rule is designed to non-dominated sort all unallocated tasks. And, based on the resource constraints and timing constraints in a distributed manner, a bidding strategy is proposed for each UAV to bid for current task. On this basis, the centralized commander investigates an improved NSGA-III to select a UAV alliance that fulfills the constraints based on the received bids to cooperatively complete the task. Finally, the effectiveness and superiority of the proposed HTACC method are verified through experimental simulations. The results show that HTACC can obtain a better Pareto frontier compared to other algorithms. In addition, HTACC can obtain task schedules within 24.25 s, and the average resource utilization rate is as high as 47.72% in a large-scale scenario of 45 tasks with 100 UAVs.