多个无人机的任务规划基于最低成本和最大流量
Xiaodong Shi1,2, Xiangping Zhai1,3,4, Rui Wang1
1College of Computer Science and Technology/Artifical Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Sensors (Basel, Switzerland)
|March 17, 2025
概括
本研究引入了使用卡车和无人机 (UAV) 的合作交付系统,以克服无人机的局限性. 综合方法提高了交付效率,并降低了物流运营中的能源消耗.
科学领域:
- 物流和供应链管理的物流和供应链管理.
- 机器人和自动化 机器人和自动化
- 运营研究 运营研究
背景情况:
- 无人驾驶飞行器 (UAV) 交付提供了降低成本的潜力,但面临着负载和能源限制.
- 现有的物流模式在密集的仓库中难以实现高效的广域配送.
研究的目的:
- 提出一项合作的卡车-无人机交付计划,以扩大无人机的作战范围,提高交付成功率.
- 在卡车独立无人机系统中开发任务分配和路径规划的新算法,以实现高效的物流.
主要方法:
- 制定了一个最低成本,最大流量模型,以确定交付任务的最佳子路径.
- 基于资源树的算法用于构建卡车和无人机的综合全球路径.
- 进行了模拟,以评估拟议的合作交付计划的性能.
主要成果:
- 合作战略显著扩大了无人机覆盖范围,并提高了整体交付完成率.
- 开发的算法在不同任务分布中,分别减少了11.53%和9.15%的总能耗.
- 与传统方法相比,卡车-无人机系统在模拟中显示出更高的效率.
结论:
- 拟议的合作卡车-无人机交付方案为现代物流挑战提供了可行和高效的解决方案.
- 这种综合方法有效地解决了独立无人机交付系统的局限性.
- 调查结果强调了物流效率和节能方面的重大改进的潜力.
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