无人机集群任务规划战略 区域覆盖任务 任务
Xiaohong Yan1,2, Renwen Chen1, Zihao Jiang1
1College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Sensors (Basel, Switzerland)
|November 25, 2023
概括
本研究介绍了无人飞行器 (UAV) 集群的高效任务规划策略,以优化区域覆盖任务. 拟议的方法提高了UAV群的任务分配效率和能源消耗.
科学领域:
- 机器人和自动化 机器人和自动化
- 人工智能的人工智能
- 航空航天工程 航空航天工程
背景情况:
- 无人驾驶飞行器 (UAV) 集群在区域覆盖任务中面临挑战,包括低效的任务分配和高能耗.
- 有效的任务规划对于优化多无人机系统在复杂环境中的性能至关重要.
研究的目的:
- 为无人机集群提出有效的任务规划战略,以应对区域覆盖任务中的挑战.
- 为了提高任务分配,效率和能源消耗在三维区域覆盖的操作.
主要方法:
- 区域覆盖范围搜索任务的分析和覆盖范围计划的确定.
- 将任务区域划分为子区域,并为无人机集群任务分配提供逐步解决方案.
- 应用改进的模糊C集群算法用于无人机任务区域的确定.
- 为路径规划开发一个优化的粒子群混合殖民地 (PSOHAC) 算法.
主要成果:
- 拟议的战略确保了任务区域的全面覆盖和无人机集群的高效任务分配.
- 模拟实验验证了开发的任务规划方案的可行性和优越性.
- 该方法在平衡能源消耗效率方面实现了最大21.9%的改进.
- 与现有算法相比,无人机集群的整体能源效率提高了高达7.9%.
结论:
- 开发的任务规划战略有效地解决了无人机集群区域覆盖面的挑战.
- 优化的PSOHAC算法显著提高了路径规划和能源效率.
- 拟议的方法为高效和节能无人机群运营提供了卓越的解决方案.
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