在多无人机辅助WSN中优化任务分配,考虑到能源预算和传感器分布特征.
Qile Xie1, Wendong Zhao1, Cuntao Liu2
1College of Communication Engineering, Army Engineering University of PLA, Nanjing 210007, China.
Sensors (Basel, Switzerland)
|September 28, 2023
概括
这项研究最大限度地减少了多无人机系统在紧急情况下收集数据的时间. 一个优化的分配算法 (AASDC) 在严格的截止日期下减少无线传感器网络 (WSN) 的任务持续时间.
科学领域:
- 计算机科学 计算机科学
- 机器人技术 机器人技术 机器人技术
- 网络工程 网络工程
背景情况:
- 应急响应需要从无线传感器网络 (WSN) 快速收集数据.
- 多个无人机系统为在具有挑战性的环境中获取数据提供了灵活的解决方案.
- 优化无人机部署和任务分配对于时间敏感的任务至关重要.
研究的目的:
- 为了尽量减少无人机在WSN数据收集中的任务时间.
- 为了解决优化无人机分配,轨迹和部署位置的复杂问题.
- 为了考虑到UAV在数据收集任务期间的能源限制.
主要方法:
- 将问题分解为无人机任务分配和轨迹/悬空位置优化.
- 基于传感器分布特征 (AASDC) 的分配算法的开发.
- 考虑传感器的地理位置和数据的重要性,以优化任务分配.
主要成果:
- 与现有方法相比,拟议的AASDC计划显著减少了数据收集时间.
- 优化无人机分配和轨道规划,提高了任务效率.
- 该方法有效地处理了任务分配和空间优化之间的合.
结论:
- 该AASDC算法提供了一个有效的解决方案,时间受限的多UAV数据收集在WSNs.
- 优化无人机操作对于提高应急响应能力至关重要.
- 这项研究有助于在灾害监测场景中有效管理资源.
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