无人机飞行器轨迹规划,在复杂环境中可靠收集边缘数据
Zhengzhe Xiang1, Fuli Ying1, Xizi Xue2
1Shcool of Computer and Computing Science, Hangzhou City University, Hangzhou 310025, China.
Biomimetics (Basel, Switzerland)
|February 25, 2025
概括
本研究介绍了Hyperion,Hyperion是一种无人机轨迹规划方法,它考虑了用于可靠边缘数据收集的电池容量. 它优化了路线,以确保无人机可以返回充电站,提高在具有挑战性的环境中任务的成功.
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
- 电气工程 电气工程
背景情况:
- 边缘计算正在将任务从云端转移到边缘节点,创造数据处理挑战.
- 无人机为边缘数据收集提供了解决方案,但轨道优化往往忽视了电池的限制.
- 在边缘计算场景中,有限的电池容量带来了任务失败和无人机安全危险的风险.
研究的目的:
- 提出一种名为Hyperion的新型无人机轨迹规划方法.
- 通过纳入电池容量和充电方面的考虑来解决现有方法的局限性.
- 优化无人机轨迹长度和能源消耗,以获得可靠的边缘数据收集.
主要方法:
- 在轨道规划中制定了一个贪的决策策略.
- 将充电站考虑因素集成到无人机飞行路径优化中.
- 专注于确保无人机在数据收集后返回充电站.
主要成果:
- 通过平衡数据收集需求与能源限制,Hyperion优化了无人机轨迹.
- 这种方法提高了边缘数据收集任务的可靠性.
- 提高无人机在复杂和极端操作环境中的适应性.
结论:
- 提出的Hyperion方法有效地解决了边缘计算中的无人机电池限制.
- 整合充电物流可显著提高任务成功率和无人机运营安全.
- 在具有挑战性的边缘环境中,Hyperion为动态数据收集提供了一个强大的解决方案.
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