多无人机协同作业中，兼顾通信与能耗的路径规划方法。
Communication and Energy-Aware Multi-UAV Coverage Path Planning for Networked Operations
- 结合能耗与通信半径，优化路径规划。
- 在有障碍物区域实现99%通信范围预测准确率。
- 适合搜救、巡检等需持续通信的多机任务。
本文提出一种面向连续无人机间通信需求（如协同搜救、监控任务）的多无人机覆盖路径规划方法。与以往仅关注能耗、时间或覆盖效率的方法不同，该方法通过最小化指定组合的能耗与无人机间连通半径，生成最优路径。算法包含简化且验证过的能耗模型、高效的连通半径估计算法，以及可在不规则、障碍物密集区域搜索最优路径的优化框架。通过在含禁飞区与无禁飞区的多种测试区域进行仿真验证，结果表明其有效性。三架无人机实测实验显示，预测与实际通信需求匹配率达99%，证明了算法的实用性。
原文摘要 · Abstract (English)
This paper presents a communication and energy-aware multi-UAV Coverage Path Planning (mCPP) method for scenarios requiring continuous inter-UAV communication, such as cooperative search and rescue and surveillance missions. Unlike existing mCPP solutions that focus on energy, time, or coverage efficiency, the proposed method generates coverage paths that minimize a specified combination of energy and inter-UAV connectivity radius. Key features of the proposed algorithm include a simplified and validated energy consumption model, an efficient connectivity radius estimator, and an optimization framework that enables us to search for the optimal paths over irregular and obstacle-rich regions. The effectiveness and utility of the proposed algorithm is validated through simulations on various test regions with and without no-fly-zones. Real-world experiments on a three-UAV system demonstrate the remarkably high 99% match between the estimated and actual communication range requirement.
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