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, our approach generates coverage paths that require minimal the communication range to maintain inter-UAV connectivity while also optimizing energy consumption. The mCPP problem is formulated as a multi-objective optimization task, aiming to minimize both the communication range requirement and energy consumption. Our approach significantly reduces the communication range needed for maintaining connectivity while ensuring energy efficiency, outperforming state-of-the-art methods. Its effectiveness is validated through simulations on complex and arbitrary shaped regions of interests, including scenarios with no-fly zones. Additionally, real-world experiment demonstrate its high accuracy, achieving 99\% consistency between the estimated and actual communication range required during a multi-UAV coverage mission involving three UAVs.

翻译：本文提出了一种面向需要持续无人机间通信场景（如协同搜救与监视任务）的通信与能耗感知多无人机覆盖路径规划方法。与现有聚焦于能量、时间或覆盖效率的多无人机覆盖路径规划解决方案不同，本方法生成的覆盖路径在优化能耗的同时，仅需最小通信范围即可维持无人机间的连通性。该多无人机覆盖路径规划问题被构建为多目标优化任务，旨在同时最小化通信范围需求与能量消耗。本方法在保证能量效率的同时，显著降低了维持连通性所需的通信范围，其性能优于现有先进方法。通过在包含禁飞区的复杂任意形状兴趣区域上进行仿真，验证了该方法的有效性。此外，真实世界实验证明了其高精度：在一次涉及三架无人机的多无人机覆盖任务中，所需通信范围的估计值与实际值达到了99%的一致性。