A Communication-Aware Path Planning Algorithm for Power Inspection UAVs Using an Improved Grey Wolf Optimizer

Unmanned Aerial Vehicles (UAVs) are revolutionizing power grid inspection, yet ensuring reliable, high-quality image transmission in complex environments remains a significant challenge for autonomous operations. Traditional path planning algorithms often neglect communication constraints, risking mission failure in areas with poor connectivity—a critical concern for future UAV swarm deployments where inter-agent coordination depends on sustained link quality. This paper proposes a novel communication-aware path planning framework to address this gap. We formulate the problem as a multi-objective optimization that simultaneously considers safety, complete inspection coverage, path length, and communication quality. The core of our solution is an Improved Grey Wolf Optimizer (IGWO), which combines a genetic mutation strategy and a greedy leader update mechanism to enhance global search capability and avoid local optima. A nonlinear convergence factor is also evaluated as a candidate enhancement, but a full 23 ablation study reveals that it is functionally redundant with mutation and actively detrimental to the Elite-containing configurations (degrading the mean cost by 16–18%); it is, therefore, excluded from the recommended IGWO configuration. To evaluate the proposed framework, we adopt a dual-scenario validation strategy: in the mountainous setting, we employ a synthetic conical-peak terrain model with the standardized 3rd Generation Partnership Project (3GPP) Rural Macrocell (RMa) channel model; in the urban setting, we use real-world building footprints from OpenStreetMap (Hangzhou, China) with deterministic ray-tracing propagation modeling. Comprehensive simulations in both scenarios demonstrate that the proposed IGWO achieves an 88% success rate in dense urban areas, substantially outperforming the standard GWO (50%) and PSO (55%), and ranking second only to GA (99%) while delivering a more balanced performance across all evaluation metrics. Crucially, communication-aware paths reduce average outage duration by 100% in the mountainous scenario and 65.6% in the urban scenario while often yielding shorter paths. This work confirms that explicit communication modeling is indispensable for reliable UAV inspection and that the proposed IGWO offers a robust and scalable solution for future autonomous and cooperative power grid maintenance systems.