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Efficient power inspection is crucial for maintaining a stable power system. During an inspection, unmanned aerial vehicles (UAVs) usually need to be recharged due to the wide geographical range of inspection and the limited battery capacity of UAVs. This limitation makes the problem more challenging that requires not only optimizing the task execution order, but also taking the chargings of UAVs into consideration. In order to address this complex problem, this work first formulates the UAV power inspection planning problem with charging stations. After that, we propose a new heuristic navigation model, in which UAVs can follow a heuristic rule to decide where to go next based on both its own information and task-related information. To obtain the heuristic rule, we design a set of features to describe the status of the UAVs and task completion. Then a genetic programming (GP) algorithm is introduced to evolve …