This research presents a novel approach for missions of Coverage Path Planning (CPP) carried out by a UAVs in a 3D environment. These missions are focused on path planning to cover a certain area in an environment in order to carry out tracking, search or rescue tasks. The methodology followed uses an optimization process based on the Differential Evolution (DE) algorithm in combination with the Fast Marching Square (FM2) planner. The DE algorithm evaluates a cost function to determine what the zigzag path with the minimum cost is, according to the steering angle of the zigzag bands.
This optimization process allows achieving the most optimal zigzag path in terms of distance traveled by the UAV to cover the whole area. Then, the FM2 method is applied to generate the final path according to the steering angle of the zigzag bands resulting from the DE algorithm. The approach generates a feasible path free from obstacles, keeping a fixed altitude flight over the ground. The flight level, smoothness and safety of the path can be modified by two adjustment parameters included in our approach. Simulated experiments carried out in this work demonstrate that the proposed approach generates the most optimal zigzag path in terms of distance, safety and smoothness to cover a certain whole area, keeping a determined flight level with successful results.