Abstract:Aiming at the challenges of high path planning complexity, complex regional boundaries, and idle aircraft resources faced by multi-UAVs in grasslands, fields, and other complex scenarios, an efficient and load-balanced multi-UAV coverage path planning framework was proposed. The framework consisted of two core elements: first, an innovative two-step construction strategy of “recursive decomposition-variable neighborhood simulated annealing algorithm”. The strategy took the minimization of the total sub-polygon width as the stage goal, firstly, using the convex decomposition property of concave polygons to design the recursive decomposition method to minimize the width and localization, and then, embedding the recursive decomposition into the improved simulated annealing algorithm with variable neighborhood to achieve the width and global minimization. Secondly, a task assignment method based on UAV performance index, which calculated the performance index based on UAV speed and bypass spacing, assigned the operation area blocks accordingly and planned the multi-trip paths in combination with the range capability, aiming to equalize the task duration of each aircraft. Simulation experiments showed that the proposed two-step construction strategy can find the width and the global minimum convex decomposition scheme in all test cases, and the width were reduced by 9.072, 5.169, and 2.869 percentage points, respectively, compared with the improved genetic algorithm in the test cases of 5, 6, 7 concave vertices;the coefficients of variation of the task duration obtained from the performance index-based task assignment method were as low as 4.02%~7.33%, which can effectively realize the equalization of task duration, effectively achieved mission duration equalization.