A Solution to UAV Route Planning Problem Based on Chaotic Genetic Algorithm

The paper addresses un-crewed aerial vehicles (UAV) route planning with its tracking trajectory of preventing obstacles by implementing a chaotic genetic algorithm (CGA). In complex environments, the dynamic 2D-grid model of low-altitude aircraft is discretized according to the constraints of 3D-space, divided into several 2D spaces. The improved CGA code is used to optimize the UAV's route planning phase for obstacles in space. The experimental results depict that the proposed scheme can effectively design an estimated optimal path and overcome route planning in the 3D space by converting engineering practicability spaces.