An Elliptical Tangent Graph Method Based on Multi-source Information for UAV Path Planning

Path planning is one of important tasks for unmanned aerial vehicles (UAVs) to achieve autonomous flight. Moreover, the solution efficiency and solution accuracy are usually two conflicting objectives in UAV path planning problem, especially for complex static environments. To alleviate the above issue, an elliptical tangent graph method based on multi-source information (ETG-MI) is proposed in the current study. In the proposed ETG-MI algorithm, the target guidance information is first used to generate candidate waypoints via elliptical tangent graph method, and then a novel heuristic rule is utilized to select promising waypoints. Additionally, a waypoint selection method is proposed to eliminate low-quality detour waypoints. Finally, the cubic B-spline curve method is used to smooth the final obtained path for meeting the actual flight requirements of UAV. The proposed algorithm is compared with four state-of-the-art path planning methods under different scenarios. The experimental results demonstrate that the proposed ETG-MI is capable of finding an optimal feasible path for different environments with various types of obstacles. Moreover, the proposed algorithm performs better than other competitors in simple maze-like environments.