Motion planning is a pivotal area of research for intelligent mobile robots, including unmanned aerial vehicles (UAVs). This paper focuses on the motion planning problem for fixed-wing UAVs and proposes a modified Dubins-Rapidly-Exploring Random Tree*(MD-RRT*) algorithm. The algorithm refines the sampling function by eliminating random angle sampling. It also enlarges the safety radius to reduce the computational load of collision detection. Then, a proof for the reasonable boundary value of the enlarged safety radius is provided. Additionally, it outlines the applicability conditions of the proposed algorithm compared to the original Dubins-RRT* algorithm. Through simulations, it demonstrates that the proposed algorithm enhances the overall computational efficiency of the algorithm at the expense of certain sampling boundaries and achieves shorter average paths.
Motion Planning for Fixed-Wing UAV Using Modified Dubins-RRT* Algorithm
Lect. Notes Electrical Eng.
International Conference on Guidance, Navigation and Control ; 2024 ; Changsha, China August 09, 2024 - August 11, 2024
2025-03-02
11 pages
Article/Chapter (Book)
Electronic Resource
English
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