A Path Planning Method for Autonomous Flying Vehicles Using an Improved RRT* Algorithm

Autonomous flying vehicles are promising transportation of the future, which have the function of ground vehicles and low-altitude aircraft. To plan a feasible path effectively, an improved optimal rapidly-exploring random tree (RRT*) method is proposed. Firstly, a cost function considering driving efficiency and the energy consumption is established. Then, the cost of a known feasible path, which flies from the start point to the goal point directly, is calculated as a benchmark. According to the benchmark, the planning area is reduced to an elliptical area. The proposed method is verified by simulations with an actual cross-country environment. Results show that the computation time decreased by 11.3% compared with the basic RRT* method.