An Efficient Trajectory Planning Algorithm for UAV

Proper trajectory planning can ensure flight safety, facilitate Unmanned aerial vehicle(UAV) efficiency and reduce cost. A trajectory planning strategy is proposed in this paper, which combines depth and breadth exploration based on enhanced kd-tree algorithm. The simulation results show that compared with the traditional PRM algorithm, RRT algorithm, RRT<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">*</sup> algorithm, 4-neighborhood A* algorithm and 8-neighborhood A* algorithm. This paper reduces runtime by 61.81% at most, and the distance by 25.65% at most in general environment. And it reduces runtime by 84.53% at most, and the distance by 67.16% at most in narrow environment. The proposed algorithm also has others advantages. Specifically, the planned trajectory is farther away from the obstacles, the number of turns in the trajectory is less, the turning angle is larger and the higher the success rate of trajectory planning in narrow environment, which ensures the safety of UAV flight.