UAV Path Planning Algorithm based on Improved Rapidly-exploring Random Tree
Aiming at the problems of high randomness of sampling point generation and poor smoothness of planning path in rapidly-exploring random tree UAV path planning algorithms,an UAV path planning algorithm based on improved rapidly-exploring random tree is proposed.During the tree expansion process,a detection field that limits the generation range of sampling points is introduced,and the genera-tion strategy of sampling points is changed,enabling the algorithm to quickly converge to the target and bypass the threat of obstacles.In addition,the improved algorithm also cuts the redundant points of the in-itial track,and uses B-spline curve method to improve the smoothness of the track.The simulation results demonstrate that the proposed path planning algorithm can reduce the average path length by 21.75%,the average number of search tree nodes by 75.78%,and the average calculation time by 48.04%com-pared to the rapidly-exploring random tree based UAV path planning algorithm.
unmanned aerial vehiclepath planning algorithmrapidly-exploring random tree
万方数据
维普
