Quad-Rotor Unmanned Aerial Vehicle Path Planning Based on the Target Bias Extension and Dynamic Step Size RRT* Algorithm

Abstract

For the path planning of quad-rotor UAVs, the traditional RRT* algorithm has weak exploration ability, low planning efficiency, and a poor planning effect. A TD-RRT* algorithm based on target bias expansion and dynamic step size is proposed herein. First, random-tree expansion is combined with the target bias strategy to remove the blindness of the random tree, and we assign different weights to the sampling point and the target point so that the target point can be quickly approached and the search speed can be improved. Then, the dynamic step size is introduced to speed up the search speed, effectively solving the problem of invalid expansion in the process of trajectory generation. We then adjust the step length required for the expansion tree and obstacles in real time, solve the opposition between smoothness and real time in path planning, and improve the algorithm’s search efficiency. Finally, the cubic B-spline interpolation method is used to modify the local inflection point of the path of the improved RRT* algorithm to smooth the path. The simulation results show that compared with the traditional RRT* algorithm, the number of iterations of path planning of the TD-RRT* algorithm is reduced, the travel distance from the starting position to the end position is shortened, the time consumption is reduced, the path route is smoother, and the path optimization effect is better. The TD-RRT* algorithm based on target bias expansion and dynamic step size significantly improves the planning efficiency and planning effect of quad-rotor UAVs in a three-dimensional-space environment.