UAV 3-Dimension Flight Path Planning Based on Improved Rapidly-exploring Random Tree

Abstract

The traditional RRT algorithm is difficult to realize the 3-dimensional flight path planning of unmanned aerial vehicle (UAV). In view of the complexity and particularity of the 3-dimensional environment, an improved RRT algorithm is proposed. According to the specific task requirements and the performance limitation of UAV, the flight height constraint, the maximum range constraint and the pitch angle constraint are designed. A new node acceptance criteria and path adjustment method is proposed for the 3-dimensional environment. From the theoretical point of view, the convergence of the improved algorithm is analyzed. On the other hand, a 3-dimensional simulation environment is established for algorithm test. The simulation results show that the improved RRT algorithm can realize the path planning in three-dimensional environment and meet the mission requirements of UAV.