Welcome to Acta Armamentarii ! Today is

Acta Armamentarii ›› 2024, Vol. 45 ›› Issue (8): 2761-2773.doi: 10.12382/bgxb.2023.0611

Previous Articles     Next Articles

A UAV Trajectory Optimization Method Based on RRT-Dubins

WANG Dongzhen1,*(), ZHANG Yue1, ZHAO Yu1, HUANG Daqing2   

  1. 1 College of Information Engineering, Yangzhou University, Yangzhou 225000, Jiangsu, China
    2 Research Institute of Unmanned Aircraft, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, China
  • Received:2023-06-26 Online:2024-01-19
  • Contact: WANG Dongzhen

Abstract:

A unmanned aerial vehicle (UAV) trajectory optimization method based on the rapidly-exploring random trees (RRT) algorithm and Dubins curves is proposed to address the problem of UAV trajectory planning in multi-obstacle environments. The initial and final poses, turning radius, and trajectory length, and first-order smoothness constraint of UAV are considered in the trajectory planning. The RRT algorithm and a pruning optimization method based on a greedy algorithm are utilized to plan the feasible discrete waypoints that satisfy the obstacle avoidance requirements in a two-dimensional task space. Multiple Dubins curves are employed to smoothly connect the waypoints. A multi-constraint trajectory optimization mathematical model is established based on the UAV's initial and final poses, and the constraints related to the UAV's performance and obstacles. The particle swarm optimization (PSO) algorithm is employed to determine the curve types and optimize the poses at the curve connections and the curve radii, thereby obtaining the shortest trajectory. Simulated results demonstrate that the proposed method reduces the average trajectory length by 11.48% in various scenarios with different numbers of obstacles and varying initial and final positions, while satisfying the UAV's kinematic constraints and avoiding obstacles compared to other methods.

Key words: unmanned aerial vehicle trajectory planning, rapidly-exploring random trees algorithm, Dubins curve, particle swarm optimization algorithm, trajectory optimization

CLC Number: