Dynamic Collision Avoidance Path Planning of Multi-UAV Based on Improved RRT Algorithm

With the continuous application of UAVs in various scenarios, the demand for path planning is also increasing, and multiple UAVs have to accomplish obstacle avoidance as well as avoid collision between UAVs during flight. To solve the multi-UAV path planning problem in a two-dimensional scene with multiple obstacles, an improved Rapidly Exploring Random Tree (RRT) algorithm based on dynamic collision avoidance with velocity obstacles is proposed. First, the target bias method is used for random sampling to avoid generating a large number of invalid branching paths. Then, the artificial potential field method is used to generate obstacle repulsion to realize static obstacle avoidance for UAVs. Finally, the collision avoidance velocity is generated based on the velocity obstacle method to prevent dynamic collisions between multiple UAVs. The experimental results show that the algorithm significantly reduces the trajectory computation time compared with the traditional RRT algorithm, and at the same time ensures high reliability compared with RRT combined with artificial potential field method.