Path Planning of UAV in Cities Based on Improved RRT Algorithm
Yifan Feng · Advances in engineering research/Advances in Engineering Research · 2025
With the development of UAV technology and low-altitude economy, path planning is an important link for UAVs to perform tasks in urban mission space.In urban environments, UAVs face many challenges, such as complex building layouts, large amounts of green belts and so on.RRT (rapidly exploring random tree) algorithm serves as a stochastic search method that employs randomly generated samples to expand its tree structure incrementally, enabling efficient exploration of task spaces.Aiming at the shortcomings of traditional RRT algorithm, such as long exploration time and poor quality of path, some improved algorithms and strategies for RRT algorithm in the past were summarized, and a new improved RRT algorithm named RRT-FieldPrune combining artificial potential field guided exploration and pruning strategy was proposed.After performing multiple simulation and using the mean value as the final result, the results are then contrasted against the traditional RRT algorithm, The algorithm named RRT-FieldPrune proposed in this paper saves 73.0% in path search time, reduces the path by 20.86%, and 91.30% of the bending times are eliminated, significantly improving the path quality and reflecting better performance.