Path Planning of UAV in Cities Based on Improved RRT Algorithm

DOI

10.2991/978-94-6463-821-9_84How to use a DOI?

Keywords

UAV; Path Planning; RRT; Artificial Potential Field; Pruning Strategy

Abstract

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.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yifan Feng
PY  - 2025
DA  - 2025/08/31
TI  - Path Planning of UAV in Cities Based on Improved RRT Algorithm
BT  - Proceedings of the 2025 2nd International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2025)
PB  - Atlantis Press
SP  - 878
EP  - 887
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-821-9_84
DO  - 10.2991/978-94-6463-821-9_84
ID  - Feng2025
ER  -