UAV flight path optimisation based on improved RRT algorithm

被引：0

作者：

Zeng, Sheng ^{[1
]}

Yilin, Wu ^{[2
]}

Dai, Xian-Jun ^{[3
]}

机构：

[1] School of Electrical Engineering, Wanjiang Institute of Technology, Anhui, Ma’anshan

[2] ENAE Business School, Universidad de Murcia, Murcia

[3] College of Life Sciences, China Jiliang University, Zhejiang, Hangzhou

来源：

International Journal of Information and Communication Technology | 2025年 / 26卷 / 22期

关键词：

flight path; improve; RRT algorithm; UAV; unmanned aerial vehicle;

D O I：

10.1504/IJICT.2025.146905

中图分类号：

学科分类号：

摘要：

The fast search random tree (RRT) algorithm is an algorithm used for path planning, which aims to reduce the search distance of UAV during flight and find the optimal path. Search for viable paths in the environment by building a random tree. The basic steps of UAV RRT algorithm include initialisation, generating random node, finding nearest tree node, extending tree and generating path. The improved algorithm can accelerate the search speed of the whole search space, and can optimise the multi-dimensional environment, and has good adaptability to the uncertain environment. However, the traditional RRT algorithm is not guaranteed to find the optimal path. By improving the centralised RRT algorithm, the flight path of UAV can be optimised, and then the advantages and disadvantages of each can be compared. First, build space model and drone model space. Secondly, the artificial potential field algorithm, pruning algorithm and area limit algorithm are improved to improve the search efficiency. Copyright © 2025 Inderscience Enterprises Ltd.

引用

页码：23 / 39

页数：16

共 18 条

[1]

Chen H., Chen H-z., Liu Q., 3D formation path planning of multi-UAV based on improved artificial potential field method, Journal of System Simulation, 32, 3, pp. 414-420, (2022)

[2]

Chen J., Research on 3D Path Planning Method of UAV, (2022)

[3]

Ding X., Research on the Optimization of UAV Three-Dimensional Flight Path Planning and Vehicle-UAV Collaborative Delivery Path, (2023)

[4]

Feng Y., Zhou Z., Shen Y., Et al., Obstacle avoidance path planning based on improved RRT algorithm, Chinese Journal of Engineering Design, 8, 7, pp. 1-9, (2023)

[5]

Han J., Research on path planning based on improved RRT algorithm, Mechanical Engineering and Automation, 8, 6, pp. 31-33, (2023)

[6]

He X., Research on Optimization Method of Urban Logistics UAV Distribution Route, (2023)

[7]

Jia H., Fang L., Wang H., Adaptive path planning of robotic arm based on artificial potential field and informed-RRT* algorithm, Computer Integrated Manufacturing Systems, 2, 9, pp. 1-21, (2023)

[8]

Kong W., Research on 3D Path Planning Algorithm of UAV, (2023)

[9]

Li Z., Peng Q., Liu Q., Robot path planning with improved RRT~*FN algorithm, Modular Machine Tool & Automatic Processing Technology, 7, 12, pp. 12-16, (2023)

[10]

Liu C., Liu B., Lu E., Et al., Path planning of indoor mobile robot based on improved RRT algorithm, Combined Machine Tool & Automatic Processing Technology, 10, pp. 20-23, (2023)

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