TY - GEN
T1 - A Rapid Path Planning Method Based on RRT-BAS for Unmanned Aerial Vehicles in Urban Environments
AU - Zhu, Yuanjun
AU - Yang, Bingjie
AU - Zhang, Xuejun
AU - Zhang, Weidong
N1 - Publisher Copyright:
© Beijing Paike Culture Commu. Co., Ltd. 2025.
PY - 2025
Y1 - 2025
N2 - This paper proposes a rapid path planning algorithm based on the Rapidly-Exploring Random Tree (RRT), enhanced with Beetle Antennae Search (BAS) to improve unmanned aerial vehicle (UAV) operational efficiency in complex urban environments. The algorithm combines the random expansion capability of RRT with the directed exploration feature of BAS to quickly generate an optimized path in three-dimensional (3D) environments. The objective is to create a feasible, collision-free path from a designated start point to a target location, considering terrain complexity. Simulation results show that, in terms of both path quality and convergence speed, the RRT-BAS algorithm significantly outperforms RRT, BAS, RRT*, and RRT*-BAS.
AB - This paper proposes a rapid path planning algorithm based on the Rapidly-Exploring Random Tree (RRT), enhanced with Beetle Antennae Search (BAS) to improve unmanned aerial vehicle (UAV) operational efficiency in complex urban environments. The algorithm combines the random expansion capability of RRT with the directed exploration feature of BAS to quickly generate an optimized path in three-dimensional (3D) environments. The objective is to create a feasible, collision-free path from a designated start point to a target location, considering terrain complexity. Simulation results show that, in terms of both path quality and convergence speed, the RRT-BAS algorithm significantly outperforms RRT, BAS, RRT*, and RRT*-BAS.
KW - Beetle Antennae Search
KW - Rapid Path Planning
KW - Rapidly-Exploring Random Tree
KW - Unmanned Aerial Vehicle
UR - https://www.scopus.com/pages/publications/105002566674
U2 - 10.1007/978-981-96-3977-9_35
DO - 10.1007/978-981-96-3977-9_35
M3 - 会议稿件
AN - SCOPUS:105002566674
SN - 9789819639762
T3 - Lecture Notes in Electrical Engineering
SP - 315
EP - 323
BT - The Proceedings of 2024 International Conference on Artificial Intelligence and Autonomous Transportation - Volume VI
A2 - Liu, Jun
A2 - Li, Wang
A2 - Geng, Xiongfei
A2 - Zhang, Ke
A2 - Ji, Honghai
A2 - Li, Kailong
PB - Springer Science and Business Media Deutschland GmbH
T2 - International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024
Y2 - 6 December 2024 through 8 December 2024
ER -