TY - GEN
T1 - UAV Trajectory Planning Algorithms in Uncertain Environments
AU - She, Yang
AU - Song, Chao
AU - Li, Jiarui
AU - Li, Bo
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - UAV trajectory planning has attracted significant attention in recent years as one of the important prerequisites for ensuring the safe completion of UAV missions. However, in the event of a complex and uncertain mission environment, the real-time collision-free trajectory planning for UAVs will undoubtedly present a significant challenge. In this paper, for the problem of real-time UAV trajectory planning in uncertain environments, we propose a UAV trajectory planning method based on an improved artificial potential field(IAPF) algorithm, which solves problem of goals non-reachable with obstacles nearby (GNRON) and the local-minima problem, and is able to avoid complex obstacles in real time, including moving, sudden and concave obstacles. Firstly, to address the GNRON problem, we propose the concept of distance repulsion, which is designed to minimize the repulsive potential field at the location of goal point. Besides, with regard to the local-minima problem, we propose the concept of rotational repulsion, which enables the UAV to circumvent concave obstacles. In addition, compared to the conventional artificial potential field(APF) method which only considers the distance between the UAV and the obstacle, the IAPF algorithm takes the velocity difference between the two into account and proposes a velocity potential field for more effective avoidance of moving obstacles. Finally, the simulation experiment verifies that, compared with the traditional APF method, the algorithm proposed in this paper is capable of addressing the problem of GNRON and local-minima, and has the feasibility and effectiveness for the UAV trajectory planning problem in uncertain environments.
AB - UAV trajectory planning has attracted significant attention in recent years as one of the important prerequisites for ensuring the safe completion of UAV missions. However, in the event of a complex and uncertain mission environment, the real-time collision-free trajectory planning for UAVs will undoubtedly present a significant challenge. In this paper, for the problem of real-time UAV trajectory planning in uncertain environments, we propose a UAV trajectory planning method based on an improved artificial potential field(IAPF) algorithm, which solves problem of goals non-reachable with obstacles nearby (GNRON) and the local-minima problem, and is able to avoid complex obstacles in real time, including moving, sudden and concave obstacles. Firstly, to address the GNRON problem, we propose the concept of distance repulsion, which is designed to minimize the repulsive potential field at the location of goal point. Besides, with regard to the local-minima problem, we propose the concept of rotational repulsion, which enables the UAV to circumvent concave obstacles. In addition, compared to the conventional artificial potential field(APF) method which only considers the distance between the UAV and the obstacle, the IAPF algorithm takes the velocity difference between the two into account and proposes a velocity potential field for more effective avoidance of moving obstacles. Finally, the simulation experiment verifies that, compared with the traditional APF method, the algorithm proposed in this paper is capable of addressing the problem of GNRON and local-minima, and has the feasibility and effectiveness for the UAV trajectory planning problem in uncertain environments.
KW - artificial potential field algorithm
KW - drone trajectory planning
KW - uncertain environment
UR - http://www.scopus.com/inward/record.url?scp=85218071280&partnerID=8YFLogxK
U2 - 10.1109/ICUS61736.2024.10839805
DO - 10.1109/ICUS61736.2024.10839805
M3 - 会议稿件
AN - SCOPUS:85218071280
T3 - Proceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
SP - 713
EP - 718
BT - Proceedings of 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
A2 - Song, Rong
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 IEEE International Conference on Unmanned Systems, ICUS 2024
Y2 - 18 October 2024 through 20 October 2024
ER -