TY - GEN
T1 - Obstacle avoidance of UAV based on neural networks and interfered fluid dynamical system
AU - Wang, Yanxiang
AU - Wang, Honglun
AU - Wen, Jiayun
AU - Lun, Yuebin
AU - Wu, Jianfa
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/11/27
Y1 - 2020/11/27
N2 - Obstacle avoidance is the prerequisite guarantee for the unmanned aerial vehicle (UAV) to fly safely in the three-dimensional dynamic complex environment. In this paper, a three-dimensional real-time obstacle avoidance method is proposed by combining neural network and the Interfered Fluid Dynamical System (IFDS) for the first time. First, in order to solve the problem of insufficient samples, sample data are generated based on the sparrow search algorithm (SSA) and receding horizon control (RHC). Second, training neural network offline, the relative position between UAV, destination and obstacle from sample data as input of neural network, and the IFDS parameters are used as the feature extraction of the output terminal of the neural network. Third, the trained neural network is used to adjust the coefficients of the IFDS according to environment in real time. Finally, the simulations demonstrate effectiveness of the proposed method.
AB - Obstacle avoidance is the prerequisite guarantee for the unmanned aerial vehicle (UAV) to fly safely in the three-dimensional dynamic complex environment. In this paper, a three-dimensional real-time obstacle avoidance method is proposed by combining neural network and the Interfered Fluid Dynamical System (IFDS) for the first time. First, in order to solve the problem of insufficient samples, sample data are generated based on the sparrow search algorithm (SSA) and receding horizon control (RHC). Second, training neural network offline, the relative position between UAV, destination and obstacle from sample data as input of neural network, and the IFDS parameters are used as the feature extraction of the output terminal of the neural network. Third, the trained neural network is used to adjust the coefficients of the IFDS according to environment in real time. Finally, the simulations demonstrate effectiveness of the proposed method.
KW - Intefered Fluid Dynamic System (IFDS)
KW - Neural network.
KW - Obstacle avoidance
KW - Receding horizon control (RHC)
KW - Sparrow search algorithm (SSA)
KW - Unmanned aerial vehicle (UAV)
UR - https://www.scopus.com/pages/publications/85098958401
U2 - 10.1109/ICUS50048.2020.9274988
DO - 10.1109/ICUS50048.2020.9274988
M3 - 会议稿件
AN - SCOPUS:85098958401
T3 - Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020
SP - 1066
EP - 1071
BT - Proceedings of 2020 3rd International Conference on Unmanned Systems, ICUS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Unmanned Systems, ICUS 2020
Y2 - 27 November 2020 through 28 November 2020
ER -