In recent years, vision technology is more and more widely used in aviation. The purpose of this paper is to realize the autonomous landing of the aircraft, and complete a series of processes from algorithm design to verification effect on the X-Plane simulation flight platform, so as to do some forward-looking work for the application and verification of AI algorithm in the field of aircraft landing. In the existing work, algorithm selection and simulation verification have been realized. In this paper, the VGG16 convolutional neural network is built firstly. The input of the network is the preprocessed pictures collected during landing, and the output is the four manipulations of the joystick in longitudinal, transverse, heading and throttle. After the analysis of training results, the algorithm is verified in X-Plane environment. The experimental results show that the method is verified and demonstrated in the X-Plane environment.


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    Title :

    Research on Autonomous Landing Method of Flying Vehicle Based on Deep Learning


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Deng, Yimin (editor) / Xiulin, Zhang (author) / Chong, Zhen (author) / Lei, Quxiao (author) / Yifeng, Wang (author) / Yuangan, Li (author) / Jingcheng, Zhang (author) / Ke, Li (author)

    Conference:

    International Conference on Guidance, Navigation and Control ; 2022 ; Harbin, China August 05, 2022 - August 07, 2022



    Publication date :

    2023-01-31


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




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