The multicopter formation is widely used in many different complex circumstances. And the semi-autonomous multicopter formation controlled with a single pilot on the ground draws people’s attention due to the great adaptability to various kinds of environments. In this paper, we focus on the problem of passing through narrow channels with semi-autonomous multicopter formation. Similar to the definition for a single multicopter, the altitude hold mode for the multicopter formation is defined first. Then, the formation decision-making and formation low-level control of the altitude hold mode are proposed one by one. Finally, a hardware-in-the-loop simulation and a real experiment are performed with four multicopters to pass through a narrow channel.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Semi-autonomous Multicopter Formation Control Under One Remote Pilot in GPS-Denied Environment


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Wu, Meiping (editor) / Niu, Yifeng (editor) / Gu, Mancang (editor) / Cheng, Jin (editor) / Gao, Yan (author) / Wei, Donghui (author) / Bai, Chenggang (author) / Quan, Quan (author)

    Conference:

    International Conference on Autonomous Unmanned Systems ; 2021 ; Changsha, China September 24, 2021 - September 26, 2021



    Publication date :

    2022-03-18


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Semi-autonomous Multicopter Formation Control Under One Remote Pilot in GPS-Denied Environment

    Gao, Yan / Wei, Donghui / Bai, Chenggang et al. | British Library Conference Proceedings | 2022



    Tethered Multicopter Guidance in GPS-Denied Environments Through Reinforcement Learning

    Al-Radaideh, Amer / Selje, Robert A. / Coraspe, Daniel et al. | AIAA | 2023


    Tethered Multicopter Guidance in GPS-Denied Environments Through Reinforcement Learning

    Al-Radaideh, Amer / Selje, Robert A. / Coraspe, Daniel et al. | TIBKAT | 2023