The environment map is the basis of robot navigation. Autonomous robot exploration is the process by which a robot autonomously constructs a map in an unknown environment. How to make the robot reduce the traveling distance when completing an unknown environment is a worthwhile research problem. This work proposes a transformer-based decision network for autonomous exploration and a deep reinforcement learning framework for autonomous robot exploration tasks. Experiments show that our proposed method is feasible and saves an average of 6.7% on distance traveled compared to traditional methods.


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    Titel :

    A Transformer-Based Robot Autonomous Exploration Method


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Liu, Lianqing (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Fu, Wenxing (Herausgeber:in) / Qu, Yi (Herausgeber:in) / Wang, Rui (Autor:in) / Zhao, Xin (Autor:in) / Lyu, Ming (Autor:in) / Zhang, Jie (Autor:in)

    Kongress:

    International Conference on Autonomous Unmanned Systems ; 2024 ; Shenyang, China September 19, 2024 - September 21, 2024



    Erscheinungsdatum :

    28.03.2025


    Format / Umfang :

    10 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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