This paper provide an overview of the emerging trends and challenges in the field of decision-making of unmanned ground vehicles. Specifically, four important decision-making methods are analyzed, including the classical rule-based, the decision tree based, reinforcement learning based, and POMDP based decision-making system. Furthermore, we compare the pros and cons among these methods, and analyze the difficulties encountered in current decision-making systems. On the basis of these comparison and analysis, we suggest that the integration of different methods could improve the performance of the decision-making systems. Finally, we discuss the future development for the decision-making system and recommend to combine graph-based knowledge representation and learning-based method to tackle the complex task and traffic information in the decision-making process.


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    Titel :

    Review and Outlook of Decision-Making Methods in Unmanned Ground Vehicles


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Wu, Meiping (Herausgeber:in) / Niu, Yifeng (Herausgeber:in) / Gu, Mancang (Herausgeber:in) / Cheng, Jin (Herausgeber:in) / Qin, Lina (Autor:in) / Yang, Aihua (Autor:in) / Li, Junxiang (Autor:in) / Li, Yanlin (Autor:in) / Feng, Yu (Autor:in) / Liu, Liu (Autor:in)

    Kongress:

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



    Erscheinungsdatum :

    2022-03-18


    Format / Umfang :

    11 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch