In this article, the problem of air-ground vehicles path planning is investigated. The objective is to navigate each vehicle from its starting position to the intended destination, while avoiding collisions with obstacles and other vehicles. First, by combining the objective functions of unmanned ground vehicle (UGV) and unmanned aerial vehicles (UAVs) with the constraints of system equations, control constraints and obstacle avoidance constraints, the vehicles’ path planning is formulated as multiple model predictive control (MPC) problems. Second, considering the interdependencies inherent in these optimization problems, we employ an assumed state method to decouple them effectively. Third, the control inputs of the UGV and UAVs are obtained by solving quadratic programming problems and thus the vehicles’ path can be obtained. Finally, a simulation example is shown to illustrate the effectiveness of the proposed path planning method.


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    Titel :

    Unmanned Air-Ground Vehicles Path Planning Using Model Predictive Control


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Jia, Limin (Herausgeber:in) / Yao, Dechen (Herausgeber:in) / Ma, Feng (Herausgeber:in) / Zhang, Liguo (Herausgeber:in) / Chen, Yuejian (Herausgeber:in) / Xue, Qingwan (Herausgeber:in) / Gu, Yuanwen (Autor:in) / Wang, Mi (Autor:in) / Wu, Huaining (Autor:in) / Li, Chenlong (Autor:in)

    Kongress:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Erscheinungsdatum :

    28.03.2025


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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