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    ARTICLE

    3D Path Optimisation of Unmanned Aerial Vehicles Using Q Learning-Controlled GWO-AOA

    K. Sreelakshmy1, Himanshu Gupta1, Om Prakash Verma1, Kapil Kumar2, Abdelhamied A. Ateya3, Naglaa F. Soliman4,*

    Computer Systems Science and Engineering, Vol.45, No.3, pp. 2483-2503, 2023, DOI:10.32604/csse.2023.032737

    Abstract Unmanned Aerial Vehicles (UAVs) or drones introduced for military applications are gaining popularity in several other fields as well such as security and surveillance, due to their ability to perform repetitive and tedious tasks in hazardous environments. Their increased demand created the requirement for enabling the UAVs to traverse independently through the Three Dimensional (3D) flight environment consisting of various obstacles which have been efficiently addressed by metaheuristics in past literature. However, not a single optimization algorithms can solve all kind of optimization problem effectively. Therefore, there is dire need to integrate metaheuristic for general acceptability. To address this issue,… More >

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