A major limitation of current battery-powered Unmanned Aerial Vehicles (UAVs) is their finite onboard energy, which restricts both flight duration and the range of missions they can effectively complete. To overcome this challenge and extend flight times, reducing the vehicle's energy consumption is crucial. Various strategies have been explored in the literature to achieve this, including advancements in UAV design and materials, the incorporation of energy-capturing systems, and the development of energy-minimizing control approaches. This work focuses on optimizing control strategies to minimize energy consumption. Specifically, the aim is to improve the efficiency of a hexarotor supplied by a Lithium-Polymer (Li-Po) battery as it follows a designated reference position by introducing innovative high-level energy-saving control techniques. To achieve this, three metaheuristic algorithms are developed to address the optimization problem: Grey Wolf Optimizer, Particle Swarm Optimization and Genetic Algorithm. All methods are implemented and validated using the MATLAB/Simulink simulation environment.


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    Title :

    Optimal Energy-Efficient Trajectory Planning for Multirotor UAVs


    Contributors:


    Publication date :

    2025-02-11


    Size :

    432802 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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