ENERGY-AWARE PATH PLANNING FOR A QUADCOPTER USING GENERALIZED PARTICLE SWARM OPTIMIZATION
DOI:
https://doi.org/10.62985/j.huit_ojs.vol26.no2E.399Keywords:
Path planning, Particle swarm optimization, Generalized PSO, Obstacle avoidance, QuadcopterAbstract
This paper presents an integrated framework for energy-aware path planning of a quadcopter unmanned aerial vehicle (UAV). The ultimate objective is to generate a trajectory that simultaneously satisfies path-length constraints, collision avoidance, and mission goals while accounting for vehicle energy consumption. The path-planning objectives are combined into a multi-objective cost function to discover optimal solutions. The generalized particle swarm optimization (GEPSO) is then applied to manage the overall cost, considering real-world applications. Simulation and experimental results exhibit that the proposed framework achieves smoother trajectories and significant reductions in overall energy expenditure compared to energy-ignored planning strategies.
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