Optimal Energy Consumption Path Planning for Unmanned Aerial Vehicles Based on Improved Particle Swarm Optimization

In order to enhance the energy efficiency of unmanned aerial vehicles (UAVs) during flight operations in mountainous terrain, this research paper proposes an improved particle swarm optimization (PSO) algorithm-based optimal path planning method, which effectively reduces non-essential consumption UAV through a reasonable method. First, designs 3D method based on PSO algorithm with goal achieving operations. Then, overcome limitations classical algorithm, such as poor global search capability and susceptibility local optimality, parameter adaptive deep deterministic policy gradient (DDPG) is introduced. This dynamically adjusts main parameters by monitoring state solution set. Finally, improvement applied terrain environments, energy-consuming path-planning for UAVs proposed. Simulation results show that proposed operations, especially more complex scenarios.