Path planning of inventory UAV based on adaptive fireworks algorithm

This article focuses on the problem of unmanned aerial vehicle (UAV) trajectory planning in inventory counting. Considering the flying environment area, the UAV trajectory planning model under multiple constraint conditions is established with the goal of minimizing the total cost of trajectory length, yaw angle cost, and obstacle threat cost. An adaptive fireworks algorithm (AFWA) has been proposed. An adaptive explosion radius transformation strategy is proposed for fireworks with different adaptations. An elite Gaussian substitution selection method is designed to avoid the algorithm falling into local optimality. In the trajectory planning problem of UAVs in smart inventory, by simulating the explosion process of fireworks, the algorithm can continuously generate new solutions and quickly approximate the global optimal solution. The comparison results show that the adaptive fireworks algorithm has great advantages in convergence speed, solution efficiency and robustness, and can optimize the UAV inventory path, improve inventory efficiency and accuracy, and reduce flight time and energy consumption.