Optimization of Urban Logistics Obstacle Avoidance UAV Path Based on Improved Crowned Porcupine Pig Algorithm

Path planning for unmanned aerial vehicles (UAVs) in complex urban logistics is a core component of UAV mission planning systems. In order to solve the problem of safe and efficient logistics drone path planning, this paper proposes a crowned porcupine Pig defense mechanism based on the crowned porcupine Pig optimization algorithm, which relies on four defense mechanisms: odor, sound, line of sight, and physical attack. This algorithm has made the following contributions: targeting the problem of urban logistics drone transportation tasks, and comprehensively considering the restrictions of different cities’ no fly airspace (different flight heights), minimizing economic costs, optimizing time efficiency, and improving drone performance. It has established an adjusted terrain map, obstacle size and range, and drone flight altitude to determine the optimal flight path of the drone from the starting point to the end point through the algorithm. The simulation results show that after 500 iterations of optimization using crowned porcupine Pig, the convergence of path planning is good. This article can provide a reference for drone path planning and a solution for drone path optimization.