Predator-Prey Pigeon-Inspired Optimization for UAV Three-Dimensional Path Planning

摘要

Pigeon-inspired optimization (PIO) is a new bio-inspired optimization algorithm. This algorithm searches for global optimum through two models: map and compass operator model is presented based on magnetic field and sun, while landmark operator model is designed based on landmarks. In this paper, a novel Predator-prey pigeon-inspired optimization (PPPIO) is proposed to solve the three-dimensional path planning problem of unmanned aerial vehicles (UAVs), which is a key aspect of UAV autonomy. To enhance the global convergence of the PIO algorithm, the concept of predator-prey is adopted to improve global best properties and enhance the convergence speed. The comparative simulation results show that our proposed PPPIO algorithm is more efficient than the basic PIO and particle swarm optimization (PSO) in solving UAV three-dimensional path planning problems.