二进制粒子群算法融合遗传算法路径规划方法

Path Planning Method Based on Binary Particle Swarm Optimization and Genetic Algorithm

针对粒子群算法应用于连续模型时难以处理离散性的问题,运用二进制粒子群算法搭配栅格地图,提高路径规划的效率,降低算法复杂度。融合算法用于路径规划,避免了早熟收敛并陷入局部最优解的问题,调节算法的局部收敛和全局规划能力。仿真结果表明,该算法能够获得全局最优路径。

Aiming at the problem that particle swarm algorithm is difficult to deal with discreteness when it is applied to continuous model, binary particle swarm algorithm is used to match grid map to improve the efficiency of path planning and reduce the complexity of algorithm. Fusion algorithm for path planning, which avoids the problem that traditional particle swarm is easy to premature convergence and fall into local optimal solution, and adjusts the local convergence and global planning ability of the algorithm. The simulation results show that the algorithm can obtain the global optimal path.