基于量子粒子群算法的机器人路径规划

提出了一种基于量子粒子群优化算法的移动机器人全局路径规划方法。首先对环境地图进行建模,通过坐标变换在路径的起点与终点之间建立新地图,然后利用量子粒子群优化算法获得一条全局最优路径。该方法模型简单,算法复杂度低,收敛速度快,而且模型不依赖于障碍物的形状。仿真实验证实了该方法的可行性与有效性。

Path Planning for Robots Based on Quantum-behaved Particle Swarm Optimization

A global path planning approach based on quantim-behaved particle swarm optimization (QPSO ) is presented. The first step is to make a new map between starting -point and goal -point through coordinate system transferring. Then the QPSO is introduced to get a global optimized path. This algorithm has a simple model, low complexity, rapid convergencend no restrict on the shapes of obstacles. Simulation results are provided to verify the effectivenss and practicability.