一种改进灰狼优化算法的移动机器人路径规划方法

针对移动机器人路径规划中存在易陷入局部最优、收敛速度慢、搜索路径消耗成本较大等问题,提出一种改进的灰狼优化算法对移动机器人进行路径规划.建立移动机器人避障路径规划二维空间模型,将灰狼优化算法中的线性收敛因子转变为非线性收敛因子,并将灰狼优化算法与粒子群算法结合,给予Omega狼意识;加入协同量子化优化灰狼群体;采用4类...

A Path Planning Method for Mobile Robot Based on Improved Grey Wolf Optimizer

Aiming at the problems of mobile robot path planning, such as prone to fall into local optimum, slow convergence speed and high cost of searching paths, an improved grey wolf optimizer was proposed for mobile robot path planning. A two dimensional space model of obstacle avoidance path planning related to mobile robots was established, the linear convergence factor of the grey wolf optimizer was transformed into the nonlinear convergence factor, and the grey wolf optimizer algorithm was combined with particle swarm optimizer to give Omega wolf consciousness; collaborative quantization was added to optimize the grey wolf population. 4 types of international test function were used to prove that the improved algorithm had better convergence accuracy and stability. The improved algorithm was applied to the mobile robot path planning, and compared with the particle swarm optimization algorithm and the original gray wolf optimizer. The simulation results verify the effectiveness of the proposed algorithm.