AGV path planning method based on grey wolf optimization algorithm

The invention particularly relates to an AGV (Automatic Guided Vehicle) path planning method based on a grey wolf optimization algorithm. The method comprises the steps of constructing a mobile environment, setting a starting coordinate point and a target coordinate point of an AGV, adopting the grey wolf optimization algorithm, forming a fitness function by three target functions, synchronously updating positions of all grey wolf individuals in an iteration process, and finally outputting an optimal path. The optimal moving route of the AGV can be given in the three-dimensional space, and meanwhile the AGV is prevented from colliding and exceeding the space boundary. 本申请具体涉及一种基于灰狼优化算法的AGV小车路径规划方法，通过建构移动环境，设定AGV小车的起始坐标点和目标坐标点，采用灰狼优化算法，以三个目标函数组成适应度函数，迭代过程同步更新所有灰狼个体的位置，最终输出最优路径。本申请能够在三维空间内给出AGV小车的最佳移动路线，同时避免其发生碰撞和超出空间边界。