为解决移动机器人在丘陵山区不规则、崎岖地形等复杂果园环境下的路径规划问题，提出一种基于改进灰狼算法的移动机器人三维路径规划方法。通过模拟实际地理环境，建立三维果园地形及障碍物模型，构建路径规划目标函数模型。通过引入麻雀搜索算法（sparrow search algorithm, SSA）改进标准灰狼算法（grey wolf optimizer, GWO）的初始化方式、收敛因子、局部搜索能力及全局搜索能力。仿真实验结果表明，所提出的算法相较于其他算法，具有寻优速度快、路径规划距离最优、收敛速度快的优点，表明了本文方法的有效性和优越性。

To solve the path planning problem of mobile robots in complex orchard environments such as irregular and rugged terrain in hilly and mountainous areas, an improved grey wolf algorithm based 3D path planning method for mobile robots was proposed. By simulating the actual geographical environment, a three-dimensional orchard terrain and obstacle model was established, and a path planning objective function model was structed. By introducing the sparrow search algorithm (SSA) the initialization method, convergence factor, local search ability, and global search ability of the standard grey wolf optimization (GWO) were improved. The simulation experimental results show that the proposed algorithm has the advantages of fast optimization speed, optimal path planning distance, and fast convergence speed compared to other algorithms, indicating the effectiveness and superiority of the proposed method.