目的 为了提高码垛机器人的工作效率，减小能量损耗，优化机器人末端抓手的工作轨迹。方法 建立机器人路径规划的数学模型，在此基础上对传统的蚁群算法进行改进，将环境中局部的机器人路径信息引入蚁群信息素的初始化和路径选择概率中，提高蚁群算法的收敛速度，并防止算法早熟，避免算法陷入局部最优。结果 仿真结果表明，改进后的蚁群算法收敛速度更快，能够在较短时间内规划出最佳路径。结论 所提方法能够明显提高码垛机器人最佳路径搜索能力，对于提升机器人运行效率具有重要指导意义。

The work aims to improve the working efficiency of palletizing robot, reduce the energy loss, and optimize the work trajectory of robot end hand. Firstly, the mathematical model of robot path planning was established. On the basis of this, the traditional ant colony algorithm was improved. The local robot path information in the environment was introduced into the initialization of ant pheromone and the path selection probability, to improve the convergence speed of ant colony algorithm and prevent the algorithm from precocity, and protect the algorithm from falling into local optimum. The simulation results showed that, the improved ant colony algorithm converged faster and could plan the optimal path in a short time. The proposed method can obviously improve the optimal path searching ability of the palletizing robot, and it is of great significance to improve the operation efficiency of the robot.