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Aiming at the problems of path optimization and collision of multiple robots, the obstacle avoidance control algorithm of warehouse handling robots is studied and a control algorithm based on potential ant colony is proposed. The moving trajectory of the robot in the process of transport is studied, and the space kinematics equation is given. The ant colony algorithm is used to optimize the classical artificial potential field algorithm, improve the global optimization ability and balance the relationship between gravity and repulsion. In the aspect of local obstacle avoidance of warehouse handling robots, the artificial potential field is optimized twice based on the strategy gradient algorithm, and the randomness of path selection when multiple robots work at the same time is improved by analyzing the probability of occurrence of the next action instruction. After testing, the proposed control algorithm has the shortest path and only takes 12.3s to complete a single transportation task. Moreover, under the condition of complex path planning, the number of collisions between robots is significantly less than that of the traditional obstacle avoidance control algorithm, which can meet the needs of warehousing and logistics through practical application.