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An ant colony potential field algorithm was designed to solve the problem of poor global optimization ability and easy collision with moving obstacles in existing building material transport robots. Firstly, the accumulation process of individual pheromone concentration under ant colony algorithm is analyzed, and the cooperation of gravity and repulsion force is solved by constructing artificial potential field, which is regarded as an important constraint for selecting the heuristic factor of ant colony algorithm. Secondly, SA algorithm is introduced to optimize the ant colony potential field algorithm twice, and the cooling process is regarded as a global optimization process. Finally, a mass point model is constructed in terms of local collision avoidance, and a penalty function is established by evaluating the robot"s current position, running speed and obstacle position, and the penalty function value is reduced to the minimum to avoid collision with obstacles. The experimental results show that the proposed algorithm has higher iterative efficiency, and the shortest travel distance and time are 110.6m and 115.1s respectively under complex dynamic conditions, and there is no local collision with other mobile robots.