Obstacle Avoidance Control Method for Warehouse Handling Robots Based on Potential Ant Colony Algorithm
Existing obstacle avoidance control algorithms for warehouse handling robots are prone to path optimization and falling into local optimization,and multiple robot operations are prone to collisions simultaneously.To address these issues,,this paper studies the obstacle avoidance control algorithm of warehouse handling robots,proposes a control algorithm based on potential ant col-ony,researches the moving trajectory of the robot in the process of transport,and describes the space kinematics equation.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 local obstacle avoidance of warehouse handling robots,the artificial potential field undergoes the secondary optimization based on the strategy gradient algorithm,which improves the randomness of path selection dur-ing multiple robots operating by analyzing the occurrence probability of the next operation instruction.After testing,the results show that the proposed control algorithm has the shortest path,and it takes only 12.3 s to complete single transportation task.Moreover,under the complex path planning conditions,the number of collisions between robots is significantly lower than that of the traditional obstacle avoidance control algorithms,which can improve the efficiency of warehousing and logistics management through practical application.
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