Autonomous Obstacle Avoidance of AGV Based on Improved Ant Colony Algorithm
An improved ant colony algorithm was proposed to address the shortcomings of traditional ant colony algorithms in AGV task scheduling efficiency and path obstacle avoidance problems.First,by introducing the path busy value,the path pheromone concentration in the ant colony algorithm was upgraded to improve the quality of the path planning solution;Secondly,random influence factors were added to the heuristic pheromone concentration to improve the search efficiency of the algorithm.Then,based on the improved ant colony algorithm,multiple path planning parameters and work operation impact parameters were introduced,and basic scheduling rules and task priorities were formulated for AGV to propose a comprehensive obstacle avoidance strategy to solve the conflict problem.The simulation experimental results showed that the improved ant colony algorithm could evaluate path utilization and plan the optimal path.It had obvious advantages in multi task scheduling efficiency and could effectively achieve autonomous obstacle avoidance and solve collision problems.
scheduling efficiencyroute planningautonomous obstacle avoidanceAGVimproved ant colony algorithm
万方数据
维普
