Path Planning of Logistics Robot Based on Improved Ant Colony Algorithm
The article proposes various improvement methods to address the shortcomings of traditional ant colony algorithms.Firstly,the artificial potential field gravity adjustment heuristic information function is introduced to enhance the guidance towards the target point.Secondly,a strategy of dynamically adjusting the increment of pheromones is adopted to improve the algorithm's tendency to get stuck in local optima and slow convergence speed during search.Finally,the triangular pruning method is used to remove redundant nodes and lines,in order to reduce the length of the robot's path and the number of turns,making the planned path more suitable for robot travel.Through these improvement methods,the efficiency and quality of ant colony algorithm in logistics robot path planning have been improved,which can meet the needs of practical applications.
path planningant colony algorithmtriangular pruning methodlogistics robotartificial potential field gravity
万方数据
维普
