Abstract: An improved potential field ant colony algorithm is proposed for the path planning of material transfer sorting platforms to address problems of low convergence and local optimality of traditional ant colony algorithms and the unreachability of artificial potential field method. For global path planning, the distance between the next node position and the target point position at the time of material transmission and the dynamic weight factor are added to optimise the heuristic function, and a factor adaptive update strategy is used by considering the different importance of the pheromone heuristic factor, the distance expectation function factor, and the pheromone volatility factor at different moments. In the local path planning, the traditional artificial potential field method is improved by introducing the distance adjustment factor between  material and the target point and the fuzzy repulsion point. Finally, an IACSPF is designed by taking the inflection points in the global path as sub-target points in the local path, and a simulation is also carried out to analyse the path planning of the material transfer. Simulation?results show that the IACSPF can shorten the path length of the transmission by 13.1%, reduce the number of inflection points by 71.4%, and effectively avoid obstacles, thus verifying the rationality of the algorithm.

Key words: material transmission platform, path planning, improved ant colony system algorithm with potential field （IACSPF）, MATLAB

摘要： 针对传统蚁群算法收敛速度慢、易陷入局部最优与人工势场法目标不可达等问题，在物料传输分拣平台的路径规划中提出了一种改进势场蚁群算法。全局路径规划时，通过增设物料传输时下一节点位置与目标点位置间的距离与动态权重系数以优化启发函数，并考虑信息素启发因子、距离期望函数因子及信息素挥发因子在不同时刻的重要程度不同，采用了因子自适应更新策略。在局部路径规划中，通过引入物料与目标点的距离调节因子和模糊斥力点，改进了传统人工势场法。最后，将全局路径中的拐点作为局部路径中的子目标点，设计了改进势场蚁群融合算法，并对物料传输路径规划进行了仿真分析。仿真结果表明，改进势场蚁群算法可使传输路径长度缩短13.1%，拐点数目减少71.4%，并能有效避开障碍物，从而验证了算法的合理性。

关键词: 物料传输平台, 路径规划, 改进势场蚁群算法（IACSPF）, MATLAB