基于改进蚁群算法的桥式起重机路径规划问题研究  

Study on Path Planning of Overhead Traveling Crane Based on Improved Ant Colony Algorithm

作　　者：周浩 曹旭阳[1] 王殿龙[1] 陈敬涛 ZHOU Hao;CAO Xu-yang;WANG Dian-long;CHEN Jing-tao(School of Mechanical Engineering,Dalian University of Technology,Liaoning Dalian116024,China)

机构地区：[1]大连理工大学机械工程学院,辽宁大连116024

出　　处：《机械设计与制造》2021年第4期133-136,共4页Machinery Design & Manufacture

基　　金：国家科技支撑计划课题—桥式起重机械轻量化共性技术研究(2015BAF06B01)。

摘　　要：通过研究桥式起重机路径规划问题,提出一种改进的蚁群路径规划算法。针对传统蚁群算法收敛速度慢,容易陷入局部最优的缺点,借鉴A*算法和狼群分配原则改进自适应启发函数、信息素更新机制。根据桥式起重机的运行特征,通过运动学动力学分析抽象出两个仿真因子:路径长度和节点数量,提出以路径长度、运行时间和稳定性等性能参数为代价的新的评价标准。栅格环境下的桥式起重机路径规划仿真结果表明,改进的蚁群算法提高算法的收敛速度,避免搜索陷入局部最优,可以得到较优的工程应用路径。An improved ant colony algorithm for the path planning of overhead traveling crane is proposed.Aiming at the shortcoming of ant colony algorithm in slow convergence,easily falls into the local optimum,improved the adaptive heuristic functions and the pheromone-updating mechanism borrowed A*algorithm and the assignment rule of wolf colony.According to the operating characteristics of the overhead traveling crane,two simulation factors,path length and number of nodes,are abstracted by kinematics and dynamics analysis.The evaluation criteria based on the performance parameters such as path length,running time and stability is proposed.The simulation test for overhead traveling crane path planning in grid environment shows that improved algorithm increases the convergence speed,avoids the local optimum and can obtain better engineering application path.

关 键 词：桥式起重机 路径规划 改进蚁群算法 评价标准 

分 类 号：TH16[机械工程—机械制造及自动化] TH215