Tower crane path planning based on improved ant colony algorithm  

基于改进蚁群算法的塔机路径规划

作　　者：HE Yumin HU Xiangyang ZHANG Jinhua YAO Shipeng LIU Difang MEN Xinyan 何育民;胡象洋;张锦华;姚世鹏;刘帝芳;门新延(西安建筑科技大学机电工程学院,陕西西安710055;陕西建设机械股份有限公司,陕西西安710201)

机构地区：[1]College of Electrical&Mechanical Engineering,Xi’an University of Architecture&Technology,Xi’an 710055,China [2]Shaanxi Construction Machinery Co.,Ltd.,Xi’an 710201,China

出　　处：《Journal of Measurement Science and Instrumentation》2024年第4期509-517,共9页测试科学与仪器（英文版）

基　　金：supported by Shaanxi Provincial Key Research and Development Program of China(Nos.2024GX-YBXM-305,2024GX-YBXM-178);Shaanxi Province Qinchuangyuan“Scientists+Engineers”Team Construction(No.2022KXJ032)。

摘　　要：In order to solve the problem of path planning of tower cranes,an improved ant colony algorithm was proposed.Firstly,the tower crane was simplified into a three-degree-of-freedom mechanical arm,and the D-H motion model was established to solve the forward and inverse kinematic equations.Secondly,the traditional ant colony algorithm was improved.The heuristic function was improved by introducing the distance between the optional nodes and the target point into the function.Then the transition probability was improved by introducing the security factor of surrounding points into the transition probability.In addition,the local path chunking strategy was used to optimize the local multi-inflection path and reduce the local redundant inflection points.Finally,according to the position of the hook,the kinematic inversion of the tower crane was carried out,and the variables of each joint were obtained.More specifically,compared with the traditional ant colony algorithm,the simulation results showed that improved ant colony algorithm converged faster,shortened the optimal path length,and optimized the path quality in the simple and complex environment.针对塔式起重机的路径规划问题,提出了一种改进蚁群算法。首先,将塔式起重机简化成一个三自由度的机械臂,建立D-H运动模型求解正、逆运动学方程。其次,对传统蚁群算法进行了改进。将可选节点与目标点的距离引入启发函数,对启发函数进行改进;在状态转移概率中引入周围点安全因素,对转移概率进行了改进;采用局部路径分块策略,对局部多拐点路径进行了优化,减少了局部冗余拐点。最后,根据吊钩的位姿对塔机进行运动学求逆,得到各关节的变量。通过在简单环境和复杂环境下塔机路径规划的仿真研究,发现提出的改进蚁群算法可加快收敛速度,缩短最优路径长度,改善路径质量。

关 键 词：tower crane ant colony algorithm transition probability local path chunking strategy path planning 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TU61[自动化与计算机技术—控制科学与工程]