摘要
工程四自由度宏微机械臂的传统逆运动求解方法需要大量公式推导,繁琐且复杂,新出现的智能优化算法在应用上存在缺陷和不足,本文在结合原有粒子群和遗传算法的基础上,提出了改进遗传粒子群逆解算法。以2F2R机械臂为例,首先利用齐次变换法构建机械臂运动学模型,然后基于Matalab Robotics Toolbox搭建仿真模型,并训练和测试模型。测试结果表明,遗传粒子群算法有效提高了机械臂的逆解速度和关节角精度。
The traditional inverse motion solution method of engineering four-degree-of-freedom macro-micromanipulator is often cumbersome and complex due to the need for a large number of formula derivations,and the newly emerged intelligent optimization algorithm has defects and shortcomings in its application.Taking the 2F2R manipulator as an example,the kinematics model of the manipulator is first constructed by the homogeneous transformation method,and then the simulation model is built based on matalab robotics toolbox,and the model is trained and tested.The test results show that the genetic particle swarm algorithm effectively improves the inverse solution speed and joint angle accuracy of the robotic arm.
作者
王鸿杰
宋建辉
代淙戈
WANG Hongjie;SONG Jianhui;DAI Zongge(College of Communication Engineering,Jilin University,Changchun,Jilin 130000,China)
出处
《自动化应用》
2023年第7期43-47,共5页
Automation Application
关键词
逆运动学
机械臂
遗传粒子群算法
inverse kinematics
robotic arm
genetic particle swarm algorithm
作者简介
王鸿杰,男,2002年生,研究方向为人工智能与机器学习、机器人与智能无人系统。
