4-RRR冗余驱动并联机器人的驱动力协调分配对比研究  

Comparative study on driving force coordination and distribution of 4-RRR redundant parallel manipulators

作　　者：刘浩 徐江涛 LIU Hao;XU Jiangtao(School of Electronic Information Engineering,Hengshui University,Hengshui 053000,Hebei,China;Henan Transportation Technician College,Zhumadian 463000,Henan,China)

机构地区：[1]衡水学院电子信息工程学院,河北衡水053000 [2]河南交通技师学院,河南驻马店463000

出　　处：《中国工程机械学报》2024年第5期582-587,共6页Chinese Journal of Construction Machinery

基　　金：衡水市科技计划资助项目(2019011014Z)。

摘　　要：应用于3D打印的冗余驱动可以有效降低并联机器人的瞬时最大驱动功率,提高机构的承载能力。但影响其实现的关键因素是驱动力的协调性及其控制方法,因此本文以4-RRR冗余驱动并联机器人为对象展开研究。首先,求解机构的位置逆解以及机构末端与关节速度、加速度之间的映射关系。其次,采用虚功原理构建动力学模型,分别采用4种方法优化以最大瞬时驱动力矩为优化目标对并联机器人动力学逆解进行对比研究。最后,通过仿真对最优驱动力矩优化方法的峰值力矩降低效果进行验证对比。仿真结果表明:加权最小二范数法在降低机构最大瞬时驱动力矩方面具有优越性,呈明显降低趋势且驱动力分配均衡,为提高并联机器人面向3D打印功能的运动精度及后续的应用奠定了理论基础。Redundant drive applied to 3D printing can effectively reduce the instantaneous maximum driving power of parallel robots and improve the load-bearing capacity of the mech-anism,but the key factor affecting its realization is the coordination of driving force and its control method.Therefore,this paper focuses on the 4-RRR redundant drive parallel robot.Firstly,the inverse solution of the mechanism and the mapping relationship between the end of the mechanism and the joint speed and acceleration are solved.Secondly,four optimization methods are used to optimize the inverse solution of the parallel robot dynamics with the maximum instantaneous driving torque as the optimization objective.Finally,the peak torque reduction effect of the optimal driving torque optimization method is verified and compared through simulation.The simulation results show that the weighted least-squares method has superiority in reducing the maximum instantaneous driving torque of the mechanism,showing a significant reduction trend and balanced driving force distribution,laying a theoretical foundation for improving the motion accuracy of parallel robots for 3D printing functions and subsequent applications.

关 键 词：4-RRR并联机器人 冗余驱动 驱动力 协调分配 

分 类 号：TH133.33[机械工程—机械制造及自动化]