Inverse dynamics analysis of a 6-RR-RP-RR parallel manipulator with offset universal joints

IF 1.9 4区 计算机科学 Q3 ROBOTICS
Robotica Pub Date : 2024-03-26 DOI:10.1017/s0263574724000365
Huze Huang, Hasiaoqier Han, Dawei Li, Zhenbang Xu, Qingwen Wu
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引用次数: 0

Abstract

This paper presents an algorithm for solving the inverse dynamics of a parallel manipulator (PM) with offset universal joints (RR–joints) via the Newton–Euler method. The PM with RR–joints increase the joint stiffness and enlarge the workspace but introduces additional joint parameters and constraint torques, rendering the dynamics more complex. Unlike existing studies on PMs with RR–joints, which emphasize the kinematics and joint performance, this paper studies the dynamical model. First, an iterative algorithm is established through a rigid body velocity transformation, which calculates the input parameters of the link velocity and acceleration. A linear system of equations in matrix form is then established for the entire PM through the Newton–Euler method. By using the generalized minimal residual method (GMRES) to solve the equation system, all the forces and torques on the joints can be obtained, from which the required actuation force can be derived. This method is validated through numerical simulations using the automatic dynamic analysis of multibody systems software. The proposed method is suitable for establishing the dynamic model of complex PMs with redundant or hybrid structures.

带偏移万向节的 6-RR-RP-RR 并联机械手的逆动力学分析
本文介绍了一种通过牛顿-欧拉法求解带有偏置万向关节(RR-关节)的并联机械手(PM)逆动力学的算法。带有 RR 关节的并联机械手增加了关节刚度,扩大了工作空间,但也引入了额外的关节参数和约束扭矩,使动力学变得更加复杂。与强调运动学和关节性能的现有带 RR 关节的 PM 研究不同,本文研究的是动力学模型。首先,通过刚体速度变换建立迭代算法,计算链路速度和加速度的输入参数。然后,通过牛顿-欧拉法为整个 PM 建立矩阵形式的线性方程组。通过使用广义最小残差法(GMRES)求解方程组,可以得到关节上的所有力和扭矩,并由此得出所需的驱动力。通过使用多体系统自动动态分析软件进行数值模拟,对该方法进行了验证。所提出的方法适用于建立具有冗余或混合结构的复杂 PM 的动态模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Robotica
Robotica 工程技术-机器人学
CiteScore
4.50
自引率
22.20%
发文量
181
审稿时长
9.9 months
期刊介绍: Robotica is a forum for the multidisciplinary subject of robotics and encourages developments, applications and research in this important field of automation and robotics with regard to industry, health, education and economic and social aspects of relevance. Coverage includes activities in hostile environments, applications in the service and manufacturing industries, biological robotics, dynamics and kinematics involved in robot design and uses, on-line robots, robot task planning, rehabilitation robotics, sensory perception, software in the widest sense, particularly in respect of programming languages and links with CAD/CAM systems, telerobotics and various other areas. In addition, interest is focused on various Artificial Intelligence topics of theoretical and practical interest.
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