刚度
工作区
机器人
维数之咒
歧管(流体力学)
机械加工
工业机器人
计算机科学
控制理论(社会学)
非线性降维
偏转(物理)
控制工程
人工智能
工程类
机械工程
降维
结构工程
控制(管理)
物理
光学
作者
Guanhua Li,Weidong Zhu,Huiyue Dong,An Li
标识
DOI:10.1016/j.rcim.2020.102076
摘要
Abstract In this paper, the modeling of the stiffness of a 6-DOF industrial robot is introduced, and two different stiffness-oriented performance indices are compared to improve the two-dimensional manifold. In previous study, the two-dimensional manifold is applied to simplify the workspace for error compensation to avoid the curse of dimensionality. Stiffness is one of the most concerned factors in robotic machining to reduce the deflection at the end of robot arm, which makes a stiffness-oriented manifold is quite essential in the actual application. An improved two-dimensional index is presented based on the Frobenius-condition-number of translational compliance matrix to avoid the ill-conditions of manipulator. The superiority of the improved index over the previous one is theoretically proved with several propositions in matrix theory. The simulations performed with sample points on a panel surface imply that the ill-conditions of robot can be effectively avoided. The results of contrast experiments conducted on KUKA robot show that the improved still ensure the accuracy of positioning in robotic machining.
科研通智能强力驱动
Strongly Powered by AbleSci AI