机器人设计自动计算 (ACRoD):APython 软件包,用于围绕指定的末端执行器点,对机器人在给定配置下的雅各布系数进行数值计算

A. Jacob, Rituparna Datta
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引用次数: 0

摘要

机器人的雅各比是指将末端执行器的速度分量与执行关节的速度进行线性映射的矩阵。雅各布矩阵被广泛应用于基于雅各布矩阵的机器人机械手最佳性能的尺寸合成中,其中计算了机器人的最佳尺寸参数。在切比切夫-格吕布勒-库茨巴赫准则无法准确确定移动性的情况下,也可以使用雅各布函数来确定平面和空间机构的准确移动性(Yang 等人,2008 年)(Gogu,2005 年)。因此,雅各布函数对于机构的运动学分析、尺寸合成和流动性确定都具有重要意义。因此,雅各布公式在文献中以及在性能优化和机动性计算的应用中都具有重要意义。串联机械手的雅各布公式可以轻松计算,但由于存在被动关节速度以及这些速度与主动关节速度之间的关系,并联机械手的雅各布公式计算变得越来越复杂。一些研究(Altuzarra 等人,2006 年;Dutre 等人,1997 年;D. Kim 等人,2000 年;S.-G.Kim &
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Computation for Robot Design (ACRoD): A Python package for numerical calculation of Jacobian of a robot at a given configuration around a specified end-effector point
The Jacobian of a robot refers to the matrix that linearly maps the velocity components of the end-effector and the velocities at the actuated joints. The Jacobian is extensively used in dimensional synthesis for Jacobian-based optimal performances of robotic manipulators, in which the optimal dimensional parameters of robots are computed. Determination of accurate mobility (Yang et al., 2008) of planar and spatial mechanisms can also be performed by using Jacobian in cases where Chebychev–Grübler–Kutzbach criterion cannot accurately determine the mobility (Gogu, 2005). As a result, Jacobian is a significant part for both kinematic analysis, dimensional synthesis and mobility determination of a mechanism. Hence, the formulation of Jacobian has its key importance in the literature and in the application of performance optimisation along with mobility computation. Formulation of Jacobian for serial manipulators can be computed easily, however, it is increasingly complicated to formulate Jacobian for parallel manipulators due to the existence of passive joint velocities and the nature in which these are related to active joint velocities. Several studies (Altuzarra et al., 2006; Dutre et al., 1997; D. Kim et al., 2000; S.-G. Kim &
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