Robot Dynamics with URDF & CasADi

Lill Maria Gjerde Johannessen, M. H. Arbo, J. Gravdahl
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引用次数: 4

Abstract

Fast, accurate evaluation of the dynamics parameters is a key ingredient for accurate control, estimation, and simulation of robots. As these are time-consuming to compute by hand, a software library for generating the rigid body dynamics symbolically can be of great use for robotics researchers. In this paper, we propose a library to efficiently compute and evaluate robot dynamics and its derivatives. Based on a URDF description of the robot’s kinematics, three major rigid body dynamics algorithms are used to retrieve the dynamics symbolically in the CasADi framework. To validate the numerical accuracy, the numerical evaluation of the solutions are compared against three other well-established rigid body dynamics libraries, namely RBDL, KDL, and PyBullet. We conduct a timing comparison between the libraries, and we show that the evaluation times of the symbolic expressions are at most one order of magnitude higher than the evaluation times of the numerical libraries. Last, it is shown that the evaluation times of the dynamics derivatives remain of the same order as the evaluation times of the dynamics expressions.
机器人动力学与URDF和CasADi
快速、准确地评估动力学参数是机器人精确控制、估计和仿真的关键因素。由于这些都是费时的手工计算,一个软件库生成刚体动力学符号可以为机器人研究人员很大的用处。在本文中,我们提出了一个库来有效地计算和评估机器人动力学及其导数。在对机器人运动学进行URDF描述的基础上,采用三种主要的刚体动力学算法在CasADi框架中进行符号化的动力学检索。为了验证数值精度,将解的数值评估与其他三个已建立的刚体动力学库(即RBDL, KDL和PyBullet)进行比较。我们对两个库进行了时间比较,结果表明符号表达式的求值时间最多比数值库的求值时间高一个数量级。最后,证明了动力学导数的求值次数与动力学表达式的求值次数保持同一阶次。
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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