Robot Dynamics with URDF & CasADi

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.