Article
Effects of Temperature and Mounting Configuration on the
Dynamic Parameters Identification of Industrial Robots
Andrea Raviola * , Roberto Guida , Andrea De Martin, Stefano Pastorelli , Stefano Mauro
and Massimo Sorli
Citation: Raviola, A.; Guida, R.; De
Martin, A.; Pastorelli, S.; Mauro, S.;
Sorli, M. Effects of Temperature and
Mounting Configuration on the
Dynamic Parameters Identification of
Industrial Robots. Robotics 2021, 10,
83. https://doi.org/10.3390/
robotics10030083
Academic Editor: Saïd Zeghloul
Received: 21 May 2021
Accepted: 25 June 2021
Published: 29 June 2021
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4.0/).
Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Corso Duca degli Abruzzi 24,
10129 Torino, Italy; roberto.guida@studenti.polito.it (R.G.); andrea.demartin@polito.it (A.D.M.);
stefano.pastorelli@polito.it (S.P.); stefano.mauro@polito.it (S.M.); massimo.sorli@polito.it (M.S.)
* Correspondence: andrea.raviola@polito.it
Abstract:
Dynamic parameters are crucial for the definition of high-fidelity models of industrial
manipulators. However, since they are often partially unknown, a mathematical model able to
identify them is discussed and validated with the UR3 and the UR5 collaborative robots from
Universal Robots. According to the acquired experimental data, this procedure allows for reducing
the error on the estimated joint torques of about 90% with respect to the one obtained using only
the information provided by the manufacturer. The present research also highlights how changes in
the robot operating conditions affect its dynamic behavior. In particular, the identification process
has been applied to a data set obtained commanding the same trajectory multiple times to both
robots under rising joints temperatures. Average reductions of the viscous friction coefficients of
about 20% and 17% for the UR3 and the UR5 robots, respectively, have been observed. Moreover,
it is shown how the manipulator mounting configuration affects the number of the base dynamic
parameters necessary to properly estimate the robots’ joints torques. The ability of the proposed
model to take into account different mounting configurations is then verified by performing the
identification procedure on a data set generated through a digital twin of a UR5 robot mounted on
the ceiling.
Keywords: collaborative robotics; industrial robots; dynamic identification
1. Introduction
Detailed knowledge of robot dynamic parameters can be beneficial for several appli-
cations. However, in contrast with the kinematic ones, these values are usually not fully
provided by the manufacturer. As an example, Universal Robots, one of the main brands
in collaborative robotics, details only the expected values of the mass and the position
of the center of mass of each joint/link of its manipulators [
1
], for a total of 24 (4
×
6)
parameters. On the other hand, the remaining 54 (9
×
6), which include links and motors
inertia and Coulomb and viscous friction, remain unknown, thus preventing the definition
of accurate dynamic models. According to [
2
,
3
], this is of primary importance for control
algorithms currently adopted for industrial manipulators which often rely on control strate-
gies far more complex than simple Proportional-Integral-Differential (PID) ones [
4
]. On the
other hand, a different approach could be derived from [
5
], where deterministic artificial
intelligence has been effectively used to learn the dynamic properties of an unmanned
underwater vehicle for autonomous trajectory generation and control.
Moreover, an imprecise estimate of the torques required to execute the desired trajec-
tory could negatively influence the effectiveness of algorithms used to provide performance
indexes to evaluate the energy consumption of a manipulator [
6
], or to define optimal
trajectories to minimize the power required by the robot without compromising its pro-
ductivity [
7
,
8
]. Since these methods use the Lagrange formulation [
9
], more accurate
Robotics 2021, 10, 83. https://doi.org/10.3390/robotics10030083 https://www.mdpi.com/journal/robotics
