Comprehensive modeling and identification of nonlinear joint dynamics for collaborative industrial robot manipulators

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Comprehensive modeling and identification of nonlinear joint dynamics for collaborative industrial robot manipulators. / Madsen, Emil; Rosenlund, Oluf Skov; Brandt, David; Zhang, Xuping.

I: Control Engineering Practice, Bind 101, 104462, 08.2020.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

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@article{8bce742cbc124d79b05a0ebf4f898311,
title = "Comprehensive modeling and identification of nonlinear joint dynamics for collaborative industrial robot manipulators",
abstract = "For collaborative robots, the ability to accurately predict the actuator torques required to realize the desired task is highly important. This will improve and guarantee the safety, motion and force control performance, and smooth lead-through programming experience. Thus, this paper presents the investigation towards comprehensive modeling and identification of nonlinear joint dynamics for collaborative robots. The proposed joint dynamics model and identification describes the most dominant dynamic characteristics of robot joints that comprise strain-wave transmissions, such as nonlinear friction, nonlinear stiffness, hysteresis, and kinematic error. Position-dependent backlash characteristics is observed and quantified using our proposed identification method and the Generalized Maxwell-Slip friction model is extended to describe the observed phenomena. The developed dynamic modeling and identification procedures provides insightful guidance for the design and model-based control of collaborative robots.",
keywords = "Collaborative robots, Flexible-joint robot manipulators, Friction, Strain-wave transmissions, System identification",
author = "Emil Madsen and Rosenlund, {Oluf Skov} and David Brandt and Xuping Zhang",
year = "2020",
month = aug,
doi = "10.1016/j.conengprac.2020.104462",
language = "English",
volume = "101",
journal = "Control Engineering Practice",
issn = "0967-0661",
publisher = "Pergamon Press",

}

RIS

TY - JOUR

T1 - Comprehensive modeling and identification of nonlinear joint dynamics for collaborative industrial robot manipulators

AU - Madsen, Emil

AU - Rosenlund, Oluf Skov

AU - Brandt, David

AU - Zhang, Xuping

PY - 2020/8

Y1 - 2020/8

N2 - For collaborative robots, the ability to accurately predict the actuator torques required to realize the desired task is highly important. This will improve and guarantee the safety, motion and force control performance, and smooth lead-through programming experience. Thus, this paper presents the investigation towards comprehensive modeling and identification of nonlinear joint dynamics for collaborative robots. The proposed joint dynamics model and identification describes the most dominant dynamic characteristics of robot joints that comprise strain-wave transmissions, such as nonlinear friction, nonlinear stiffness, hysteresis, and kinematic error. Position-dependent backlash characteristics is observed and quantified using our proposed identification method and the Generalized Maxwell-Slip friction model is extended to describe the observed phenomena. The developed dynamic modeling and identification procedures provides insightful guidance for the design and model-based control of collaborative robots.

AB - For collaborative robots, the ability to accurately predict the actuator torques required to realize the desired task is highly important. This will improve and guarantee the safety, motion and force control performance, and smooth lead-through programming experience. Thus, this paper presents the investigation towards comprehensive modeling and identification of nonlinear joint dynamics for collaborative robots. The proposed joint dynamics model and identification describes the most dominant dynamic characteristics of robot joints that comprise strain-wave transmissions, such as nonlinear friction, nonlinear stiffness, hysteresis, and kinematic error. Position-dependent backlash characteristics is observed and quantified using our proposed identification method and the Generalized Maxwell-Slip friction model is extended to describe the observed phenomena. The developed dynamic modeling and identification procedures provides insightful guidance for the design and model-based control of collaborative robots.

KW - Collaborative robots

KW - Flexible-joint robot manipulators

KW - Friction

KW - Strain-wave transmissions

KW - System identification

UR - http://www.scopus.com/inward/record.url?scp=85085276269&partnerID=8YFLogxK

U2 - 10.1016/j.conengprac.2020.104462

DO - 10.1016/j.conengprac.2020.104462

M3 - Journal article

AN - SCOPUS:85085276269

VL - 101

JO - Control Engineering Practice

JF - Control Engineering Practice

SN - 0967-0661

M1 - 104462

ER -