Large industrial robots are inexpensive compared to their workspace. Due to flexibility, the positioning accuracy is compromised. This paper presents a simple yet effective static calibration method for robots using a laser tracker that can be applied to processes with no change in external load and without high processing forces. The calibration method is based on a novel elastokinematic model that captures the nonlinear gearbox and link compliance and also accounts for the effects of pose dependent joint friction and nonlinearities due to the gravity compensation mechanism. Furthermore, a feedforward concept is presented that separates kinematics from compliance to reduce computation time. The calibration method was implemented on industrial hardware and experimentally validated on a KUKA KR210–2. In comparison to state of the art compliance modeling, accuracy is improved by 23.1 %. Finally, the feedforward model reduces the mean positioning error in the entire workspace by 54.9% compared to the purely kinematically calibrated model, emphasizing the need for compliance compensation.
%0 Journal Article
%1 10962177
%A Dzubba, Marcel
%A Neubauer, Michael
%A Hinze, Christoph
%A Lechler, Armin
%A Verl, Alexander
%D 2025
%J IEEE Transactions on Automation Science and Engineering
%K robotics
%P 1-1
%R 10.1109/TASE.2025.3559673
%T A Nonlinear Elasticity Model and Feedforward Compensation Method to Increase Positioning Accuracy of Industrial Robots
%X Large industrial robots are inexpensive compared to their workspace. Due to flexibility, the positioning accuracy is compromised. This paper presents a simple yet effective static calibration method for robots using a laser tracker that can be applied to processes with no change in external load and without high processing forces. The calibration method is based on a novel elastokinematic model that captures the nonlinear gearbox and link compliance and also accounts for the effects of pose dependent joint friction and nonlinearities due to the gravity compensation mechanism. Furthermore, a feedforward concept is presented that separates kinematics from compliance to reduce computation time. The calibration method was implemented on industrial hardware and experimentally validated on a KUKA KR210–2. In comparison to state of the art compliance modeling, accuracy is improved by 23.1 %. Finally, the feedforward model reduces the mean positioning error in the entire workspace by 54.9% compared to the purely kinematically calibrated model, emphasizing the need for compliance compensation.
@article{10962177,
abstract = {Large industrial robots are inexpensive compared to their workspace. Due to flexibility, the positioning accuracy is compromised. This paper presents a simple yet effective static calibration method for robots using a laser tracker that can be applied to processes with no change in external load and without high processing forces. The calibration method is based on a novel elastokinematic model that captures the nonlinear gearbox and link compliance and also accounts for the effects of pose dependent joint friction and nonlinearities due to the gravity compensation mechanism. Furthermore, a feedforward concept is presented that separates kinematics from compliance to reduce computation time. The calibration method was implemented on industrial hardware and experimentally validated on a KUKA KR210–2. In comparison to state of the art compliance modeling, accuracy is improved by 23.1 %. Finally, the feedforward model reduces the mean positioning error in the entire workspace by 54.9% compared to the purely kinematically calibrated model, emphasizing the need for compliance compensation.},
added-at = {2025-04-22T10:45:01.000+0200},
author = {Dzubba, Marcel and Neubauer, Michael and Hinze, Christoph and Lechler, Armin and Verl, Alexander},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/298b6fdb3eb8cf6c154bc9485b8d7d1f6/isw-bibliothek},
doi = {10.1109/TASE.2025.3559673},
interhash = {b2c0cccf77f376da552ee40f08d26575},
intrahash = {98b6fdb3eb8cf6c154bc9485b8d7d1f6},
issn = {1558-3783},
journal = {IEEE Transactions on Automation Science and Engineering},
keywords = {robotics},
pages = {1-1},
timestamp = {2025-04-22T10:45:01.000+0200},
title = {A Nonlinear Elasticity Model and Feedforward Compensation Method to Increase Positioning Accuracy of Industrial Robots},
year = 2025
}
