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Transmission Error Compensation for Industrial Robots Using Fourier Series

arXiv2 min read

arXiv:2610.23882v1 Announce Type: cross Abstract: Due to their low accuracy, industrial robots commonly require online teaching after the offline development of a robot program in simulation. The accuracy is limited by compliance and transmission errors in the robot joints. Transmission errors are defined as errors between the load-side angles of the gearboxes and the motor encoder angles. An approach to identify the transmission errors based on laser tracker measurements is presented. The developed velocity-dependent Fourier series model is integrated in a virtual commissioning software as a co-simulated functional mock-up unit. Additionally, it is used to compensate the transmission errors by correcting the setpoint from the computerized numerical control (CNC). The model identification and the compensation are experimentally evaluated with a St\"aubli TX2-40 industrial robot. The model has a mean absolute error of 0.114 mrad, and the compensation improves the accuracy by 83.26 % for axis 2 and 49.21 % for axis 3.

Abstract:Due to their low accuracy, industrial robots commonly require online teaching after the offline development of a robot program in simulation. The accuracy is limited by compliance and transmission errors in the robot joints. Transmission errors are defined as errors between the load-side angles of the gearboxes and the motor encoder angles. An approach to identify the transmission errors based on laser tracker measurements is presented. The developed velocity-dependent Fourier series model is integrated in a virtual commissioning software as a co-simulated functional mock-up unit. Additionally, it is used to compensate the transmission errors by correcting the setpoint from the computerized numerical control (CNC). The model identification and the compensation are experimentally evaluated with a Stäubli TX2-40 industrial robot. The model has a mean absolute error of 0.114 mrad, and the compensation improves the accuracy by 83.26 % for axis 2 and 49.21 % for axis 3.

10 pages, 6 figures, 1 table. Accepted for publication in Annals of Scientific Society for Assembly, Handling and Industrial Robots, 2026. Dataset available on this https URL

Systems and Control (eess.SY); Robotics (cs.RO); Signal Processing (eess.SP)

I.6.4; I.6.5; I.6.6; I.6.8; J.2; J.7

arXiv:2610.23882 [eess.SY]

(or arXiv:2610.23882v1 [eess.SY] for this version)

Full text under the publisher's open licence · 197 words

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