Disturbance Elimination for the Modular Joint Torque Sensor of a Collaborative Robot

He Zhang, Wenlei Qin, Yongsheng Gao, Qiang Li, Zhigang Chen and Jie Zhao

Mathematical Problems in Engineering, 2020, vol. 2020, 1-14

Abstract:

The ability to obtain accurate torque information and detect collision information is the key demand for collaborative robots. Given the highly integrated modular joint, the joint torque-sensing system is disturbed by other elements during online measurement, affecting the accuracy of measurement. For example, the torque ripple caused by the periodic deformation of the flexspline of the harmonic driver and the temperature drift due to the heating of motor are the two main factors affecting the measurement of the torque sensor. In this study, a torque sensor suitable for a modular joint is developed. Moreover, a strain gauge configuration based on a specified phase difference for torque ripple cancelation and a temperature compensation method based on the combination of the Wheatstone bridge and a nonlinear model are proposed. Finally, the performance of the developed sensor is experimentally evaluated.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:2405134

DOI: 10.1155/2020/2405134

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