State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China
Department of Aerospace Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada
: Received: 23 September 2016 / Approved: 23 September 2016 / Online: 23 September 2016 (09:52:45 CEST)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite:
Xia, K.; Ding, L.; Liu, G.; Gao, H.; Deng, Z. A Novel Virtual Torque Sensor for Rescue Robots with Harmonic Drives. Preprints2016, 2016090084 (doi: 10.20944/preprints201609.0084.v1).
Xia, K.; Ding, L.; Liu, G.; Gao, H.; Deng, Z. A Novel Virtual Torque Sensor for Rescue Robots with Harmonic Drives. Preprints 2016, 2016090084 (doi: 10.20944/preprints201609.0084.v1).
In this paper, a method is developed for presenting a novel virtual torque sensor based on precise model and position measurements avoids the need of traditional strain gauges and amplifiers. More specifically, the harmonic drive compliance model and the Gaussian process regression (GPR) technique are used together to achieve virtual torque sensor measurement. While the harmonic drive compliance model provides the analytic part, the Gaussian process regression method is used to reconstruct the unmolded part based on motor-side and link-side joint angles as well as motor current. After an automatic offline calibration, the method allows for a lean online implementation. The virtual torque sensor measurement is compared with measurements of a commercial torque sensor, and the results have attested the effectiveness of the proposed method.
robot joint; virtual torque sensor; Gaussian process regression; harmonic drive compliance model