Abstract
This study developed a six-axis force/torque sensor and calibration system. To improve the stability of the calibration system, voice coil motors (VCMs) were used as the system’s output force device. A simply and directly designed structure lent reliability to the six-axis calibration force/torque sensor. Furthermore, the system combined two precise one-axis load cells to receive the output reactionary force from the VCMs, and then used a proportional-integral-derivative controller to reduce the steady-state time. Finally, a mechanism was designed to adjust the orientation of the calibration force. The six-axis force/torque sensor is based on the principle of mechanical deformation of the structure. Resistance strain gauges were used as measuring devices because of their wide measurement range and high level of accuracy. According to the results of a strain analysis using ANSYS, we designed a crab-type force sensor as the main structure of our sensor. Through measuring the strain gauges on the elastic body surfaces, we obtained the corresponding voltages of each applied calibration force. In this study, we conducted least squares estimation (LSE) and maximum likelihood estimation (MLE) to determine the transfer function between the calibration force/torque and the voltages of the sensor. Overall, we integrated the entire system with LabVIEW and simplified its usage to minimize operation errors. Furthermore, the six-axis calibration process was conducted to verify the proposed method.
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The authors appreciate the support from Ministry of Science and Technology, R.O.C under the grant No. NSC 107-2221-E-110-071 and 107-2622-E-110-CC3. Also appreciate the support from NSYSU-KMU JOINT RESEARCH PROJECT under the grant No. NSYSUNKUST 108-I008, National Applied Research Laboratories under the grant NARL-IMS-107-005 and from Industrial Technology Research Institute.
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Wang, YJ., Hsu, CW., Huang, PH., Wu, LC., Sue, CY., Lin, CC. (2020). Based on a Calibration Machine and Process to Develop a Six-Axis Force/Torque Sensor. In: Kuo, CH., Lin, PC., Essomba, T., Chen, GC. (eds) Robotics and Mechatronics. ISRM 2019. Mechanisms and Machine Science, vol 78. Springer, Cham. https://doi.org/10.1007/978-3-030-30036-4_22
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DOI: https://doi.org/10.1007/978-3-030-30036-4_22
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