標題: Using maximum likelihood to calibrate a six-DOF force/torque sensor
作者: Tran, Trong-Hieu
Wang, Yu-Jen
Cheng, Chun-Kai
Chao, Paul C. -P.
Wang, Chun-Chieh
電子工程學系及電子研究所
Department of Electronics Engineering and Institute of Electronics
公開日期: 1-Nov-2018
摘要: This study presents a new six-DOF force/torque sensor and its calibration method. This calibration method apply the method of so-called maximum likelihood estimation (MLE). MLE is utilized to determine and identify the parameters related to applied torques/forces towards resulted deformations at varied locations of the sensor structure. Formulating such relations in a vector-matrix form, those parameters are captured as coefficients in a matrix related to torques/forces towards angular/linear deformations in different directions. In addition to applying MLE, finite element modeling and analysis are conducted to generate realistic-like empirical data for the afore-mentioned calibration computation. The matrix formed by these coefficients can predict exactly forces and torques by this sensor based on deformations detected by strain gauges. In simulated results the worst sum of error for three forces is less than 0.04% while the worst sum of error for three torques is less than 0.005%. Experiments are also conducted, and the results show that the designed sensor and maximum-likelihood parameter estimation approach achieve favorable performance of predicting forces and torques with error less than 1%. The developed sensor is suitable for real-time sensing of multi-dimensional interactive forces/torques in a robot arm.
URI: http://dx.doi.org/10.1007/s00542-018-4009-9
http://hdl.handle.net/11536/148300
ISSN: 0946-7076
DOI: 10.1007/s00542-018-4009-9
期刊: MICROSYSTEM TECHNOLOGIES-MICRO-AND NANOSYSTEMS-INFORMATION STORAGE AND PROCESSING SYSTEMS
Volume: 24
起始頁: 4493
結束頁: 4509
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