Title :
Neural-Network-Based Six-axis Force/Torque Robot Sensor Calibration
Author :
Yao, Zhihui ; Wang, Fei ; Wang, Weijie ; Qin, Yu
Author_Institution :
Sch. of Mech. Eng., Harbin Inst. of Technol., Harbin, China
Abstract :
Six-axis force/torque robot sensor is an important component of intelligent robots. It is unable to interpret the relationship between input and output accurately by means of the conventional least-squares method for six-axis force/torque sensor calibration, because the sensor may suffer from non-linearity and various forms of uncertainty. In this paper, neural-networks method is used for the robot sensor calibration. This method and the least-squares method are both presented in this paper. And the results of both methods are compared and discussed. The results show that neural-networks-based calibration is more efficient and accurate.
Keywords :
control nonlinearities; force sensors; intelligent robots; least squares approximations; neurocontrollers; uncertain systems; intelligent robots; least-squares method; neural-network-based six-axis force robot sensor calibration; neural-network-based six-axis torque robot sensor calibration; Artificial neural networks; Calibration; Force; Robot sensing systems; Torque; Training; calibration; neural-networks; non-linearity; six-axis force/torque sensor;
Conference_Titel :
Electrical and Control Engineering (ICECE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-6880-5
DOI :
10.1109/iCECE.2010.332
