A Robust Static Decoupling Algorithm for 3-Axis Force Sensors Based on Coupling Error Model and ε-SVR

Abstract

Coupling errors are major threats to the accuracy of 3-axis force sensors. Design of decoupling algorithms is a challenging topic due to the uncertainty of coupling errors. The conventional nonlinear decoupling algorithms by a standard Neural Network (NN) are sometimes unstable due to overfitting. In order to avoid overfitting and minimize the negative effect of random noises and gross errors in calibration data, we propose a novel nonlinear static decoupling algorithm based on the establishment of a coupling error model. Instead of regarding the whole system as a black box in conventional algorithm, the coupling error model is designed by the principle of coupling errors, in which the nonlinear relationships between forces and coupling errors in each dimension are calculated separately. Six separate Support Vector Regressions (SVRs) are employed for their ability to perform adaptive, nonlinear data fitting. The decoupling performance of the proposed algorithm is compared with the conventional method by utilizing obtained data from the static calibration experiment of a 3-axis force sensor. Experimental results show that the proposed decoupling algorithm gives more robust performance with high efficiency and decoupling accuracy, and can thus be potentially applied to the decoupling application of 3-axis force sensors.

Estimation of Forest Canopy Height and Aboveground Biomass from Spaceborne LiDAR and Landsat Imageries in Maryland

“…The Libsvm toolbox supports two kinds of formulations for regression. In this study, we trained ν-SVR [80] and ε-SVR [81], and chose linear, polynomial, and RBF (Radial Basis Function) kernels.…”

Fast Estimation of Strains for Cross-Beams Six-Axis Force/Torque Sensors by Mechanical Modeling

“…Weights and pulley blocks are utilized for force/torque loading [21]. Loading forces in X direction are generated by a unilateral pulley block and weights while indexing plate is rotated to adjust the loading direction.…”

Development of an optoelectronic 6-axis force/torque sensor for robotic applications

“…The analysis of the cross coupling error is usually performed to verify the properties of strain-gauge based F/T sensors, especially in case of mechanically decoupled sensors [2,22,23], and it can be considered as an index of the sensor quality. According to the definition given in [24], the cross coupling error is defined as the ratio of unfavorable signals to the intended one at a given output of the sensor according to pure force components.…”