ヒューマノイドロボット向けひずみゲージ式力覚センサの非線形オンサイトキャリブレーション
Nonlinear In-situ Calibration of Strain-Gauge Force/Torque Sensors for Humanoid Robots
ヒューマノイドロボットの力覚センサの校正に非線形多項式モデルを導入し、従来の線形モデルより力推定誤差を大幅に低減できることをiCub3での実験で示した。
著者: Hosameldin Awadalla Omer Mohamed, Gabriele Nava, Punith Reddy Vanteddu, Francesco Braghin, Daniele Pucci
分類: cs.RO
原文アブストラクト
High force/torque (F/T) sensor calibration accuracy is crucial to achieving successful force estimation/control tasks with humanoid robots. State-of-the-art affine calibration models do not always approximate correctly the physical phenomenon of the sensor/transducer, resulting in inaccurate F/T measurements for specific applications such as thrust estimation of a jet-powered humanoid robot. This paper proposes and validates nonlinear polynomial models for F/T calibration, increasing the number of model coefficients to minimize the estimation residuals. The analysis of several models, based on the data collected from experiments with the iCub3 robot, shows a significant improvement in minimizing the force/torque estimation error when using higher-degree polynomials. In particular, when using a 4th-degree polynomial model, the Root Mean Square error (RMSE) decreased to 2.28N from the 4.58N obtained with an affine model, and the absolute error in the forces remained under 6N while it was reaching up to 16N with the affine model.
