SPIDAR calibration based on regression methods

In order to obtain accurate position estimation, it is imperative that the SPIDAR, a haptic interface device, is properly calibrated. The driving idea of this work is to derive easy-to-use calibration algorithms that can be used to calibrate our haptic device and to add therefore adaptability to the system behavior. We make use of regression methods and we obtain calibration algorithms as a solution to SPIDAR inaccuracy. The efficacy of the proposed methods is illustrated using experimental data collected from a sensor platform.