A developed a Qt-GUI and a set Machine Learning classifiers for the Syntouch BioTac sensor, a synthetic finger which provide pressure and temperature information at 19 different locations across the finger’s skin. Figure Data collection illustrates the data gathering step for four different classes (Corner, Edge, Surface, Air ). Once a sufficient amount of data was gathered for each class I proceeded to learn different classifiers. I found that Support Vector Machine (SVM) was the most robust classifier when compared with other classification approaches such as Gaussian Mixture Model.
Figure Syntouch BioTac classifier illustratese the SVM classifier in action.