DLR robot arm successfully distinguishes between water, oil, and glycerin in a bottle, based on viscosity only. UEDIN developed a framework for discrimination of dynamic object properties based purely on the learned sensorimotor contingency representation of actions and tactile sensor activations (Saal, Ting, & Vijayakumar, 2010a). This was used to not only discriminate between liquids of different viscosity (e.g., water, motor oil and glycerin of equal weight in a bottle) but also used to implement an info-max based active learning framework for optimizing the exploratory movements for discrimination (Saal, Ting, & Vijayakumar, 2010b).