Tactile object class and internal state recognition for mobile manipulation

Tactile information is valuable in determining properties of objects that are inaccessible from visual perception. In this work, we present a tactile perception strategy that allows any mobile robot with tactile sensors in its gripper to measure a set of generic tactile features while grasping an object. We propose a hybrid velocity-force controller, that grasps an object safely and reveals at the same time its deformation properties. As an application, we show that a robot can use these features to distinguish the open/closed and fill state of bottles and cans - purely from tactile sensing - from a small training set. To prove that this is a hard recognition problem, we also conducted a comperative study with 17 human test subjects. We found that the recognition rate of the human subjects were comparable to our robotic gripper.