TactileMemory: Multi-Fingered Simultaneous Shape and Pose Identification Using Contact Traces

We propose a model of Tactile Memory that integrates sequential touches to identify the shape and pose of an object. The memory also controls the next tactile action to approximately optimize its information gain at each step. The information fusion and determination of the next tactile action is achieved with the aid of an ensemble of hypotheses, each of which represents a possible shape and pose of the object. We assume a first touch event has already occurred, and focus on the process of shape and pose identification. In order to minimize the number of tactile actions required, the proposed method combines: 1) Tactile Memory: a record of the tactile event history from multiple fingers of a Shadow Hand along with the contact traces and hand location 2) the hypothesis ensemble as a distributed representation of the remaining shape and pose uncertainty and 3) Explorative Tactile Actions: a set of tactile event-specific heuristics that create proposals for hand location based on the tactile feedback. We analyze our approach in simulation and quantify its improvement of exploration over a baseline algorithm that does not use the contact traces. Also we compare Explorative Tactile Actions with a baseline that uses random hand locations. We also demonstrate our algorithm on a robot with Shadow Hand to show that we can estimate the shape and pose of an object in about ten tactile actions.