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In this paper we propose a novel method for in-hand object recognition. The method is composed of a grasp stabilization controller and two exploratory behaviours to capture the shape and the softness of an object. Grasp stabilization plays an important role in recognizing objects. First, it prevents the object from slipping and facilitates the exploration of the object. Second, reaching a stable and...
The problem of “providing robots with the sense of touch” is fundamental in order to develop the next generations of robots capable of interacting with humans in different contexts: in daily housekeeping activities, as working partners or as caregivers, just to name a few. In a low-level perspective, through tactile sensing it is possible to measure or estimate physical properties of manipulated or...
In the context of object interaction and manipulation, one characteristic of a robust grasp is its ability to comply with external perturbations applied to the grasped object while still maintaining the grasp. In this work, we introduce an approach for grasp adaptation which learns a statistical model to adapt hand posture solely based on the perceived contact between the object and fingers. Using...
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