5 accepted papers
Perceiving the physical properties of different surfaces/textures via tactile sensing has been a long-standing problem in robotics. Most prior work has been limited to discriminative models that classify textures into a fixed set of categories. However, to enable seamless autonomous manipulation, ro…
Perceiving the physical properties of different surfaces/textures via tactile sensing has been a long-standing problem in robotics. Most prior work has been limited to discriminative models that classify textures into a fixed set of categories. However, to enable seamless and efficient autonomous ma
An essential problem in robotic systems that are to be deployed in unstructured environments is the accurate and autonomous perception of the shapes of previously unseen objects. Existing methods for shape estimation or reconstruction have leveraged either visual or tactile interactive exploration t
For robotic systems to interact with objects in dynamic environments, it is essential to perceive the physical properties of the objects such as shape, friction coefficient, mass, center of mass, and inertia. This not only eases selecting manipulation action but also ensures the task is performed as…
This work presents a novel active visuo-tactile based framework for robotic systems to accurately estimate pose of objects in dense cluttered environments. The scene representation is derived using a novel declutter graph (DG) which describes the relationship among objects in the scene for declutter