The Advancements in tactile sensors and machine learning techniques open new
opportunities for achieving intelligent grasping in robotics. Traditional robot is limited in its …

Deformable objects manipulation can benefit from representations that seamlessly integrate
vision and touch while handling occlusions. In this work, we present a novel approach for …

In this paper, we address the problem of estimating the in-hand 6D pose of an object in
contact with multiple vision-based tactile sensors. We reason on the possible spatial …

Robotic manipulation tasks such as object insertion typically involve interactions between
object and environment, namely extrinsic contacts. Prior work on Neural Contact Fields …

In this paper, we propose a method for estimating in-hand object poses using proprioception
and tactile feedback from a bimanual robotic system. Our method addresses the problem of …

For many robotic manipulation and contact tasks, it is crucial to accurately estimate uncertain
object poses, for which certain geometry and sensor information are fused in some optimal …

In automated robot assembly and industrial palletization tasks it is crucial to ensure a good
accuracy while placing objects given a planned target pose. To achieve this goal post-grasp …

Dexterous robotic manipulation tasks depend on estimating the state of in-hand objects,
particularly their orientation. Although cameras have been traditionally used to estimate the …

Electrical connectors (ECs) are extensively employed in industrial scenarios, and their
assembly quality is crucial. However, these connectors are often located in confined spaces …

From serving a cup of coffee to carefully rearranging delicate items, stable object placement
is a crucial skill for future robots. This skill is challenging due to the required accuracy, which …