The visual organ is important for animals to obtain information and understand the outside
world; however, robots cannot do so without a visual system. At present, the vision …

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 …

In policy learning for robotic manipulation, sample efficiency is of paramount importance.
Thus, learning and extracting more compact representations from camera observations is a …

6D object pose tracking has been extensively studied in the robotics and computer vision
communities. The most promising solutions, leveraging on deep neural networks and/or …

Accurate shape reconstruction of transparent ob-jects is a challenging task due to their non-
Lambertian surfaces and yet necessary for robots for accurate pose perception and safe …

Applications from manipulation to autonomous vehicles rely on robust and general object
tracking to safely perform tasks in dynamic environments. We propose the first certifiably …

Fast and accurate tracking of an object's motion is one of the key functionalities of a robotic
system for achieving reliable interaction with the environment. This paper focuses on the …

In recent years, policy learning methods using either reinforcement or imitation have made
significant progress. However, both techniques still suffer from being computationally …

Pose estimation methods for robotics should return a distribution of poses rather than just a
single pose estimate. Motivated by this, in this work we investigate multi-modal pose …

In this paper, we design a novel 6-DOF object pose tracking framework for robotic
manipulation tasks. The framework takes a RGB-D video stream as input observations and …