Real-time sensing and modeling of the human body, especially the hands, is an important
research endeavor for various applicative purposes such as in natural human computer …

In this work, we tackle the problem of learning universal robotic dexterous grasping from a
point cloud observation under a table-top setting. The goal is to grasp and lift up objects in …

We propose a novel, object-agnostic method for learning a universal policy for dexterous
object grasping from realistic point cloud observations and proprioceptive information under …

While significant progress has been made on understanding hand-object interactions in
computer vision, it is still very challenging for robots to perform complex dexterous …

We propose a sim-to-real framework for dexterous manipulation which can generalize to
new objects of the same category in the real world. The key of our framework is to train the …

Optimizing behaviors for dexterous manipulation has been a longstanding challenge in
robotics, with a variety of methods from model-based control to model-free reinforcement …

Dexterous manipulation with a multi-finger hand is one of the most challenging problems in
robotics. While recent progress in imitation learning has largely improved the sample …

The human hand is a complex biological system able to perform numerous tasks with
impressive accuracy and dexterity. Gestures furthermore play an important role in our daily …

We propose to perform imitation learning for dexterous manipulation with multi-finger robot
hand from human demonstrations, and transfer the policy to the real robot hand. We …

Basketball is one of the world's most popular sports because of the agility and speed
demonstrated by the players. This agility and speed makes designing controllers to realize …