Generating dexterous grasping has been a long-standing and challenging robotic task.
Despite recent progress, existing methods primarily suffer from two issues. First, most prior …

Robotic dexterous grasping is the first step to enable human-like dexterous object
manipulation and thus a crucial robotic technology. However, dexterous grasping is much …

We present ArtiGrasp, a novel method to synthesize bimanual hand-object interactions that
include grasping and articulation. This task is challenging due to the diversity of the global …

To enable general-purpose robots, we will require the robot to operate daily articulated
objects as humans do. Current robot manipulation has heavily relied on using a parallel …

Many real-world manipulation tasks consist of a series of subtasks that are significantly
different from one another. Such long-horizon, complex tasks highlight the potential of …

Recent rapid developments of dexterous robotic hands have greatly enhanced the
manipulative capabilities of robots, enabling them to perform industrial tasks in human-like …

Estimating and synthesizing the hand's manipulation of objects is central to understanding
human behaviour. To accurately model the interaction between the hand and object …

Hand manipulating objects is an important interaction motion in our daily activities. We
faithfully reconstruct this motion with a single RGBD camera by a novel deep reinforcement …

In this work, we aim to learn a unified vision-based policy for multi-fingered robot hands to
manipulate a variety of objects in diverse poses. Though prior work has shown benefits of …

Daily objects embedded in a contextual environment are often ungraspable initially.
Whether it is a book sandwiched by other books on a fully packed bookshelf or a piece of …