Grasping is the process of picking up an object by applying forces and torques at a set of
contacts. Recent advances in deep learning methods have allowed rapid progress in robotic …

Dexterous manipulation, especially dexterous grasping, is a primitive and crucial ability of
robots that allows the implementation of performing human-like behaviors. Deploying the …

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 …

Intelligent manipulation benefits from the capacity to flexibly control an end-effector with high
degrees of freedom (DoF) and dynamically react to the environment. However, due to the …

Deep learning-based robotic grasping has made significant progress thanks to algorithmic
improvements and increased data availability. However, state-of-the-art models are often …

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 …

Robots for picking in e-commerce warehouses require rapid computing of efficient and
smooth robot arm motions between varying configurations. Recent results integrate grasp …

Nonprehensile dynamic manipulation can be reasonably considered as the most complex
manipulation task. It might be argued that such a task is still rather far from being fully solved …

The effects of robotics and artificial intelligence (AI) on the job market are matters of great
social concern. Economists and technology experts are debating at what rate, and to what …

In this article, a six-step approach is proposed to simulate the grasp and evaluate the grasp
quality for a versatile vacuum gripper by tracking the deformation and force-torque wrench of …