Haptic human–machine interfaces (HHMIs) combine tactile sensation and haptic feedback
to allow humans to interact closely with machines and robots, providing immersive …

Reinforcement learning (RL), particularly its combination with deep neural networks,
referred to as deep RL (DRL), has shown tremendous promise across a wide range of …

As the basis for prehensile manipulation, it is vital to enable robots to grasp as robustly as
humans. Our innate gras** system is prompt, accurate, flexible, and continuous across …

Gras** 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 …

Robotic equipment has been playing a central role since the proposal of smart
manufacturing. Since the beginning of the first integration of industrial robots into production …

Gras** unseen objects in unconstrained, cluttered environments is an essential skill for
autonomous robotic manipulation. Despite recent progress in full 6-DoF grasp learning …

Industrial robots and associated control methods are continuously develo**. With the
recent progress in the field of artificial intelligence, new perspectives in industrial robot …

Develo** e-skins that can perceive stimuli with high sensitivity and material recognition
functionality at low cost is of great importance to intelligent perception. Here, a hybrid e-skin …

Multiple degrees of freedom (DOFs) motion manipulation of various objects is a crucial skill
for robotic systems, which relies on various robotic hands. However, traditional robotic …

Gras** objects by a specific subpart is often crucial for safety and for executing
downstream tasks. We propose LERF-TOGO, Language Embedded Radiance Fields for …