Humans excel at dexterous manipulation; however, achieving human-level dexterity
remains a significant challenge for robots. Technological breakthroughs in the design of …

Recent progress in imitation learning from human demonstrations has shown promising
results in teaching robots manipulation skills. To further scale up training datasets, recent …

Humanoid robots capable of autonomous operation in diverse environments have long
been a goal for roboticists. However, autonomous manipulation by humanoid robots has …

Imitation learning from human demonstrations is an effective means to teach robots
manipulation skills. But data acquisition is a major bottleneck in applying this paradigm more …

In most contact-rich manipulation tasks, humans apply time-varying forces to the target
object, compensating for inaccuracies in the vision-guided hand trajectory. However, current …

Teaching robots to autonomously complete everyday tasks remains a challenge. Imitation
Learning (IL) is a powerful approach that imbues robots with skills via demonstrations, but is …

The rapid and widespread diffusion of generative artificial intelligence (AI) has unlocked
new capabilities and changed how content and services are created, shared, and …

Training robots directly from human videos is an emerging area in robotics and computer
vision. While there has been notable progress with two-fingered grippers, learning …

We introduce a teleoperation system that integrates a 5 DOF actuated neck, designed to
replicate natural human head movements and perception. By enabling behaviors like …

Dual-arm manipulation is an area of growing interest in the robotics community. Enabling
robots to perform tasks that require the coordinated use of two arms, is essential for complex …