Humanoid robots have great potential to perform various human-level skills. These skills
involve locomotion, manipulation, and cognitive capabilities. Driven by advances in machine …

Recently, humanoid robots have made significant advances in their ability to perform
challenging tasks due to the deployment of Reinforcement Learning (RL), however, the …

Can we enable humanoid robots to generate rich, diverse, and expressive motions in the
real world? We propose to learn a whole-body control policy on a human-sized robot to …

We introduce Berkeley Humanoid, a reliable and low-cost mid-scale humanoid research
platform for learning-based control. Our lightweight, in-house-built robot is designed …

Bipedal robots are garnering increasing global attention due to their potential applications
and advancements in artificial intelligence, particularly in Deep Reinforcement Learning …

We present Human to Humanoid (H2O), a reinforcement learning (RL) based framework that
enables real-time whole-body teleoperation of a full-sized humanoid robot with only an RGB …

This paper enables real-world humanoid robots to maintain stability while performing
expressive motions like humans do. We propose ExBody2, a generalized whole-body …

Learning generic skills for humanoid robots interacting with 3D scenes by mimicking human
data is a key research challenge with significant implications for robotics and real-world …

Soccer kicking is a complex whole-body motion that requires intricate coordination of
various motor actions. To accomplish such dynamic motion in a humanoid robot, the robot …

A necessary capability for humanoid robots is the ability to stand and walk while rejecting
natural disturbances. Recent progress has been made using sim-to-real reinforcement …