Humanoid Robot Achieves Unprecedented Robustness and Expressiveness with New Skill Space

A groundbreaking development in humanoid robotics has been unveiled, showcasing a robot capable of navigating complex tasks and challenging terrains with remarkable stability. The achievement, highlighted in a recent social media post by researcher Yitang Li, points to a "robust and expressive" humanoid that can handle "Push, pull, payload, uneven terrain… no worries falling down!!!!!!" The innovation centers around a "SAFE humanoid," suggesting significant advancements in reliable and adaptable robotic control.

The breakthrough is attributed to a novel framework called "Real-world-Ready Skill Space (R2S2)," developed by a team including Zhikai Zhang and Yitang Li, affiliated with institutions such as Tsinghua University, Peking University, and Galbot. This framework aims to unlock the full reaching potential of humanoids by creating a structured skill prior that ensures efficient and reliable transfer from simulation to real-world applications. The team demonstrated the R2S2 framework on Unitree G1 and the full-sized Unitree H1 humanoids, achieving stable performance in tasks like point touching and box pickup.

The R2S2 approach constructs a library of "real-world-ready primitive skills," including locomotion, body-pose-adjustment, and hand-reaching. These individual skills are meticulously tuned and evaluated for robust sim2real transfer. Subsequently, these skills are ensembled into a unified latent space using a combination of imitation learning and reinforcement learning, allowing the robot to learn coordination and seamless transitions between different motor abilities. This integrated skill space significantly improves the robot's ability to perform complex, multi-faceted tasks.

The researchers emphasize that traditional model-based control methods often struggle with real-world imperfections, while end-to-end reinforcement learning faces challenges with optimization difficulty and sim2real transferability for complex whole-body control. The R2S2 framework addresses these issues by providing a structured prior that enhances stability and adaptability, enabling humanoids to operate effectively in dynamic and unpredictable environments. The successful real-world demonstrations suggest a major step forward in developing human-level goal-reaching capabilities for humanoid robots.