Unleashing Humanoid Reaching Potential via Real-world-Ready Skill Space

Zhikai Zhang, Chao Chen, Han Xue, Jilong Wang, Sikai Liang, Yun Liu, Zongzhang Zhang, He Wang, Li Yi

Keywords: Humanoid, Whole Body Control, Action Representation

Abstract:

Humans possess a large reachable space in the 3D world, enabling interactions with objects at varying heights and distances. However, realizing such large-space reaching on humanoids is a complex whole-body control (WBC) problem and requires the robot to master and intelligently utilize diverse skills simultaneously. Learning from scratch often leads to optimization difficulty and poor sim2real transferability. To address these challenges, we present Real-world-Ready Skill Space (R2S2), a structural skill prior that helps autonomous whole-body-control task execution in an efficient manner while maintaining sim2real transferability. Inheriting knowledge from
a set of real-world-ready primitive skills to ease multi-skill learning, R2S2 further expands the capability of primitive skills and learns a unified structural skill representation. By sampling from R2S2, we unleash humanoid reaching potential in many real-world tasks. As a beneficial side effect, R2S2 can also support humanoid whole-body teleoperation with a large reachable space. We validate the generalizability of R2S2 in various challenging goal-reaching tasks across different robot platforms, simulation and real world.

Submission Number: 1