ExBody2: Advanced Expressive Humanoid Whole-Body Control
Mazeyu Ji, Xuanbin Peng, Fangchen Liu, Jialong Li, Ge Yang, Xuxin, Cheng, Xiaolong Wang

TL;DR
This paper introduces ExBody2, a novel humanoid robot control method that enables expressive, stable, and robust whole-body motions by training on human and simulated data, then transferring to real robots.
Contribution
The paper presents a new decoupling technique for velocity and landmark tracking, along with a two-step training process for effective real-world deployment of expressive humanoid motions.
Findings
Improved tracking performance after fine-tuning.
Successful deployment of walking, crouching, and dancing motions.
Trade-off analysis between versatility and motion accuracy.
Abstract
This paper tackles the challenge of enabling real-world humanoid robots to perform expressive and dynamic whole-body motions while maintaining overall stability and robustness. We propose Advanced Expressive Whole-Body Control (Exbody2), a method for producing whole-body tracking controllers that are trained on both human motion capture and simulated data and then transferred to the real world. We introduce a technique for decoupling the velocity tracking of the entire body from tracking body landmarks. We use a teacher policy to produce intermediate data that better conforms to the robot's kinematics and to automatically filter away infeasible whole-body motions. This two-step approach enabled us to produce a student policy that can be deployed on the robot that can walk, crouch, and dance. We also provide insight into the trade-off between versatility and the tracking performance on…
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Taxonomy
TopicsRobotic Locomotion and Control · Prosthetics and Rehabilitation Robotics · 3D Printing in Biomedical Research
