ExBody2: Advanced Expressive Humanoid Whole-Body Control
About
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 specific motions. We observed significant improvement of tracking performance after fine-tuning on a small amount of data, at the expense of the others.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Humanoid motion tracking | MotionX (test) | Success Rate88 | 9 | |
| Motion Tracking | Nymeria (test) | Success Rate94 | 6 | |
| Humanoid Control | AMASS IsaacLab ID (test) | Success Rate86.6 | 5 | |
| Humanoid Control | AMASS IsaacLab + DR ID (test) | MPJPE (Egocentric, mm)237 | 5 | |
| Humanoid Control | AMASS Genesis OOD (test) | Ego MPJPE (mm)305 | 5 | |
| Humanoid Control | AMASS Genesis + DR OOD (test) | Eg-MPJPE (mm)342 | 5 |