HumanPlus
Stanford CoRL 2024 system + HDF5 imitation-learning demos on a 33-DoF Unitree H1 humanoid for whole-body skills via human shadowing.
| Year | 2024 |
|---|---|
| Total hours | 40 |
| Embodiments | human, unitree_humanoid |
| Modalities | proprioception, rgb |
| Task categories | manipulation, navigation |
| License | unknown |
| Access | open |
| Maintainer | Stanford University |
HumanPlus is a Stanford full-stack system that lets a customized 33-DoF Unitree H1 humanoid shadow human body and hand motion in real time from RGB cameras, and then learn autonomous whole-body skills via behavior cloning on teleoperated demonstrations. The low-level shadowing policy is trained in simulation using the 40-hour AMASS human-motion dataset; the released task data consists of HDF5 imitation-learning episodes (ACT/Mobile-ALOHA style) recording two head-mounted egocentric RGB cameras plus 19-DoF body and dexterous-hand joint positions. Demonstrated skills include folding clothes, rearranging objects, warehouse unloading, two-robot greeting, wearing a shoe, and typing.