Event
Dual-critic humanoid loco-manipulation paper trains Unitree G1 policies in NVIDIA Isaac Lab
Evidence notes
- The paper compares unified and dual critic architectures for humanoid loco-manipulation reinforcement learning.
- Experiments train Unitree G1 policies through a 13-level curriculum in NVIDIA Isaac Lab.
- This is outside-team product research; Isaac Lab is the primary product binding while G1 is captured as a related product in metadata.
Company context
NVIDIA is a compute and AI infrastructure company providing the simulation, training, edge-compute and model platforms used across modern robotics. Its stack includes tools for robot learning, digital twins, perception and on-device inference.
Context
- Company
- NVIDIA
- Segment
- Ai Compute
- Event type
- Research Publication
- Evidence
- Source linked
- Added to Korthos
- Jun 27, 2026
- Geography
- Santa Clara, California · United States