Stanford and Caltech use GPT-6 Astra in Unitree G1 robot to clean unfamiliar kitchen
Researchers from Stanford and Caltech introduced HomeBody, a system that lets a Unitree G1 robot explore an unknown kitchen, build a digital twin in Nvidia's Isaac Sim, and autonomously tidy up and fetch items. The robot relies on a swappable vision‑language model—GPT‑6 Astra—that calls directly into an extensible skill library for grasping, navigation, and drawer opening, eliminating the usual…
Key points
- Stanford and Caltech built HomeBody, letting a Unitree G1 robot autonomously clean an unfamiliar kitchen.
- The system connects GPT-6 Astra directly to the robot, bypassing a trained control layer.
- Limitations noted include model latency, overheating finger servos, and high compute costs.
The language model plans each cleaning step and self‑corrects when errors occur. The team noted practical limits: GPT‑6 Astra’s response latency, overheating of the robot’s finger servos, and the high compute cost of running the model. The code has been released on GitHub, and OpenAI has previously signaled a return to robotics research for personal‑use applications.
Model page: GPT-6 (Astra) →
Researchers plug GPT-6 Astra directly into a robot and let it clean up an unfamiliar kitchen
The Decoder · 27 September 2026
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