Researchers plug GPT-6 Astra directly into a robot and let it clean up an unfamiliar kitchen
Stanford and Caltech's HomeBody uses GPT-6 Astra to let a Unitree G1 tidy an unfamiliar kitchen.
Stanford and Caltech researchers built HomeBody, which uses GPT-6 Astra to let a Unitree G1 robot navigate an unfamiliar kitchen, tidy it, and fetch items from drawers. The vision-language model skips a separate trained controller and calls a skill library for grasping, navigation, and opening drawers. The robot first explores the room, builds a digital twin in Nvidia Isaac Sim, and logs objects in spatial memory so it can find items outside its view. Reported limits include Astra latency, overheating finger servos, and high compute cost, and the code is on GitHub.
- HomeBody links GPT-6 Astra directly to a Unitree G1 skill library.
- The robot maps the kitchen in Isaac Sim and keeps spatial memory.
- The model plans cleanup steps and self-corrects after failed actions.
- Limits include Astra latency, overheating finger servos, and compute cost.
- Code is on GitHub; earlier work also flagged robot-control safety issues.
- Products
- Unitree G1HomeBodyIsaac Sim
- AI models
- GPT-6 Astra
From the original article
1 min read at the-decoder.com
Researchers from Stanford and Caltech had a humanoid robot powered by GPT-6 Astra independently tidy up an unfamiliar kitchen. Their HomeBody system skips a specially trained control layer, letting the language model call directly into modular skills like grasping and navigating. The article Researchers plug GPT-6 Astra directly into a robot and let it clean up an unfamiliar kitchen appeared first on The Decoder.
By Matthias Bastian · the-decoder.com
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