HomeBody: A humanoid that explores, remembers, and acts on its own

1 Caltech 2 Stanford University † Equal advising

A common approach to humanoid autonomy follows a three-part architecture: a System 2 VLM processes visual observations and instructions, a learned System 1 VLA produces commands, and a System 0 controller executes coordinated motion.

As frontier VLMs such as Astra become more capable, we ask whether a learned VLA is still needed between high-level reasoning and the robot’s skills. Can System 2 directly orchestrate a library of reusable motor skills?

We present HomeBody , a system that equips frontier VLMs with persistent spatial memory and composable humanoid skills for long-horizon tasks . In a previously unseen kitchen, our system allows a Unitree G1 guided by GPT Astra to clean up across the room and retrieve a remembered object from an underspecified request, without environment-specific training data or additional policy learning.