air-embodied-brain/Zetta-Embodiment

Zetta is an efficient closed-loop embodied harness for self-evolving physical intelligence. It evolves code-based runtime critics and recovery skills online while keeping the base policy frozen. Project Page: https://air-embodied-brain.github.io/zetta/

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Zetta is an efficient closed-loop embodied harness for self-evolving physical intelligence. It evolves code-based runtime critics and recovery skills online while keeping the base policy frozen, achieving state-of-the-art success on LIBERO-Pro (90.8%) and RoboCasa (93.6%) with an 11.1x inference speedup. More updates 🚀 Roadmap: we continue to expand model and environment coverage at an approximate cadence of one integration per week. Runtime presets live under rolloutruntime/config/presets/ and campaign preparation scripts under scripts/evolution/. Cosmos-Lite is available as an additional remote policy backend (cosmosliteremote.yaml). Python 3.11 through 3.12 is supported. The minimal test environment (no simulator/model required): Campaigns call LLM agents in two places, configured separately: planner (openai-codex). Set CODEXAPIKEY, plus CODEXBASEURL for an OpenAI-compatible gateway; runcampaign.py --model selects the model. To fail over across several routes, set ZETTAAPIPROVIDERS to a JSON list of routes (name, model, baseurl, and apikey or apikeyenv). RoboCasa and RoboTwin preparation scripts freeze its backend via --role1-planner…

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Owner: air-embodied-brain
Primary language: Python
Stars: 1,209
Forks: 83
Open issues + pull requests: 8
License: Not reported — inspect the license file
Archived: No
Default branch: main
Created: 2026-08-18T03:05:09.000Z
Last push: 2026-09-16T10:53:27.000Z

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