EMOS – The Embodied Operating System¶

The open-source unified orchestration layer for Physical AI.

EMOS transforms robots into Physical AI Agents. It provides a hardware-agnostic runtime that lets robots see, think, move, and adapt – all orchestrated from pure Python scripts called Recipes.

Write a Recipe once, deploy it on any robot – from wheeled AMRs to humanoids – without rewriting code.

Get Started • Why EMOS? • View on GitHub

What You Can Build¶

Intelligent Agents

Wire together vision, language, speech, and memory components into agentic workflows. Route queries by intent, answer questions about the environment, or build a semantic map – all from a single Python script.

See cognition recipes

Autonomous Navigation

GPU-accelerated planning and control for real-world mobility. Point-to-point navigation, path recording, and vision-based target following – across differential drive, Ackermann, and omnidirectional platforms.

See navigation recipes

Runtime Adaptivity

Event-driven architecture lets agents reconfigure themselves at runtime. Hot-swap ML models on network failure, switch navigation algorithms when stuck, trigger recovery maneuvers from sensor events, or compose complex behaviors with logic gates.

See adaptivity recipes

Planning & Manipulation

Use VLMs for high-level task decomposition and VLAs for end-to-end manipulation. Closed-loop control where a VLM referee stops actions on visual task completion.

See manipulation recipes

What’s Inside¶

EMOS is built on three open-source components:

Component	Role
EmbodiedAgents	Intelligence layer – agentic graphs of ML models with semantic memory and event-driven reconfiguration
Kompass	Navigation layer – GPU-powered planning and control for real-world mobility
Sugarcoat	Architecture layer – event-driven system primitives and imperative launch API