dimensionalOS/dimos

dimensionalOS 프로필

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<div align="center"> <img width="1000" alt="banner_bordered_trimmed" src="https://github.com/user-attachments/assets/64f13b39-da06-4f58-add0-cfc44f04db4e" /> <h2>The Agentive Operating System for Physical Space</h2> [![Discord](https://img.shields.io/discord/1341146487186391173?style=flat-square&logo=discord&logoColor=white&label=Discord&color=5865F2)](https://discord.gg/dimos) [![Stars](https://img.shields.io/github/stars/dimensionalOS/dimos?style=flat-square)](https://github.com/dimensionalOS/dimos/stargazers) [![Forks](https://img.shields.io/github/forks/dimensionalOS/dimos?style=flat-square)](https://github.com/dimensionalOS/dimos/fork) [![Contributors](https://img.shields.io/github/contributors/dimensionalOS/dimos?style=flat-square)](https://github.com/dimensionalOS/dimos/graphs/contributors) [![Docs](https://img.shields.io/badge/Docs-docs.dimensionalos.com-1682a3?style=flat-square&logo=readthedocs&logoColor=white)](https://docs.dimensionalos.com) ![Nix](https://img.shields.io/badge/Nix-flakes-5277C3?style=flat-square&logo=NixOS&logoColor=white) ![NixOS](https://img.shields.io/badge/NixOS-supported-5277C3?style=flat-square&logo=NixOS&logoColor=white) ![CUDA](https://img.shields.io/badge/CUDA-supported-76B900?style=flat-square&logo=nvidia&logoColor=white) [![Docker](https://img.shields.io/badge/Docker-ready-2496ED?style=flat-square&logo=docker&logoColor=white)](https://www.docker.com/) <a href="https://trendshift.io/repositories/23169" target="_blank"><img src="https://trendshift.io/api/badge/repositories/23169" alt="dimensionalOS%2Fdimos | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a> <big><big> [Docs](https://docs.dimensionalos.com) • [Hardware](#hardware) • [Installation](#installation) • [Agent CLI & MCP](#agent-cli-and-mcp) • [Blueprints](#blueprints) • [dimTELE: Remote Teleop](#dimtele-remote-teleop) • [Development](#development) ⚠️ **Pre-Release Beta** ⚠️ </big></big> </div> # About Dimensional is the modern operating system for generalist robotics. We are setting the next-generation SDK standard, integrating with the majority of robot manufacturers. With a simple install and no ROS required, build physical applications entirely in python that run on any humanoid, quadruped, or drone. Dimensional is agent native -- "vibecode" your robots in natural language and build (local & hosted) multi-agent systems that work seamlessly with your hardware. Agents run as native modules — subscribing to any embedded stream, from perception (lidar, camera) and spatial memory down to control loops and motor drivers. <table> <tr> <td align="center" width="50%"> <a href="docs/capabilities/navigation/index.md"><img src="assets/readme/navigation.gif" alt="Navigation" width="100%"></a> </td> <td align="center" width="50%"> <img src="assets/readme/perception.png" alt="Perception" width="100%"> </td> </tr> <tr> <td align="center" width="50%"> <h3><a href="docs/capabilities/navigation/index.md">Navigation and Mapping</a></h3> SLAM, dynamic obstacle avoidance, route planning, and autonomous exploration — via both DimOS native and ROS<br><a href="https://x.com/stash_pomichter/status/2010471593806545367">Watch video</a> </td> <td align="center" width="50%"> <h3>Perception</h3> Detectors, 3d projections, VLMs, Audio processing </td> </tr> <tr> <td align="center" width="50%"> <a href="docs/capabilities/agents/index.md"><img src="assets/readme/agentic_control.gif" alt="Agents" width="100%"></a> </td> <td align="center" width="50%"> <img src="assets/readme/spatial_memory.gif" alt="Spatial Memory" width="100%"> </td> </tr> <tr> <td align="center" width="50%"> <h3><a href="docs/capabilities/agents/index.md">Agentive Control, MCP</a></h3> "hey Robot, go find the kitchen"<br><a href="https://x.com/stash_pomichter/status/2015912688854200322">Watch video</a> </td> <td align="center" width="50%"> <h3>Spatial Memory</h3> Spatio-temporal RAG, Dynamic memory, Object localization and permanence<br><a href="https://x.com/stash_pomichter/status/1980741077205414328">Watch video</a> </td> </tr> </table> # Hardware <table> <tr> <td align="center" width="20%"> <h3>Quadruped</h3> <img width="245" height="1" src="assets/readme/spacer.png"> </td> <td align="center" width="20%"> <h3>Humanoid</h3> <img width="245" height="1" src="assets/readme/spacer.png"> </td> <td align="center" width="20%"> <h3>Arm</h3> <img width="245" height="1" src="assets/readme/spacer.png"> </td> <td align="center" width="20%"> <h3>Drone</h3> <img width="245" height="1" src="assets/readme/spacer.png"> </td> <td align="center" width="20%"> <h3>Misc</h3> <img width="245" height="1" src="assets/readme/spacer.png"> </td> </tr> <tr> <td align="center" width="20%"> 🟩 <a href="docs/platforms/quadruped/go2/index.md">Unitree Go2 pro/air</a><br> 🟥 <a href="dimos/robot/unitree/b1">Unitree B1</a><br> </td> <td align="center" width="20%"> 🟨 <a href="docs/platforms/humanoid/g1/index.md">Unitree G1</a><br> </td> <td align="center" width="20%"> 🟨 <a href="docs/capabilities/manipulation/index.md">Xarm</a><br> 🟨 <a href="docs/capabilities/manipulation/index.md">AgileX Piper</a><br> </td> <td align="center" width="20%"> 🟧 <a href="dimos/robot/drone/README.md">MAVLink</a><br> 🟧 <a href="dimos/robot/drone/README.md">DJI Mavic</a><br> </td> <td align="center" width="20%"> 🟥 <a href="https://github.com/dimensionalOS/openFT-sensor">Force Torque Sensor</a><br> </td> </tr> </table> <br> <div align="right"> 🟩 stable 🟨 beta 🟧 alpha 🟥 experimental </div> > [!IMPORTANT] > 🤖 Direct your favorite Agent (OpenClaw, Claude Code, etc.) to [AGENTS.md](AGENTS.md) and our [CLI and MCP](#agent-cli-and-mcp) interfaces to start building powerful Dimensional applications. # Installation ## Guided installation (recommended) Use the official installer to set up system dependencies, Python 3.12, and dimOS: ```sh skip curl -fsSL https://raw.githubusercontent.com/dimensionalOS/dimos/main/scripts/install.sh | bash ``` > See [`scripts/install.sh --help`](scripts/install.sh) for non-interactive and advanced options. See [installer options](docs/installation/index.md), or platform notes: - 🟩 [Ubuntu 22.04 / 24.04](docs/installation/ubuntu.md) - [NixOS / General Linux (not CI-tested)](docs/installation/nix.md) - 🟧 [macOS](docs/installation/osx.md) > Full system requirements, tested configs, and dependency tiers: [docs/requirements.md](docs/requirements.md) ## Manual installation If you need to install without the script, follow the system-package and Python steps for [Ubuntu](docs/installation/ubuntu.md#manual-installation), [macOS](docs/installation/osx.md#manual-installation), or [Nix](docs/installation/nix.md#manual-installation). ## Quickstart Activate the environment using the command printed by the installer, then run: ```bash # Replay a recorded quadruped session (no hardware needed) # NOTE: First run will show a black rerun window while ~75 MB downloads from LFS dimos --replay run unitree-go2 ``` ```bash # The installer's default extras include simulation support. # Run quadruped in MuJoCo simulation dimos --simulation run unitree-go2 # Run humanoid in simulation dimos --simulation run unitree-g1-sim ``` ```bash # Control a real robot (Unitree quadruped over WebRTC) export ROBOT_IP=<YOUR_ROBOT_IP> dimos run unitree-go2 ``` # Featured Runfiles | Run command | What it does | |-------------|-------------| | `dimos --replay run unitree-go2` | Quadruped navigation replay — SLAM, costmap, A* planning | | `dimos --replay --replay-db go2_bigoffice run unitree-go2-memory` | Quadruped temporal memory replay | | `dimos --simulation run unitree-go2-agentic` | Quadruped agentic + MCP server in simulation | | `dimos --simulation run unitree-g1-sim` | Humanoid in MuJoCo simulation | | `dimos --replay run drone-basic` | Drone video + telemetry replay | | `dimos --replay run drone-agentic` | Drone + LLM agent with flight skills (replay) | | `dimos run demo-camera` | Webcam demo — no hardware needed | | `dimos run keyboard-teleop-xarm7` | Keyboard teleop with mock xArm7 (requires `dimos[manipulation]` extra) | | `dimos --simulation run unitree-go2-agentic-ollama` | Quadruped agentic with local LLM (requires [Ollama](https://ollama.com) + `ollama serve`) | > Full blueprint docs: [docs/usage/blueprints.md](docs/usage/blueprints.md) # Agent CLI and MCP The `dimos` CLI manages the full lifecycle — run blueprints, inspect state, interact with agents, and call skills via MCP. ```bash dimos run unitree-go2-agentic --daemon # Start in background dimos status # Check what's running dimos log -f # Follow logs dimos agent-send "explore the room" # Send agent a command dimos mcp list-tools # List available MCP skills dimos mcp call move_to --arg x=0.5 --arg relative=true # Call a skill directly dimos stop # Shut down ``` > Full CLI reference: [docs/usage/cli.md](docs/usage/cli.md) # dimTELE: Remote Teleop **dimTELE** is hosted teleoperation for DimOS robots: operate them remotely from any browser or Quest headset over WebRTC. The robot dials out to a hosted broker, so you don't need to open any inbound ports on the robot's network. It works behind a home router, on Wi-Fi, wired LAN, or cellular. 1. Open the [Dimensional console](https://console.dimensional.org/console/keys), sign in, and create an API key (**API keys → Create key**). 2. Run a teleop blueprint on the robot, passing the key as `TRANSPORTS__BROKER__API_KEY`: ```bash # Robot dials out to the broker with your API key TRANSPORTS__BROKER__API_KEY=<your-api-key> \ dimos run teleop-hosted-go2-transport ``` 3. Your robot appears under **Available Robots** — click **Connect** and drive the robot from the browser. | Blueprint | Notes | |-----------|-------| | `teleop-hosted-go2-transport` | Browser teleop — drive + camera + minimap + click-to-nav (recommended) | | `teleop-hosted-go2-multicam` | Adds a second RealSense, operator-selectable, mux'd into one video track | > Full guide: [dimTELE](docs/capabilities/teleoperation/hosted.md) • [WebRTC internals](dimos/teleop/hosted/README.md) # Usage ## Use DimOS as a Library See below a simple robot connection module that sends streams of continuous `cmd_vel` to the robot and receives `color_image` to a simple `Listener` module. DimOS Modules are subsystems on a robot that communicate with other modules using standardized messages. ```py skip import threading, time, numpy as np from dimos.core.coordination.blueprints import autoconnect from dimos.core.core import rpc from dimos.core.module import Module from dimos.core.stream import In, Out from dimos.msgs.geometry_msgs import Twist from dimos.msgs.sensor_msgs import Image, ImageFormat class RobotConnection(Module): cmd_vel: In[Twist] color_image: Out[Image] @rpc def start(self): threading.Thread(target=self._image_loop, daemon=True).start() def _image_loop(self): while True: img = Image.from_numpy( np.zeros((120, 160, 3), np.uint8), format=ImageFormat.RGB, frame_id="camera_optical", ) self.color_image.publish(img) time.sleep(0.2) class Listener(Module): color_image: In[Image] @rpc def start(self): self.color_image.subscribe(lambda img: print(f"image {img.width}x{img.height}")) if __name__ == "__main__": autoconnect( RobotConnection.blueprint(), Listener.blueprint(), ).build().loop() ``` ## Blueprints Blueprints are instructions for how to construct and wire modules. We compose them with `autoconnect(...)`, which connects streams by `(name, type)` and returns a `Blueprint`. Blueprints can be composed, remapped, and have transports overridden if `autoconnect()` fails due to conflicting variable names or `In[]` and `Out[]` message types. A blueprint example that connects the image stream from a robot to an MCP-backed LLM agent for reasoning and action execution. ```py skip from dimos.core.coordination.blueprints import autoconnect from dimos.core.transport import LCMTransport from dimos.msgs.sensor_msgs import Image from dimos.robot.unitree.go2.connection import go2_connection from dimos.agents.mcp.mcp_client import McpClient from dimos.agents.mcp.mcp_server import McpServer blueprint = autoconnect( go2_connection(), McpServer.blueprint(), McpClient.blueprint(), ).transports({("color_image", Image): LCMTransport("/color_image", Image)}) # Run the blueprint if __name__ == "__main__": blueprint.build().loop() ``` ## Library API - [Modules](docs/usage/modules.md) - [LCM](docs/usage/lcm.md) - [Blueprints](docs/usage/blueprints.md) - [Transports](docs/usage/transports/index.md) — Zenoh, LCM, DDS, ROS 2 - [Data Streams](docs/usage/data_streams/index.md) - [Configuration](docs/usage/configuration.md) - [Visualization](docs/usage/visualization.md) - [Web](docs/web/index.md): cockpit, web SDK, relay ## Demos <img src="assets/readme/dimos_demo.gif" alt="DimOS Demo" width="100%"> # Development ## Develop on DimOS ```sh skip export GIT_LFS_SKIP_SMUDGE=1 git clone https://github.com/dimensionalOS/dimos.git cd dimos # Run the default test suite (uv run syncs deps on demand; --all-groups # only needed for self-hosted tests / mypy — see docs/development/testing.md) uv run pytest --numprocesses=auto dimos ``` ## Multi Language Support Python is our glue and prototyping language, but we support many languages via LCM interop. Check our language interop examples: - [C++](examples/language-interop/cpp/) - [Lua](examples/language-interop/lua/) - [TypeScript](examples/language-interop/ts/)

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2026-10-15

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