oomwoo

The open-source robot vacuum you build yourself.

Raspberry Pi · ROS2 · Home Assistant · 2D LiDAR · 3D printed · ESP32 · Arduino

What is this?

oomwoo is an open-source home robot vacuum you can build yourself, made for the Raspberry Pi, ROS2, Home Assistant, and 3D-printing communities. It uses an affordable 2D LiDAR to map your home and navigate on its own. Local, no cloud required for regular functionality, no vendor lock-in. Follow the community newsletter.

Reference design images - this is approximately how the finished design will look:

Reference robot vacuum cleaner top

Goals

Affordable, fully open hardware, software and firmware
Home appliance product quality - not a throwaway build
Easy to build, with step-by-step zero-to-hero instructions
2D LiDAR mapping and autonomous navigation (ROS2 / Nav2)
Native Home Assistant integration for local control
3D-printable, documented, and hackable chassis
Buildable from parts you source yourself
Local, no cloud required for regular functionality
Optional extra functionality when connected cloud
Apps on top of ROS2 to customize vacuum operation
Stretch goal: App store
Stretch goal: LeRobot integration, OpenClaw

** v0 target: bare-bones build:

3D-printed chassis
ROS2 Gazebo sim
LiDAR with manual SLAM
ROS2 on Raspberry Pi 5 AND/OR ESP32 running micro-ROS with ROS2 on local PC - decision TBD

Open Source Deliverables:

Build one

Status: design / RFC stage. Step-by-step build instructions don't exist yet — they arrive once the first BoM and parts are validated (first BoM targeted ~mid-July).

📋 Bill of Materials (BoM) — work-in-progress parts list + budget target
🛠️ Build Instructions — placeholder for now; how to follow along

Full build docs and a complete BoM are on the way, with the goal that you can source every part yourself.

Contributing

Would you like to contribute? See CONTRIBUTING for the full guide.

oomwoo is organized to built by the community, massively in parallel. The vacuum and its software are subdivided into modules, see list below.

A volunteer picks whatever module she wants, works on that module whenever she wants, submits her contribution as a PR under contributions/module-name/.

Multiple developers are welcome to work on the same module. The best solution for each module surfaces for over time, with the project master having the last call.

Pick a contribution from the list below.
Let us know you're working on it and your progress.
Check ARCHITECTURE.md for the system design and interfaces.
Say hi on Discord

Reddit: build-in-public home at r/ArduinoAndRobotics
YouTube: build-in-public channel
X: @0OMWO0
Community newsletter.

How the RFCs fit together

The modules can be worked on in parallel, but some build on others. An arrow A → B means "B builds on A" — green modules have no dependencies and are ready now; amber modules are unblocked once their parents land; the blue one needs real hardware. The mechanical modules (dust-bin, vacuum-fan) have no software dependency and can start anytime.

flowchart TD
    URDF["urdf-gazebo-sim"]

    CM["clean-and-map"]
    NL["nav-localize"]
    DC["dock-cycle"]
    RS["recovery-safety"]
    FC["floor-care"]
    CJ["cleaning-jobs"]

    LR["live-robot-bringup"]

    DB["dust-bin"]
    VF["vacuum-fan"]

    URDF --> CM
    URDF --> RS
    CM --> NL
    CM --> FC
    NL --> DC
    CM --> CJ
    NL --> CJ
    DC --> CJ
    CM --> LR
    NL --> LR
    DC --> LR
    RS --> LR
    FC --> LR
    CJ --> LR

    classDef ready fill:#d4edda,stroke:#28a745,color:#155724;
    classDef blocked fill:#fff3cd,stroke:#ffc107,color:#856404;
    classDef hw fill:#cfe2ff,stroke:#0d6efd,color:#084298;
    class URDF,DB,VF ready;
    class CM,NL,DC,RS,FC,CJ blocked;
    class LR hw;

A standalone image of this graph (with a legend) lives at assets/rfc-graph.png for sharing on Discord, Reddit, etc. The source is assets/rfc-graph.mmd — edit it and re-export with npx @mermaid-js/mermaid-cli -i assets/rfc-graph.mmd -o assets/rfc-graph.png -s 3.

Requests for Contributions

Module	ID	Phase	Notes
ROS2 URDF + Gazebo sim	urdf-gazebo-sim	Ready to start work	Design URDF, TF, bumper, simulate in Gazebo
First clean: coverage + mapping + exploration	clean-and-map	Blocked by urdf-gazebo-sim	Coverage cleaning while SLAM-mapping and exploring, in Gazebo
Localization & navigation on a known map	nav-localize	Blocked by urdf-gazebo-sim, clean-and-map	Nav2 nav, AMCL localization, relocalize when lost, resume map
Dock cycle: undock, dock, recharge	dock-cycle	Blocked by urdf-gazebo-sim, nav-localize	Undock, return-to-dock, precise docking, station services, find dock when lost
Recovery behaviors & safety	recovery-safety	Blocked by urdf-gazebo-sim	Recovery ladder, escalation, pause-and-alert, safety sensors, status reporting
Floor-surface handling & edge cleaning	floor-care	Blocked by urdf-gazebo-sim, clean-and-map	Wall/edge following, carpet vs hardwood, mop lift/lower
Cleaning modes, zones & job orchestration	cleaning-jobs	Blocked by urdf-gazebo-sim + behaviors	Modes (regular/spot), virtual walls, room segmentation, job splitting + resume
Live robot bring-up & validation	live-robot-bringup	Blocked by behaviors + needs hardware	Connect real vacuum to ROS2, re-run sim tests on hardware
Dust bin 3D design	dust-bin	Ready to start work	Design, 3D print, test dust bin
Vacuum fan / blower assembly	vacuum-fan	Ready to start work	Source blower motor + impeller, design volute housing + gasket

The full granular module list lives in docs/RFC_MASTER_LIST.md.

Source code reference

oomwoo ROS2 and Ubuntu installation source code
oomwoo ROS2 URDF package and config source code
remakeai reference vacuum teardown — a consumer LiDAR vacuum with a basic dock and stationary mop.

Related prior art

AlieksieievYurii/vacuum-cleaner — a DIY 3D-printed robot vacuum (Raspberry Pi Zero W, gyroscope-based, Fusion 360, Android control app, no dock)
kaiaai/LDS, kaiaai/lds2d — open-source 2D LiDAR libraries (C++, Python) supporting 23+ LiDAR models
remakeai/vacuum_ros2_bridge — ROS2 bridge for a 3irobotix CRL-200-based vacuum (Proscenic), full ROS2 control
Valetudo — cloud-free firmware replacement for commercial vacuums (local app-level control, not ROS2)
Dennis Giese / robotinfo.dev — teardowns and rootability of commercial robot vacuums.
codetiger/VacuumTiger - 3irobotix CRL-200-based vacuum low-level control reverse engineered
Build a ROS2/LiDAR robot crash course - watch this if you have no robotics experience
Open Mower - open-source outdoor lawn mower

Design research

We reviewed the 2025–2026 consumer robot vacuum landscape (global + China-sourceable brands, all price tiers) to decide which solutions to copy and which to skip. Key takeaways for the build:

Suction is a sourcing problem, not an engineering one. Real-world cleaning does not track advertised suction (Pa); ~$500 mid-tier models beat flagships. A moderate sealed sourced motor + a good brush + tight airflow sealing matches flagships — no custom impeller needed.
"Never gets stuck" needs camera + AI sensor fusion, not LiDAR alone — LiDAR is blind below its ~10 cm turret (cables, socks). v1 leans on the bumper for low obstacles; vision-based avoidance is a later / experimental goal, not an MVP promise.
Anti-tangle brush: a tapered rubber roller resists hair-wrap best (a top user complaint) and is easy to 3D-print.
Mop: a 3D-printed dual-spinning mop is competitive; the self-washing roller mop's edge is overstated and hard to replicate — skip it for now.

Well-loved models worth studying: Eufy Omni S2 (obstacle avoidance), Narwal Flow (roller mop), Ecovacs Deebot T90 Pro Omni (~$499 all-rounder), Dreame X40 Ultra (dual-spinning mop). Dreame is also the most Valetudo-rootable brand — the safest donor to study. (Per-model rankings are directional, from single-run reviewer tests.)

About

The project name "oomwoo" is a rotational ambigram - it reads the same flipped 180°, like the robot itself, roaming your floor in every direction.

The project is sponsored by makerspet.com and remake.ai. We are reusing their open-source solutions.

If you'd rather skip the parts hunt, a kit (motors, PCB, brushes, gaskets, LiDAR) will be available at makerspet.com, from the same maker behind this project. The kit is a convenience, never a requirement. Everything here stays open.
When we get to apps, remake.ai will be providing its robot apps platform and app store. Using the app store will be entirely optional. The vacuum will always support cloud-free, local operation for regular functionality out-of-the-box.

License

Code is released under the Apache License 2.0.

Hardware design files, once added, to be released under an open hardware license (TBD).