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TODDLERBOT — STANFORD OPEN-SOURCE TODDLER-SIZED HUMANOID

A toddler-sized humanoid that learns tasks from human demonstrations, then repeats them — and the whole platform is MIT-licensed and printable.

by Stanford Autonomous Systems Lab

FULL CAD BOM FIRMWARE DOCS

RoboticsAI

difficulty
●●●●●
time
weeks-plus
license
MIT
repo
repo ACTIVE720 stars

WHAT YOU’LL NEED

  • 3D printer + filament — printable parts — files are in the repo
  • Dev board / microcontroller — runs the project firmware
  • Soldering kit + basic tools — one-time buy, serves every future build

Partner

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Videos
1

COMPAREE VERDICT

ToddlerBot is a toddler-sized humanoid research platform from Stanford's Autonomous Systems Lab, designed for loco-manipulation tasks: robots that walk, manipulate objects, and learn from human demonstrations using diffusion policies and reinforcement learning. The January 2026 release added whole-body multi-skill locomotion. The software stack installs with pip, the CAD is public on Onshape, and printable files are on MakerWorld — all under an MIT licence. This is a serious research platform, not a weekend robot. The repository assumes you already know ROS, PyTorch, and Isaac Sim, and can source your own servos, motors, and control electronics from the CAD. There is no explicit BOM, no beginner assembly guide, and no hand-holding on tuning. The single thing most likely to go wrong is underestimating the integration work: even with all the files, you are building a one-off research prototype, not assembling a kit. If you are doing humanoid research or serious multi-robot manipulation experiments and need an open platform to build on, this is one of the best-documented starts available. If you want a robot that works out of the box, this is not it.

NOT IN THE REPO

  • —CAD is on Onshape (public), printable files are on MakerWorld, and the software stack is pip-installable Python.
  • —The repository contains training code, simulation environments, and real-robot deployment scripts — but no explicit bill of materials for actuators, electronics, or connectors.
  • —The structure is printable; the motors and servos are commercial hobby-grade parts you purchase separately.
  • —Documentation covers installation, simulation, and policy training — but assumes significant ML and robotics background.
  • —MIT licence permits commercial use.
  • —The January 2026 release added whole-body multi-skill locomotion; this is an active research platform, not a turnkey kit.

Can I build this?

PrintFull humanoid structure — arms, legs, torso, head — printable on a standard FDM printer; files are on MakerWorld
BuyCommercial hobby servos and motors (not specified in repo), control electronics, sensors, wiring, connectors — no explicit BOM provided, you derive it from the CAD
Tools3D printer (FDM), soldering station, Linux workstation with GPU for simulation and training, ROS, Isaac Sim, Python ML stack
SkillsAdvanced — requires ML (diffusion policies, RL), ROS, robotics kinematics, electronics integration, and the ability to debug multi-robot systems
TimeWeeks to months — printing is days, assembly is weeks, getting the software stack running and training your first policy is another week minimum
Cost$$$, dominated by actuators and control electronics — printable structure is cheap, motors and servos are not
SafetyActuators can pinch or crush if mis-controlled; lithium batteries if you use them for mobile power; otherwise standard electronics and mechanical assembly precautions. No mains voltage in the design shown.

Build at your own risk. Projects involve tools, electronics and sometimes mains voltage — follow the creator’s safety notes.

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Videos

Primary demonstration video from the repository

Gallery

Start here

Navigation into the creator’s own docs — we don’t rewrite the guide, we route you to the source.

  1. 1.Read the repository README and watch the demonstration videos to understand what the platform actually does and what background you need (The README is technical and assumes ML + robotics familiarity — if it reads like a foreign language, this project is not a good starting point)
  2. 2.Download the printable files from MakerWorld and review the CAD on Onshape to derive your own BOM for actuators and electronics(There is no explicit parts list — you work backward from the mechanical design to figure out what motors, servos, and controllers fit)
  3. 3.Set up the software stack: clone the repo, install dependencies, and verify simulation in Isaac Sim before touching hardware(The stack is pip-installable, but you need a Linux workstation with a GPU and familiarity with ROS and PyTorch)
  4. 4.Print, assemble, wire, and integrate the physical robot — this is where most of the time goes(Expect troubleshooting, calibration, and multiple iterations on wiring and control tuning)

Resources

Documentation, files and community threads for this build — we link straight to the original sources and never rehost the creator’s files.

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KNOWN ISSUES

  • There is no bill of materials — you derive your own parts list from the CAD, which means you need to understand what actuators, controllers, and sensors are mechanically and electrically compatible.
  • The software stack assumes significant ML and robotics background — if you have never trained a diffusion policy or used Isaac Sim, expect a steep learning curve before you run your first demo.
  • This is a research platform, not a kit — assembly, wiring, calibration, and debugging are all on you, and there is no step-by-step assembly guide.
  • Actuators and electronics dominate the cost — the printable structure is cheap, but commercial servos and motors for a humanoid are not, and you will need several.
  • Multi-robot collaboration (two ToddlerBots working together) requires two complete builds and coordinated control — do not assume that is the starting point.
  • The January 2026 locomotion release is recent — expect the codebase to evolve, and be prepared to pull updates and adapt your build.

Is there a parts list?

No explicit BOM is provided. You derive your own from the Onshape CAD by identifying what motors, servos, controllers, and sensors fit the mechanical design.

Can I build this without ML experience?

Not realistically. The platform is designed for loco-manipulation research using diffusion policies and reinforcement learning — the repository assumes you already know PyTorch, ROS, and Isaac Sim.

How much does it cost to build?

The printable structure is inexpensive, but actuators and control electronics push the total into the $$$ range — expect several hundred to over a thousand depending on what servos and motors you choose.

Does it work out of the box?

No. This is a research platform. You print, source parts, assemble, wire, calibrate, and train policies yourself. There is no turnkey assembly.

Can it really learn tasks from human demonstrations?

Yes — that is the point of the platform. You collect human demonstrations, train a diffusion policy, and deploy it to the robot. But training, sim-to-real transfer, and tuning are all part of the work.

What is the locomotion update?

The January 2026 release added whole-body multi-skill locomotion — the robot can now walk and manipulate at the same time, not just perform tabletop tasks.

Community builds

No community builds yet — be the first, we feature the best ones.

Discussion1

FROM THE COMPAREE TEAM

The repository has training code, simulation environments, and deployment scripts — but no explicit BOM. If you have built a printable humanoid before, what is your process for deriving a parts list from CAD?

CompareeTEAM1mo agoedited

Practical notes from our verification: the CAD is genuinely public on Onshape, the printable files are on MakerWorld, and the pip install works — but there is no hand-holding on sourcing actuators or assembly. The repository README is written for ML researchers who already know ROS and PyTorch, not for makers building their first robot. The locomotion update is real and recent (January 2026), which means the codebase is still evolving. If you are doing humanoid research and need an open platform, this is a strong start — but if you are looking for a weekend build or a kit with instructions, this is not it.

Stanford Autonomous Systems Lab

ToddlerBot is a research platform from Stanford's Autonomous Systems Lab, designed to make humanoid loco-manipulation research accessible to labs without the budget for commercial humanoid platforms. The project was released open-source under MIT to enable other research groups to build on the same foundation.

GitHub

Star the project on GitHub

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  • Comparee is not the author of the projects featured here. All rights to each project belong to its creator — every page links to the original source, and we never host creators’ files.
  • Information is provided without warranty and may become outdated as projects evolve. Prices are indicative bands only — always check the creator’s parts list for current costs.
  • Building and operating any project is at your own responsibility. Protective equipment, safe workshop practice and compliance with local regulations are the builder’s responsibility.
GitHub repo