Mini Pupper 2
Open-source ROS robot dog kit
$649
Mini Pupper 2 is an open-source, Raspberry Pi-powered quadruped robot dog kit developed by MangDang for robotics education and hobbyist experimentation. It runs ROS2 and supports SLAM, navigation, computer vision, and generative-AI integrations such as ChatGPT, Gemini, and Claude. The kit is sold in several assembly configurations and is designed to be highly expandable and customizable.
Released: 2022
RoboZaps evaluation note
Buyer-side view of Mini Pupper 2
RoboZaps reviews Mini Pupper 2 as part of a broader robot shortlist, not as a single-vendor pitch. Buyers should compare availability, deployment maturity, support terms, integration work, and total cost before committing.
- Spec sources
- 0 linked
- Last verified
- Not verified
- Availability
- announced
- Support caveat
- Verify local training, maintenance, parts, and uptime terms.
Best fit
Teams that need to compare Mini Pupper 2 against otherquadrupeds options with deployment readiness, commercial terms, and support assumptions made explicit.
Not best fit
Buyers who need a guaranteed off-the-shelf deployment before confirming current availability, integrator coverage, site readiness, and post-sale support ownership.
Commercial review before shortlist
Before recommending a robot, RoboZaps checks whether the commercial and lifecycle picture is clear enough for a buyer to act.
- price range
- availability
- lead time
- support terms
- deployment readiness
- training needs
- maintenance risk
- source quality
Buyer-intent resources
Start with the database when you need current records, then use the buyer guides for sourcing, procurement, deployment support, and shortlist context.
Overview
Mini Pupper 2 is an open-source quadruped robot dog kit from MangDang, a robotics company founded in 2020 and based in Hong Kong. It builds on the company's original Mini Pupper, aiming to make hands-on robotics accessible to students, educators, and hobbyists at an approachable price point.
The robot is powered by a Raspberry Pi compute platform and runs ROS2, letting users explore SLAM, navigation, kinematics, and computer vision with ready-to-use examples. It also integrates with generative-AI tools such as ChatGPT, Gemini, and Claude, positioning it as a flexible learning and experimentation platform.
Sold through MangDang's official store in multiple assembly configurations, including pre-assembled and DIY upgrade kits, Mini Pupper 2 is marketed as quick to set up and highly expandable, with optional add-ons such as a Raspberry Pi camera module for vision projects.
Key Features
- Open-source hardware and software designed for customization and community contribution
- Runs ROS2 with ready-to-use SLAM and navigation examples
- Raspberry Pi-powered controller for high expandability
- Supports computer vision with single and 3D camera options
- Integrates with generative-AI assistants including ChatGPT, Gemini, and Claude
- Available in multiple assembly configurations, from pre-assembled kits to DIY upgrade kits
Videos
Specifications
Connectivity
| Communication | WiFi |
Mechanics
| Degrees of Freedom | 12 |
| Locomotion | Quadruped |
Physical
| Weight | 0.56 kg |
| Height | 170 mm |
Power
| Battery Life | 0.75 hours |
Sensing
| Sensors | IMU, optional LiDAR and camera |
Software
| SDK Support | Yes |
| ROS Compatible | Yes |
Similar Robots
Ff Aegis Basic Quadruped
Faraday Future
Faraday Future's FX Aegis is an embodied-AI quadruped robot for security, companionship, and enterprise tasks, offered in multiple configurations.
From $2,490
Ff Aegis Advanced Quadruped
Faraday Future
Faraday Future's embodied-AI quadruped robot, offered in several configurations from personal companion to enterprise deployment, sold through its official robotics shop.
From $2,490
Ask RoboZaps to compare Mini Pupper 2 for your workflow
Share the workflow, site constraints, budget, geography, and timeline. RoboZaps will help compare the right category, manufacturer, sourcing path, and deployment risks.
Ready to evaluate Mini Pupper 2?
Tell us about your use case and we'll help you evaluate this solution.