OpenAMRobot is an open-source Physical AI development platform that enables startups, researchers, universities, and domain experts to build, train, validate, and deploy robotic solutions without rebuilding the entire robotics stack.
We believe the future of robotics will not be built by robotics engineers alone.
It will be built by:
- Manufacturing experts
- Logistics specialists
- Healthcare professionals
- Researchers
- Entrepreneurs
- Innovators
People who understand problems and want to automate them.
OpenAMRobot provides the infrastructure that transforms domain expertise into robotic capabilities.
Building a modern Physical AI system requires expertise across:
- Robotics
- AI
- Perception
- Teleoperation
- Data collection
- Simulation
- Training infrastructure
- Deployment
Most teams spend months assembling infrastructure before they can validate a single robotic application.
OpenAMRobot reduces this complexity by providing an integrated development platform for:
- Mobile manipulation
- Teleoperation
- Data collection
- Imitation learning
- Embodied AI research
- Human-in-the-loop training
- Robot skill development
- Real-world deployment
The fastest path from business problem to robotic solution.
Software 1.0
Write code
Software 2.0
Train models
Software 3.0
Describe outcomes
Robotics 1.0
Program robots
Robotics 2.0
Train robots
Robotics 3.0
Teach robots by demonstration
OpenAMRobot is building the platform for Robotics 3.0.
Domain Expert
↓
Demonstrates Task
↓
OpenAMRobot Collects Data
↓
AI Learns Skill
↓
Robot Executes Task
OpenAMRobot connects hardware, software, AI, and deployment into a single workflow.
- Autonomous mobile robot platform
- Dual-arm mobile manipulation
- Adjustable lift systems
- Modular sensor architecture
- Open hardware designs
- ROS 2 ecosystem
- Navigation and autodocking
- Teleoperation interfaces
- Simulation environments
- Embedded firmware
- Demonstration data collection
- ROS bag recording
- Dataset generation
- Imitation learning pipelines
- Foundation model integration
- Policy training workflows
- Deployment infrastructure
- Robotics startups
- Universities
- Research laboratories
- Corporate innovation teams
- Venture builders
- Manufacturing
- Logistics
- Healthcare
- Agriculture
- Service robotics
Our users build robots.
Their users deploy robots.
Physical AI is creating a new generation of robots that learn from demonstration, adapt to new tasks, and solve real-world problems.
Yet building a trainable robot still requires expertise across hardware, software, AI, teleoperation, data collection, training pipelines, simulation, deployment, and hardware integration.
OpenAMRobot reduces this complexity by providing an integrated platform that enables anyone with domain expertise to create robotic solutions.
The real value is not the robot itself.
The real value is how efficiently a robotic system can solve a business problem.
The next generation of creators will not just build software.
They will build robots.
OpenAMRobot enables anyone with domain expertise to create robotic solutions without becoming a robotics engineer.
The Programming Language of Robotics is Domain Expertise.
Important
OpenAMRobot is transitioning from a monolithic repository structure into a modular robotics ecosystem.
| Repository | Purpose |
|---|---|
openamr-platform-sw |
ROS 2 software, simulation, navigation, docking, drivers, perception, and robot bringup |
openamr-platform-fw |
Embedded firmware, low-level microcontroller systems, motor interfaces, and hardware communication |
openamr-platform-hw |
CAD, chassis, electrical systems, BOMs, manufacturing files, and mechatronics |
openamrobot-interfaces |
ROS 2 messages, services, actions, shared schemas, and interface contracts |
openamrobot-comm |
APIs, middleware, telemetry, transport protocols, interoperability, and fleet communication |
openamrobot-ui |
Operator interfaces, dashboards, visualization tools, and user-facing applications |
openamrobot-docs |
Architecture, onboarding, tutorials, safety, compatibility matrices, and contributor documentation |
Planned future ecosystem areas include:
- humanoid and dual-arm robotics
- fleet management
- cloud robotics
- remote operation
- AI-assisted autonomy
- industrial integrations
- educational platforms
This repository remains as a historical/community repository and migration hub while development transitions into the modular architecture.
SMEs across multiple industries can significantly enhance their operations through the adoption of Collaborative Dual-Arm Autonomous Mobile Robots. In warehouses and distribution centers, such robots streamline goods movement and order fulfillment by combining autonomous navigation with dexterous dual-arm manipulation, enabling advanced G2P workflows and reducing manual handling. In manufacturing environments, they improve production efficiency by autonomously transporting materials between workstations and performing basic assembly or handling tasks. For last-mile logistics, including courier, express, parcel (CEP), and grocery delivery, dual-arm AMRs further boost operational efficiency by automating repetitive loading, sorting, and delivery operations.
Our project empowers you to build your own AMR using open-source designs and accessible manufacturing methods. This guide provides detailed drawings, 3D models, Bill of Materials (BOM), hardware architecture, navigation software, and user interface packages. Utilize straightforward manufacturing technologies to learn and integrate advanced automation seamlessly into your business operations.
Support open-source robotics, ROS2 development, AI robotics education, Dual-arm mobile robot research.
| Tier | Price | Link |
|---|---|---|
| Community | €19/month | Subscribe |
| Builder | €79/month | Subscribe |
| Pro Support | €299/month | Subscribe |
| Startup Support | €750/month | Subscribe |
| Lab Support | €1,500/month | Subscribe |
GitHub Sponsors: https://github.com/sponsors/openAMRobot
Every contribution, big or small, helps us grow. Thank you for your support!
- Navigation: LIDAR/SLAM
- Drive type: Differential drive
- Weight: ~60 kg
- Camera view: 120 degrees
- Speed: 1500-2000 mm/s (unloaded), 1200-1500 mm/s (loaded)
- Positioning accuracy: ±20 mm
- Dimensions: 600x800 mm
- Battery: 24/48 V, 48-56 Ah, 8 hours life
- Communication: Wi-Fi (2.4/5 GHz)
- Load capacity: up to 150 kg
- Operating temperature: -10°C to +50°C
- Charging: Contact/wireless
Our design is optimized for manufacturability, requiring only basic technologies such as laser cutting, bending, turning (optional), and 3D printing (optional). Using mostly 2mm thick metal sheets, the design is robust yet simple to produce, allowing one person to build the robot in just one day if every part is ready.
Here is how the chassis design looks like:
- Downloadable resources:
- Production drawings, 3D models, STEP, and DXF files
- Specification sheet, including all parts and assemblies, sensors, and fasteners
- Fabrication process:
- Discuss the drawings with a contractor for cutting and bending metal.
- Assemble the chassis following the provided sequence.
- Assembly steps:
- The chassis design and the recommended assembly sequence are illustrated in the provided images.
- Detailed steps for assembling the drive wheels and other components are included.
-
Electronics block diagram:
- Main single-board computer (SBC)
- Safety sensors (US, IR, bumper), RPI camera, and LiDAR
- Controller Teensy board and firmware
- BLDC motors, drivers, and encoders
- Batteries, BMS, and wireless charger
- On/Off switch and Emergency button
-
Main components:
- Raspberry Pi 5: For main computing tasks.
- LIDAR: For mapping and navigation.
- Sensors: For obstacle detection and safety.
- BLDC motors and drivers: For movement control.
- Battery system: For power supply.
- Wireless charging: For autonomous charging.
-
Software setup:
- Linorobot: Open-source software package for navigation and control.
- UI: Built with Flask and Java for user interaction.
To get all files you should do the next commands:
git clone https://github.com/openAMRobot/OpenAMR.git
cd openAMR
git submodule update --init --recursive
The whole tutorial about software installation is sectioned into different topics. Click here here to get started.
Here’s how the hardware architecture of the robot looks like:
This versatile design can be adapted to create different types of robots for various logistics tasks. It can also be modified to carry tools or a roller cage, increasing its usefulness in various scenarios. Examples of practical applications include:
- Automating goods movement in warehouses
- Enhancing production workflows in manufacturing plants
- Improving operational efficiency in small farms and greenhouses
This project provides a low-cost DIY autonomous mobile robot suitable for industrial automation or warehouse logistics. By open-sourcing our technology, we offer SMEs an opportunity to leverage advanced robotics without the high costs associated with research and development.
For any questions, please refer to the documentation or the open-source project Linorobot. Basic knowledge of electronics, software, and mechanics is required.
Effective community management and moderation are essential to maintain a healthy and productive environment for collaboration. Our project welcomes contributions and feedback from the community to improve and evolve.
We are working on rules and suggestions to manage contributions and interactions within our repository. They include features like issue templates, pull request templates, and guidelines for contributors and will be published soon.
You can access the community profile of this repository by clicking on the "Community" tab on the repository's main page. This section provides all the necessary information and resources for contributors.
We are preparing standards for behavior within the community. Information about Code of Conduct will be added soon to a CODE_OF_CONDUCT.md file in the root directory. Where we will outline the expected behavior and the process for reporting violations.
We are working on information about the workflow, coding standards, and submission process to help contributors understand the best practices and expectations. This information will be outlined in a CONTRIBUTING.md file.
This project is licensed under the MIT License. For more info please check LICENSE LICENSE file in the root directory.
Help us bring innovative AI & robotics project to the next level!
Support open-source robotics, ROS2 development, AI robotics education, Dual-arm mobile robot research.
| Tier | Price | Link |
|---|---|---|
| Community | €19/month | Subscribe |
| Builder | €79/month | Subscribe |
| Pro Support | €299/month | Subscribe |
| Startup Support | €750/month | Subscribe |
| Lab Support | €1,500/month | Subscribe |
GitHub Sponsors: https://github.com/sponsors/openAMRobot
Every contribution, big or small, helps us grow. Thank you for your support!
Every contribution, big or small, helps us grow. Thank you for your support!