Turtlebot 3 Burger
Compact ROS-based mobile robot for education and research
$495 – $550
The TurtleBot 3 Burger is the smallest and most affordable model in the TurtleBot 3 series, designed for ROS education and SLAM research. Featuring a compact differential drive platform with OpenCR controller and Raspberry Pi, it provides a complete robotics development environment. Ideal for students, researchers, and hobbyists learning mobile robotics, computer vision, and autonomous navigation.
Released: 2017
Overview
The TurtleBot 3 Burger represents a complete reimagining of the TurtleBot platform, developed through collaboration between ROBOTIS and Open Source Robotics Foundation (OSRF). As the most compact and economical model in the TurtleBot 3 lineup, the Burger maintains full ROS compatibility while dramatically reducing size and cost compared to previous generations. Its minimalist design philosophy prioritizes accessibility for education while retaining the technical capabilities needed for serious robotics research.
Built on a differential drive platform measuring just 138mm in diameter, the Burger integrates an OpenCR embedded controller, Raspberry Pi 3 single-board computer, and a 360-degree LiDAR sensor. This combination provides a complete autonomous navigation stack in an incredibly compact footprint. The robot's modular design allows easy hardware expansion and customization, making it an ideal platform for learning fundamental robotics concepts from kinematics to SLAM.
The TurtleBot 3 Burger has become a standard platform in robotics education worldwide, adopted by universities and research institutions for teaching mobile robotics, ROS programming, and multi-robot systems. Its open-source hardware and software design enables students to understand every aspect of the system, from low-level motor control to high-level navigation algorithms.
Key Features
- 360-Degree LiDAR: LDS-01 laser distance sensor provides continuous environmental scanning for mapping and obstacle detection
- OpenCR Controller: Custom-designed open-source controller board with ARM Cortex-M7 processor for real-time motor control and sensor integration
- Full ROS Support: Native compatibility with ROS Kinetic and later versions, with extensive simulation support in Gazebo
- Modular Design: Stackable acrylic plate construction allows easy hardware modifications and sensor additions
- Dynamixel XL430 Motors: Smart actuators with position, velocity, and current feedback for precise motion control
- Open Source: Complete hardware schematics, firmware, and software packages freely available for customization
- Multi-Platform Compatibility: Supports Raspberry Pi, Intel Joule, and other single-board computers for computational flexibility
Applications
The TurtleBot 3 Burger serves as a foundational platform for robotics education in universities and research institutions worldwide. Students use it to learn SLAM algorithms, path planning, computer vision, and multi-robot coordination in both simulation and physical environments. Its affordability enables educational programs to deploy multiple units for swarm robotics experiments and collaborative navigation studies.
In research settings, the Burger platform supports algorithm development for autonomous navigation, human-robot interaction, and distributed robotic systems. Researchers leverage its open architecture to prototype new sensors and control strategies before scaling to larger platforms. The robot is also popular in robotics competitions and maker communities for developing proof-of-concept autonomous systems.
Technical Highlights
The TurtleBot 3 Burger's OpenCR controller represents a significant technical achievement, integrating a 32-bit ARM Cortex-M7 processor running at 216MHz with comprehensive sensor interfaces and motor drivers on a single board. This controller handles all real-time tasks including IMU data fusion, motor control loops, and emergency stop logic, while communicating with the Raspberry Pi via USB for high-level processing. The Dynamixel XL430-W250-T motors provide not just motion but also serve as precision sensors, reporting position, velocity, load, and temperature.
The robot's navigation stack leverages the LDS-01 LiDAR sensor, capable of 1,800 distance measurements per second with a range up to 3.5 meters, enabling real-time SLAM performance even on the modest computing power of a Raspberry Pi. The entire system is designed for power efficiency, running up to 2.5 hours on a standard 1,800mAh lithium polymer battery while performing continuous mapping and navigation tasks.
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