Duckietown

Duckietown: Learning robotics and AI like the professionals is a comprehensive learning ecosystem designed to teach vehicle autonomy, robotics, and artificial intelligence through hands-on, low-cost hardware and rich educational resources. Originating from MIT and expanded globally, Duckietown provides an end-to-end setup for instructors, students, researchers, and professional learners to build, program, and test autonomous systems in a safe, scalable environment.

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Overview

• A world-renowned education platform for robotics and AI that combines hands-on hardware (Duckiebots, Duckiedrones, and Duckietowns) with lecture materials, simulations, and open documentation.
• Aimed at making advanced autonomy education accessible beyond elite institutions, enabling learners to build real robots, follow lectures, and engage with a global community.
• Used for teaching, learning, and research, with a thriving ecosystem that bridges theory and practical application.

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Who is it for?

• Instructors and educators seeking streamlined teaching resources for robotics and AI.
• Students and self-learners aiming to gain practical skills in robot autonomy and embodied AI.
• Researchers exploring mobile robotics, embodied AI, and reproducible experimentation.
• Organizations and professionals looking for hands-on training and scalable curricula.

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How it works

1. Hardware platform: Low-cost Duckiebots (autonomous small robots) built from off-the-shelf parts, plus optional Duckiedrones and simulated environments.
2. Environment: Duckietowns—mini urban layouts with roads and signage to navigate—the real-world analogue of a smart city for autonomy testing.
3. Software & development: Open resources, tutorials, and a software stack for perception, control, and planning, designed for education and research.
4. Education ecosystem: Interactive lectures, rich documentation, simulations, and dedicated technical support to bridge theory with practice.

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Use cases and impact

• Classroom courses and hands-on labs for teaching robot autonomy and AI concepts.
• Research platforms for reproducible experiments in mobile robotics and embodied AI.
• Professional training and continuing education in autonomous systems.

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Safety and accessibility

• Emphasizes approachable, low-cost hardware to enable broad participation.
• Resources designed to be accessible to non-elite institutions while maintaining rigorous coverage of autonomy concepts.

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Core Features

• Low-cost, off-the-shelf hardware (Duckiebots) for hands-on robotics learning
• End-to-end learning ecosystem: hardware, software, lectures, simulations, and documentation
• Global community with teaching resources, classroom-ready materials, and research tools
• Scalable setup for classrooms, labs, and research groups
• Focus on autonomous vehicle autonomy, perception, control, and AI in a tangible, embodied context
• Historical lineage from MIT CSAIL-based origins to a worldwide educational initiative