Guide for Researchers

Research using Duckietown


We designed Duckietown to be a modular, inexpensive research platform for studying autonomy in complex systems. Think of it as an “experimental simulator”.

Value proposition

We provide a baseline implementation for you to be able to rapidly and easily test your algorithms on real physical hardware.

  • Convenience: You can only change the part that interests you and use the rest of the baselines to have a fully functional system.
  • Reproducibility: Your research has a high impact since it uses a standard platform that others can easily replicate. For maximum impact, compete in an AI Driving Olympics (AI-DO).

Tools for research

  • Imitation learning template
  • Reinforcement learning template
  • Database of Duckiebot driving logs
  • Duckiebot driving simulator
  • Modularized code (ROS baseline template)
  • Low cost, standardized robots and smart city environment
  • An international embodied AI competition: the Artificial Intelligence Driving Olympics (AI-DO)

Next steps