The “Self-Driving cars with Duckietown” Massive Open Online Course on edX

Posted on | by Jacopo Tani

"Self-Driving Cars with Duckietown" hands-on MOOC on edX

We are launching a massive open online course (MOOC): “Self-Driving Cars with Duckietown” on edX, and it is free to attend! 

This course is made possible thanks to the support of the Swiss Federal Institute of Technology in Zurich (ETHZ), in collaboration with the University of Montreal, the Duckietown Foundation, and the Toyota Technological Institute at Chicago.

This course combines remote and hands-on learning with real-world robots. It is offered on edX, the trusted platform for learning, and it is now open for enrollment. 

Learning activities will support the use of Jetson Nano equipped Duckiebots, powered by NVIDIA.

Enroll on edX

Learning autonomy

Participants will engage in software and hardware hands-on learning experiences, with focus on overcoming the challenges of deploying autonomous robots in the real world.

This course will explore the theory and implementation of model- and data-driven approaches for making a model self-driving car drive autonomously in an urban environment.

Pedestrian detection: there are many obstacles in Duckietown - some move and some don't. Being able to detect pedestrians (duckies) is important to guarantee safe driving.

Pedestrian detection

MOOC Factsheet

  • Name: Self-driving cars with Duckietown
  • Start: March 2021
  • Platform: edX
  • Cost: free to attend

Prerequisites

  • Basic Linux, Python, Git
  • Elements of linear algebra, probability, calculus
  • Elements of kinematics, dynamics
  • Computer with native Ubuntu installation

What you will learn

  • Computer Vision
  • Robot operations
  • Object Detection
  • Localization, planning and control
  • Reinforcement Learning
Enroll on edX

Why Self-driving cars with Duckietown?

Teaching autonomy requires a fundamentally different approach when compared to other computer science and engineering disciplines, because it is multi-disciplinary. Mastering it requires expertise in domains ranging from fundamental mathematics to practical machine-learning skills.

Robot Perception 

Robots operate in the real world, and theory and practice often do not play well together. There are many hardware platforms and software tools, each with its own strengths and weaknesses. It is not always clear what tools are worth investing time in mastering, and how these skills will generalize to different platforms. 

Duckiebot Detection: driving in Duckietown is fun but safety should always be paramount. DuckieBots can detect other vehicles and estimate their relative poses to avoid collisions.

Duckiebot Detection

Learning through challenges

Progressing through behaviors of increasing complexity, participants uncover concepts and tools that address the limitations of previous approaches. This allows to get Duckiebots to actually do things, while gradually re-iterating concepts through various technical frameworks. Simulation and real-world experiments will be performed using a Python, ROS, and Docker based software stack.

Robot Planning: as Duckietowns grow bigger, smart Duckiebots plan their path in town. Traffic signs at intersections provide landmarks to localize on the global map and determine next turns.

Robot Planning

Enroll on edX

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This course combines remote and hands-on learning with real-world robots.

It is offered on edX, the trusted platform for learning, and it is now open for enrollment.

Learning activities will support the use of NVIDIA Jetson Nano powered Duckiebots.