It's a "grand tour" of vehicle autonomy with hands-on activities (in simulation and on real hardware) tailored to the autonomous vehicles application.
It brings together from kinematics modeling and PID control to machine learning, passing through computer vision, planning and Bayesian filtering. The objective is having a model self-driving car driving safely while avoiding pedestrians.. in your living room.
thank you! We are very excited to bring our vision of learning autonomy to the world, and it's great to see this interest.
The MOOC Duckiebot is the first of the family to be powered by NVIDIA. Our other Duckiebots as well as the Duckiedrone are Raspberry Pi based.
This said: as for peripherals you definitely want to get a compatible wifi dongle and provide cooling to the Jetson, e.g. with a fan. Add-ons (to the robot): we went for a modular, plug-and-play sensor suite and more features to enhance the hands-on experience (i.e., LEDs, screen).
Unfortunately the shipping costs are a pain, we hear you, and custom duties are a thing to consider.
We are actively working to provide a much more effective shipping solution to gradually more countries, and India is high on our list. You can sign up to our mailing list or follow us on Facebook, Linkedin, Twitter or Instagram to stay tuned with updates! (https://www.duckietown.org/contact)
The more we iterate the Duckiebot design the more we tend towards customization; to better engineer it, reduce costs, and provide more engaging learning experiences to a broader audience.
The Founder's edition Duckiebot is designed to host several sensors (IMU, ToF, Camera, wheel encoders), has 4 LEDs, a screen, a special duckie-battery and a PCB that makes it easy to manage everything.
https://www.edx.org/course/self-driving-cars-with-duckietown
It's a "grand tour" of vehicle autonomy with hands-on activities (in simulation and on real hardware) tailored to the autonomous vehicles application.
It brings together from kinematics modeling and PID control to machine learning, passing through computer vision, planning and Bayesian filtering. The objective is having a model self-driving car driving safely while avoiding pedestrians.. in your living room.
Might be of interest to some here.
(Disclaimer: I'm one of the instructors)