We have structured our curriculum in terms of “modules” where each module is supported by several types of materials to reinforce it. All modules have slides.

In the “Extra Materials” column below:
are links to notes in the duckiebook
are links to exercises in the duckiebook
are links to Jupyter notebooks in the duckiebook
are links to demos to be run on the Duckiebot
are links to additional videos that have been created

Want some ideas about how to structure your class?

Université de Montréal’s Fall 2019 syllabus
ETH Zürich Fall 2019 class outline

Topic	Lecture Slides	Lecture Recordings	Extra Materials
Autonomy Basics Material
Introduction
Introduction – Duckietown	[keynote] [pdf]		From TTIC 2017 (Matt Walter)
Introduction – Autonomous Vehicles	[keynote] [pdf]		Autonomous Vehicles
Introduction – Autonomy	[keynote] [pdf]
Introduction – Robotic Systems	[keynote] [pdf]		Modern Robotic Systems From TTIC 2017 (Matt Walter)
Introduction – Systems Architectures	[keynote] [pdf]		System architecture basics From MIT 2016 (Misha Novitzky)
Introduction – Autonomy Architectures	[keynote] [pdf]		Autonomy architectures From MIT 2016 (Misha Novitzky)
Introduction – Representations	[keynote] [pdf]		Representations
Tools – Networking	[keynote] [pdf]
Tools – Version Control	[keynote] [pdf]		Git and Github
Tools – Middlewares (ROS)	[keynote] [pdf]		ROS installation and reference Taking and verifying a log From MIT 2016 (Shih-Yuan Liu)
Modeling, Kinematics, and Dynamics
Modeling	[keynote] [pdf]		Duckiebot modeling From TTIC 2017 (Matt Walter)
Calibration – Odometry	[keynote] [pdf]		Wheel calibration
Signal Processing	[keynote] [pdf]		Modern signal processing
Computer Vision
Basics	[keynote] [pdf]		Basic image operations Instagram filters OpenCV basics From TTIC 2017 (Matt Walter) Augmented Reality From TTIC 2017 (Matt Walter)
Feature Extraction	[keynote] [pdf]
Line Detection	[keynote] [pdf]		From TTIC 2017 (Matt Walter)
Place Recognition	[keynote] [pdf]		From TTIC 2017 (Matt Walter)
RANSAC	[keynote] [pdf]
Camera Calibration	[keynote] [pdf]		Camera calibration and validation
Estimation
Bayes Filter	[pptx] [pdf]		Probability basics From TTIC 2017 (Matt Walter) From MIT 2016 (John Leonard) From MIT 2016 (Liam Paull)
Particle Filter	[pptx] [pdf]		Particle Filter
Lane Filter	[pptx] [pdf]		Lane Following
Kalman Filter	[pdf]		Lane Filtering – Extended Kalman Filtering
SLAM	[keynote] [pdf]		From TTIC 2017 (Matt Walter)
Planning and Control
Control	[pptx] [pdf]		Make Way for Duckiebots Lane Following
Motion Planning	[pptx] [pdf]		Indefinite Navigation
Testing
Testing, Validation, Verification	[keynote] [pdf]		Who watches the watchmen?
Advanced Autonomy Material
Multi-Vehicle
Multi-Vehicle Coordination	[pptx] [pdf]
Fleet-level Planning	[keynote] [pdf]		Fleet planning
Introduction to Autonomous Mobility on Demand	[keynote] [pdf]
Machine Learning
Machine Learning and Deep Learning – Introduction	[Google slides]		How to install PyTorch on the Duckiebot How to install Caffe and Tensorflow on the Duckiebot How to use the Neural Compute Stick
Models vs. Data	[keynote] [pdf]
End-to-End Imitation Learning	[pdf]		Lane control with supervised learning
Sim to Real Transfer	[Google slides]
Human-Machine Interaction and Safety
Introduction to Safety	[pptx] [pdf]
Advanced Safety and Formal Methods	[pptx] [pdf]
Advanced Perception
Estimation from Motion Blur	[pptx] [pdf]