Tentative Class Schedule


Week Date Topic Lecture Slides Instructional Exercises Additional Notes
1 Sept 5 Overview
  • Introduction to Duckietown [key][pdf]
  • Duckietown class content overview [key][pdf]
  • Montreal Class Logistics [key][pdf]
2 Sept 10 Introduction
  • Autonomous vehicles [key][pdf]
Duckiebot Assembly
2 Sept 12 Tools ROS / Docker
3 Sept 17 Modeling Differential Drive Kinematics Project Topics Announced [key][pdf][form]
3 Sept 19 Computer Vision Basics Intro to CV
4 Sept 24 Advanced Computer Vision
4 Sept 26 Deep Learning for Perception Deep learning 101 [Google slides] Duckietown Intro to Neural Nets with PyTorch ex. AC assigned - assembly + calibration Guest lecture by Manfred Diaz and Florian Golemo
5 Oct 1 Lecture canceled because of election
5 Oct 3 Estimation Basics ex. AC due
6 Oct 10 Kalman Filter Adventures in Kalman Filtering [pdf] Guest Lecture by James Forbes
7 Oct 15 SLAM Intro to SLAM [key] [pdf] ex. AIDO1 begins
7 Oct 17 Planning Motion Planning [pptx] [pdf] Project Consultation
Week break
8 Oct 29 Control Basics Control [ppt] [pdf]
8 Oct 31 Project Consultation #2
9 Nov 5 Online Imitation Learning Online imiation learning [pdf] Guest Lecture by Manfred Diaz
9 Nov 7 Trust and Human Machine Interaction Guest Lecture by Anqi Xu (Element AI)
10 Nov 12 Testing Testing [key] [pdf]
10 Nov 14 Simulation and Sim-to-Real Sim 2 Real Transfer [gslides] AIDO1 exercise due Guest lecture by Florian Golemo
11 Nov 19 Practical Reinforcement Learning for Autonomous Vehicles The Duckietown Simulator, Sim-to-real Transfer & Some Practical Advice [gslides] Guest lecture by Maxime Chevalier-Boisvert
11 Nov 21 Class presentations 4 & 6
12 Nov 26 Class presentations 5 & 3
12 Nov 28 Class presentations 1 & 2 ex. AIDO2 begins
13 Dec 3 Class optional - A2333
13 Dec 5 Class optional - A2333
14 Dec 23 All final deliverables due for class include ex. AIDO2 and the projects