Lecture Slides

The course teaching relies on a set of slides to support the lectures. Within the lecture, slides-based presentation will often be supported with a code example and discussion on robot design. In particular slides contain the main section with theory presentation, slides for code examples (documented in the slides or indicating that such an example takes place with other means), slides on how this lecture is applied to your project implementation, as well as references to further resources. The following "visual code" is followed:

Module 1: Introduction

Lecture 1.1: Introduction & Student Projects

Lecture 1.2: Overview of the Teaching Modules

Module 2: Propulsion Systems and Vehicle Dynamics

Lecture 2.1: Propulsion Systems for Robotics

Lecture 2.3: Micro Aerial Vehicle Dynamics

Lecture 2.2: Coordinate Systems Transformations

Lecture 2.4: W heel Robotics Kinematics

Module 3: Perception and State Estimation

Lecture 3.1: Inertial Measurement Unit

Download ROSBAG with IMU Data

Lecture 3.3: The Fundamental Matrix

Lecture 3.3, 3.4: State Estimation

Lecture 3.6: Extended Kalman Filter

Tutorials:

The Extended Kalman Filter - An interactive tutorial

Papers to study:

Lecture 3.8: Feature Extraction & Matching [2/2]

SIFT Matlab example

Further links:

Lecture 3.10: EKF-SLAM

Document for homework:

Joan Sola, "Simulataneous localization and mapping with the extended Kalman filter ‘A very quick guide... with Matlab code!’". Download

Additional resources for visual odometry. Click here

Lecture 3.2: Camera Model & Camera Calibration

Lecture 3.4: Stereo

Lecture 3.5: Kalman Filter - A Primer

Lecture 3.7: Feature Extraction & Matching [1/2]

Lecture 3.9: Structure from Motion (for estimation)

Further examples (outside of the course code repository):

Software to try

VisualSFM

Student Projects Progress Presentations

Autonomous Car Team
Fixed-Wing Team
Nuclear Monitoring Team
Autonomous Boat Team
Delivery Drone Team

Module 4: Guidance and Control

Lecture 4.1: Introduction and PD/LQR Flight Control

Laplace Transform - Khan Academy. Click here
Second Order Systems Response. Click here
The Root Locus Method. Click here
Lecture on the Linear Quadratic Regulator (MIT OCW). Click here
MATLAB Webinar: Frequency Response Estimation. Click here
MATLAB Webinar: Laplace transform. Click here
MATLAB Webinar: PID Control made easy. Click here
Understanding PID Loops - video tutorial. Click here

Lecture 4.2: Wheeled Robot Control & L1 Guidance

Paper on L1 Guidance. Click here

Module 5: Path Planning

Lecture 5.1: Introduction to Path Planning

Lecture 5.3: Exploration and Path Planning

The actual lecture will employ slight more enhanced slides. For a better overview please watch the video "Talk on Autonomous Exploration & Mapping using Aerial Robots"

Complete open source toolboxes: