Autonomous Robots Lab
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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:
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Module 1: Introduction

Lecture 1.1: Introduction & Student Projects
Lecture 1.2: Overview of the Teaching Modules
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Module 2: Propulsion Systems and Vehicle Dynamics

Lecture 2.1: Propulsion Systems for Robotics
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Lecture 2.3: Micro Aerial Vehicle Dynamics
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Lecture 2.2: Coordinate Systems Transformations
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Module 3: State Estimation

Lecture 3.1 - 3.4: State Estimation
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Lecture 3.6: Extended Kalman Filter
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Tutorials:
  • The Extended Kalman Filter - An interactive tutorial

Papers to study:
  • Team Car
  • Team Nuclear
  • Team Fixed-Wing
  • Team Boat
  • Team Drone Delivery
SIFT Matlab example
  • Code
  • Video
  • PDF
​Further links:
  • SIFT Python OpenCV tutorial
  • Scholarpedia article on SIFT




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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 3.5: Kalman Filter - A Primer
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 Further examples (outside of the course code repository):
  • OpenCV SfM for motion estimation
  • MATLAB SfM with multiple camera views
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
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  • 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
  • Paper on L1 Guidance. Click here​

Advanced Study:
  • Course on Model Predictive Control by A. Bemporad
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Module 5: Path Planning

Lecture 5.1: Introduction to Path Planning
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Lecture 5.3: Exploration and Path Planning
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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:
  • ​Structural Inspection Planner. Click here
  • Next-Best-View Planner. Click here

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Lecture 5.2: Sampling-based Motion Planning
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MIT - Technical Report on Bidirectional planning. Click here

Recap and Final Lectures

Vehicle Modeling & State Estimation Recap
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Final Course Lecture
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Focused - "Primer" Series

Kalman Filter - A Primer
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Talk on Autonomous Exploration & Mapping using Aerial Robots
Sampling-based Inspection & Exploration - A Primer
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