IARMasterclass
Course companion · 0 / 17

Field notebook · non-commercial teaching

Learn the book
by teaching it back.

IAR Masterclass is a course companion for Introduction to Autonomous Robots. Original lesson notes follow the chapter map. The book stays the book — we do not host a PDF or paste chapter source.

Cite the text

Nikolaus Correll, Bradley Hayes, Christoffer Heckman and Alessandro Roncone. Introduction to Autonomous Robots: Mechanisms, Sensors, Actuators, and Algorithms, MIT Press, 2022.

Authors permit using the work for non-commercial teaching with attribution. Posting compiled versions of the book online is forbidden. This site attributes every page and points you at the GitHub .tex and the print edition.

Three ways through

Pick a curriculum, then mark lessons done locally.

Track 01

Full two-semester

CSCI 3302 + 4302 style: mechanisms and sensing first, then computation and uncertainty. Room for labs and a project.

Week-by-week →
Track 02

One-semester mobile

Intro → locomotion → mobile kinematics → sensors → planning → error and localization → SLAM. Tight and field-ready.

Week-by-week →
Track 03

Graduate crash

A compressed path through all four parts. Assume linear algebra and probability; spend time on estimation and planning.

Week-by-week →

Chapter map

Seventeen lessons. Five study sheets.