Lecture 9 (Optional) - Scan Matching I & II

Overview:

This lecture is part one of three localization lectures. We’ll learn how to determine the state (position and orietnation) of a robot with respect to its environment. The RoboRacer vehicle uses range measurements from the lidar to localize. The iterative closest point algorithm and fast correspondence search are explained. At the end of the lecture, there is an overview of Lab 5.

Topics Covered:

• Localization/SLAM

• Scan Matching

• Iterative Closest Point

• Fast Correspondence Search

Associated Assignment:

• Lab 5 (Optional): Scan Matching

Slides:

Video:

Links to additional resources:

• An ICP variant using a point-to-line metric

• Convex Optimization course