Lecture 8 - Localization: Particle Filter

Overview:

In this lecture we will understand particle filters in general, and especially particle filters used for Monte Carlo localization so for localizing robot in an environment given that we have a map.

Topics Covered:

• Map making with Hector SLAM

• Particle Filter Localization

• Adaptive Monte Carlo Localization (AMCL)

• Recursive Bayes Filtering used in AMCL

• Tuning Particle Filters in ROS First race of the semester!! See Race 1 for more information on how to setup and evaluate the race.

Slides:

Video:

Links to additional resources:

• F1TENTH Simulator Repo