This is an introductory robotics course that builds up all the pieces needed to do SLAM.

I have taught this class approximately once a year since 2019.

Lecture material

All lectures can be found here. They are largely based off of Sebastian Thrun’s “Probablistic Robotics” book.

Source code

Source code is here There are four stand-alone assignments that implement the “robot hallway” example with a Bayes’, Kalman, and Particle filter.

Additionally, there is a shell ROS 1 assignment for exploring an environment with a turtle bot.

To support development of the basic path planning there is a jupyter notebook front-end for writing A* and way point generation.