This page outlines the content for a short course on sensors that use light to approximate distance, commonly known as Light Detection and Ranging or LIDAR.
image from http://www.alfoldron.hu/
This course is designed for engineering students with an interest in robotics. Recent developments in autonomous driving technologies have driven down the cost and size of LIDAR sensors, even while their performance has drastically improved. LIDAR data can be used for navigation and object identification in a wide range of autonomous applications. The course will cover everything from the theory of operation behind LIDAR to reading data from a LIDAR sensor.
I assume the reader has the following background and interests:
The rest of the course is organized as follows:
Theory of Operation: Time-of-Flight Laser Rangefinder
HW: Light Practice Problems
Theory of Operation: 2D LIDAR
Intro to Hokuyo/LMS SICK
LIDAR Data Structures
HW: Interpret instances of digital output from LIDAR sensor
Point Clouds, Reference Points, Control Points, Mesh
HW: Import a point cloud, Mesh, Export as .STL
Theory of Operation: 3D LIDAR
Frames of Reference, Quaternions
HW: Rotation practice problems
Basic ROS Commands
Nodes, Topics, Publishers, Subscribers
HW: Write out step-by-step instructions for reading data from a Hokuyo and visualizing in rviz
The final exam consists of multiple choice questions on the above topics and a practical portion in which students demonstrate how to connect to and visualize data from a LIDAR sensor.