There will be three types of assignments in this course:

Written Assignments

• Assignment 1 as PDF and gzipped postscript.
• Assignment 2

The Warm-Up Project Assignment

The goal of the warm-up project assignment is to provide you with the opportunity to familiarize yourself with robot data and (optionally) the robot hardware, to the extent necessary for the research project.

You are given data sets of robot sensor and motion data, along with a map of a building. You task will be to implement a probabilistic localization algorithm of your choice that enables you to localize the robot relative to the map. The starting position of the robot is unknown; thus, you have to solve a global localization problem.

Optionally, you are encouraged to implement your localization algorithm on a physical robot, so that we can all enjoy watching your robot localize itself in Wean Hall.

What to turn in:

• Your localization results: this could be in form of images with a path superimposed, and AVI that shows the sample set emerging, or some other graphical way to illustrate the result of the localization. Preferred: A simple image per data set (map and path). How to do this? There are very simple file formats like PPM-ASCII where you can simply dump all pixels into a file. Here is an example of the map (without path)
• A report of your findings: What you did, what worked, what didn't work, and what opportunities you see for possible projects if you were to use this data set for your class project. The report may contain the images with the results. As a rule of thumb, 4 pages might be the right length (without figures).
How you turn it in:
• Preferrably by emailing it to thrun@cs.cmu.edu. Make sure the names of all contributors are contained in the document.

Research Project

You have to propose a small research project using robot data and, optionally, physical robots. The research project has to involve an implementation using real-world data, and a statistical algorithm that should be a variant of the algorithms covered in class. To successfully pass this requirement, you have to submit a written proposal for approval by the instructor. You also have to submit a final project report, which has to address (1) the problem you solved, (2) the statistical technique including its mathematical derivation, and (3) experimental results you obtained using your approach. Ideally, the project covers interesting new ground and might be the basis for a future conference paper submission. Consult with the instructor for identifying interesting and doable research projects.

Guidelines for your final report in PPT and PDF format.