CS378 - Autonomous Vehicles in Traffic II

Instructor Name:

Piyush Khandelwal

piyushk@cs.utexas.edu

ENS32 (ENS Basement - Robotics Lab)

Office Hours: By appointment

Teaching Staff:

Jack O’Quin

jack.oquin@gmail.com

Austin Robot Technology

Jesse Vera

advisor21@gmail.com

Undergraduate Mentor

Course Overview & Learning Goals:

This course presents an opportunity for students to help decide whether they would enjoy going on to graduate school and an eventual career as a computer science researcher. In particular, students will be required to read published research papers, participate in discussions, propose and execute a solution to a challenging open-ended problem, make presentations to the class, and write about their work. The 2005 DARPA Grand Challenge proved that autonomous vehicles are currently technologically feasible. 5 cars navigated more than 100 miles in the Mojave Desert without any human control. However in that case, the cars were given pre-specified routes, and did not need to deal extensively with each other.

The obvious next challenge is getting cars to drive in traffic. Indeed DARPA hosted the 2007 Urban Challenge with exactly that focus. This course began as an attempt to participate in the 2007 Urban challenge. The software written by students of the class for an existing autonomous vehicle placed in the top 20 teams. The challenge of this particular class will be to recreate the software necessary to support the Urban Challenge behaviors, as well as support future undergraduate and graduate-level research on the vehicle.

Class Website:

http://z.cs.utexas.edu/wiki/car/traffic11.wiki

Textbook:

There is no textbook.

Prerequisites:

This course is designed explicitly to provide hands-on research experience to undergraduates of all levels who are interested in Computer Science and Robotics. It will be a demanding course requiring a good deal of self-motivation and discipline. But it will also be very rewarding.

The backgrounds and skill sets the students in this class will vary greatly. There are no specific prerequisites other than the ability to write reasonable code and the desire to work hard on a very interesting problem.

Query/Assignment Submission:

If you have a question or wish to submit an assignment, please send an email to:

cs378-fall11@utlists.utexas.edu

Jesse, Jack and I are subscribed to this list. This way either of us can answer your questions.

Class Discussion:

We have a different mailing list for class discussion and announcements:

cs378-fall11-discuss@utlists.utexas.edu

Please send me an email with the email address you wish to use for this list, and I will add you to this list.

Class Schedule and Assessments:

The content of the lectures may change depending on the projects and the direction we choose to take.

In addition to the topic, all classes will have time for project and group discussions. TBD indicates that the lecture will be determined based on the projects being done by students.

Week	Monday Date	Topic	Assignment Due
1	8/22/11	Introduction
2	8/29/11	Software System Overview + Update	Programming 2 (5%)
3	9/5/11	Tutorial: Velodyne Processing & Project Discussion I	Self: ROS/CPP Tutorials
4	9/12/11	Tutorial: Vision (OpenCV)	Programming 3 (10 %)
5	9/19/11	Tutorial: Support Vector Machines	Research Proposal (10%)
6	9/26/11	Tutorial: Evolutionary Computation
7	10/3/11	Project Update Presentations & Project Discussion II
8	10/10/11	Tutorial: Reinforcement Learning	Literary/Software Review(10%)
9	10/17/11	TBD & Discussion
10	10/24/11	TBD & Discussion	Meeting / Presentation (1%)
11	10/31/11	TBD & Discussion	Meeting / Presentation (1%)
12	11/7/11	TBD & Discussion	Meeting / Presentation (1%)
13	11/14/11	TBD & Discussion	Meeting / Presentation (1%)
14	11/21/11	TBD & Discussion	Meeting / Presentation (1%)
15	11/28/11	Presentations & Demonstrations	Demonstrations (20%)
			Final Report Due 12/2 (40%)

Final Exam Date:

No final exam.

Lab Machines:

Use any of the machines in the ENS31NR (ENS Basement)

Code of Conduct:

You are encouraged to make an attempt at the assignments yourselves first. If you are unable to come up with the solution on your own, feel free to discuss with the teaching staff or your fellow students. If you discuss with a student, please be sure to mention this fact along with the names of the people you have worked with.
Do not copy code from anywhere without citing where you got the code from. We encourage the use of code snippets available from the internet, as long as you understand them.
Typically other students will be checking in their solutions which will be visible to you. Do not under any circumstance copy their code.
No part of the text written in your reviews or assignments must be copied verbatim from a source. You may rewrite the text and use a citation.
You will have to meet with me if you do not submit an assignment. If there are circumstances which are preventing you from completing your assignment on time, please let me know in advance.