Logistics
Prerequisites
Students should have a basic understanding of concepts in artificial intelligence (e.g., CS 440), vision (e.g., CS 543), and preferably machine learning (e.g., CS 446). You should be engaged in or interested in research in at least one of the robot perception topics. If you are not sure whether you meet the prerequisites, talk to the instructor during office hours.
Recommended Textbooks
We will not follow a specific textbook, but here are some recommended books that you can consult:
- Sebastian Thrun, Wolfram Burgard, Dieter Fox Probabilistic Robotics.
- Richard Szeliski Computer Vision: Algorithms and Applications, 2nd ed.. Draft available online.
- Tim Barfoot State Estimation for Robotics. Available online.
- Frank Dellaert and Micheal Kaess Factor Graphs for Robot Perception. Available online.
- Ian Goodfellow, Yoshua Bengio, Aaron Courville Deep Learning. Available online.
- Kris Hauser Robotic Systems. Draft available online.
Grading
Tentative grading scheme is as follows:
- Participation (10%). Participation in in-class discussion and on Piazza.
- Paper Presentations (20%). Presenting 1-2 research topics in class. More details see here.
- Paper Reviews (20%). Writing reviews for research papers. More details see here
- Final Project (50%). More details see here
Note that this class does not have any tests or exams.
Acccommodations
To obtain disability-related academic adjustments and/or auxiliary aids, students should contact both the instructor and the Disability Resources and Educational Services (DRES) as soon as possible. You can contact DRES at 1207 S. Oak Street, Champaign, IL 61820, (217) 333-1970, or via email at disability@illinois.edu.
Academic Integrity
All work that you submit should be written solely by you and your group, and you should cite any significant sources of ideas. If any part of your project builds upon efforts before the semester (e.g., your ongoing research project), be sure to discuss with the instructor in advance. Plagiarism and other integrity violations will go on record at the university, and the minimum penalty will be a zero for the entire assignment. See the student code for more information on what constitutes an academic integrity violation.
Resources
There are also several related robotics/vision courses both within and outside Illinois, whose material is available online:
- CS598 3D Vision by Derek Hoeim.
- CS498 Mobile Robotics by Girish Chowdhary.
- CS598 Advanced Computational Topics in Robotics by Kris Hauser.
- CS598 Autonomous Vehicles by David Forsyth.
- ECE598 Robot Learning by Saurabh Gupta.