Robotic Vision 2018

Course Description:

This course aims at training students to participate world-class competition, and we will target the RobotX Competition (https://www.robotx.org/) in 2018. This course will cover the fundamental and advanced domains in vision for mobility tasks, including the challenges combining object recognition, pose estimation, motion planning, and SLAM. We will systematically study each components from previous winning teams in 2014 and 2016, as well as cutting-edge methods that may better improve the performance. Students will form teams to develop term projects, and we encourage in-class discussions and presentation skills with a white board for class participations. This course is a "learning-by-doing," and include in-class lab/tutorial in each teaching module. We will use "Duckietown" (an open course "MIT 2.166 Autonomous Vehicles) as platform, and focus advanced topics using Gazebo, 3D perception, and deep learning.

Class Organization:

• Task-oriented: We aim at the RobotX competition in 2018.
• Learning by Doing: We have lecture and lab sections, and include hand-on tutorial/lab materials each week.
• In-class Discussion: We encourage discussions and presentation skills using a whiteboard each team for class participation. We also wish to train students' presentation skills.
• Project-based learning: each team will work on a term project related to RobotX Competition.

Textbooks and Resources:

• 1. Computer Vision: Algorithms and Applications, Richard Szeliski, Springer, 2010.
• 2. Robotics, Vision, and Control, Peter Croke, Springer, 2011.
• 3. Introduction to Autonomous Robots, Nikolaus Correll, 2015.
• 4. RobotX Competition (Website Link)

Assignments:

We have in-class tutorial/lab each week, and the lab materials typically include 3 specific tasks (programming / algorithm / system work). and students are expected to finish the lab materials during the class.

Exams:

There will be no midterm/final exams.

Evaluations:

• In-Class Lab/Tutorials (40%)
• Midterm Project Proposal (20%)
• Final Presentation and Term Paper/Report (40%)