Minh Hoai Nguyen

This hands-on course introduces the basic concepts in robotics, focusing on mobile robots and illustrations of current state of the art research and applications. Course information will be tied to lab experiments; students will work in teams to build and test mobile robots. The basic concepts that will be discussed include coordinate transformations, visual perception, sensors, path planning, kinematics, feedback and feedforward control. These topics will be exemplified with several robotics platforms including TurtleBot, Parrot AR Drone, Lego Mindstorm, and Intel Galileo. The last part of the course will focus on applying the knowledge from the initial lectures to the key approaches to mobile robot control (reactive, behavior-based, and hybrid), and briefly discuss robot learning and multi-robot systems. In the lab, robot kits will be used in weekly exercises illustrating lecture material; the last month of the lab will be spent in applying the learned material to a final project, in which the students will design and build a robot for a final competition. This course is intended for graduate students with interests in robotics, perception, and AI.

• Probabilistic Robotics. S, Thrun et al. MIT Press 2005.

• Introduction to robotics. J.J. Craig. Prentice Hall, 3ed, 2003.

• Week 1. Introduction, a brief history of robotics

• Week 2. Sensing and sensors

• Week 3. Quiz 1. Visual processing, computer vision techniques

• Week 4. Probabilistic robotics

• Week 5. Localization and mapping

• Week 6. Quiz 2. Mobile platforms

• Week 7. Path planning

• Week 8. Review and midterm

• Week 9. Effectors and Actuators

• Week 10. Manipulation. Direct Kinematics

• Week 11. Quiz 3. Dynamics. Inverse Kinemetics

• Week 12. Feedback control

• Week 13. Behavior-based control

• Week 14. Group robotics

• Week 15. Final projects

CSE525