一、課程說明(Course Description)
This course introduces students to localization, mapping, planning and control
of mobile robots and self-driving cars from the probabilistic perspective.
Topics include recursive state estimation, Gaussian filters, non-parametric
filters, robot motion and perception, localization, mapping, SLAM (simultaneous
localization and mapping), obstacle avoidance, navigation, and so on.
Laboratory assignments provide hands-on experience with servo drives, sensors,
interface circuitry, and microprocessor-based real-time control, Robot
Operating
System (ROS) programming. Students will build a working mobile robot system in a
group-based term project.
二、指定用書(Text Books)
1. Lecture Notes.
2. Thrun, S., W. Burgard, and D. Fox. "Probability Robotics." MIT press (2005).
三、參考書籍(References)
1. R. Siegwart, I. R. Nourbakhsh, and D. Scaramuzza, Introduction to
Autonomous Mobile Robots, 2nd Edition, MIT Press, 2011.
2. B. Siciliano, L. Sciavicco, L. Villani, and G. Oriolo, Robotics: Modeling,
Planning and Control, Springer, 2010.
四、教學方式(Teaching Method)
Lectures using chalkboard and PowerPoint presentations.
五、教學進度(Syllabus)
1. Introduction
2. Actuators, Drive Systems
3. Mobile Robot Basics
4. Navigation
5. Recursive State Estimation
6. Gaussian and Nonparametric Filters
7. Motion
8. Perception
9. Localization
10. Mapping
六、成績考核(Evaluation)
Homework/Lab assignments 40%, Midterm Report/Presentation 30%, Term Project
30%
七、可連結之網頁位址
http://elearn.nthu.edu.tw