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EE/CPE 440A  Fall 2005

Introduction to Autonomous Mobile Robots

Instructor: Professor Yan Meng 
Office Location: Burchard 215
Office Phone: (201) 216-5496
Office Hours: TBD
Lecture Time: TBD
Lecture Location:  TBD

Pre-requisite:

While not required, a familiarity with matrix algebra, calculus, and probability theory will be much helpful. 

Textbook:

Roland Siegwart and Ilah Nourbakhsh, Introduction to Autonomous Mobile Robots, MIT Press, April 2004, ISBN# 0-262-19502-X.   Textbook website

Some reading materials will be distributed in class. 

Recommended readings:

  1. Robin Murphy, An Introduction to AI Robotics, MIT Press, November 2000. ISBN 0-262-13383-0.
  2. Thomas Braunl, Embedded Robotics: Mobile Robot Design and Applications with Embedded Systems, Springer-Verlag Berlin Heidelberg New York, ISBN# 3-540-03436-6.
  3. David A. Forsyth and Jean Ponce, Computer Vision: A Modern Approach, Prentice Hall, 2003, ISBN# 0-13-085198-1.
  4. David Kortenkamp, R. Peter Bonasso, and Robin Murphy, Artificial Intelligence and Mobile Robots Case Studies of Successful Robot Systems,  MIT Press, March 1998, ISBN 0-262-61137-6.
  5. H. R. Everett, Sensors for Mobile Robots: Theory and Applications,  A.K. Peters Ltd,  1995, ISBN 1-56881-048-2.

Course Descriptions:

This course will offer the students an overview of the technology of intelligent robot systems -- the mechanisms that allow an intelligent robot to move through a real world environment to perform its tasks - including locomotion, sensing, localization, and motion planning.  Since the design of any successful intelligent robot involves the integration of many different disciplines, among them kinematics, signal analysis, information theory, artificial intelligence, and probability theory.  In order to reflect this, the course will discusses all facets of intelligent robotic system including hardware design, wheel design, kinematics analysis, sensors and perception, localization, mapping, and robot control architectures.

Course Schedule:

 Lecture 1  Introduction: History of mobile robots
 Lecture 2  Mobile Robot Locomotion
 Lecture 3  Mobile Robot Kinematics and Motion Control 
 Lecture 4  Mobile Robot Perception: sensors
 Lecture 5  Camera model and camera calibration
 Lecture 6  Computer Vision: multiple view geometry(1)
 Lecture 7  Computer Vision: multiple view geometry(2)
 Lecture 8  Mobile Robot Localization (1)
 Lecture 9  Mobile Robot Localization (2)
 Lecture 10  Robot Map Building
 Lecture 11  Mobile Robot Path Planning and Navigation (1)
 Lecture 12  Mobile Robot Path Planning and Navigation (2)
 Lecture 13  Artificial Intelligent Robotics I
 Lecture 14  Artificial Intelligent Robotics II

 
Grading:
 

HW and quiz 20%

Midterm and presentation 30%

Project assignments 20%

Final 30%