Course Number / Section:

CIS 8590 / 001

Course Title:

Perception of Intelligent Systems (Topics in CS)


Dr. Longin Jan Latecki


Wachman Hall, Room 306






Course Web Page:


Web Site for Complete  Syllabus:



Understanding of probability, statistics, linear algebra, and calculus on the undergraduate level.



David A. Forsyth and Jean Ponce . Computer Vision: A Modern Approach. Prentice Hall 2003. ISBN 0-13-085198-1


Richard O. Duda, Peter E. Hart, and David G. Stork. Pattern Classification. (2nd ed.), Wiley, ISBN: 0-471-05669-3


Sebastian Thrun , Wolfram Burgard, Dieter Fox. Probabilistic Robotics. MIT Press, 2005, ISBN 0262201623



Course Goals:

The goal is to gain understanding of problems in perception of robots and to learn mathematical and computational foundations that lead to their solutions.


Topics Covered:


The course introduces students to the underlying geometric, statistical and computational concepts of robot perception. We consider two main sources of robot perception, LIDARs (also called laser range finders) and visible light cameras. The recent progress in autonomous navigation is to large extend due to the usage and progress in LIDARs, which provide robots with precise depth perception. In addition to learning the underlying concepts of robot perception, the students will be able to estimate the perceptive abilities of robots.




Attendance Policy:



Attendance is mandatory; Attendance will be taken during lectures.