Perception of Intelligent Systems (Topics in CS)

Longin Jan Latecki

Computer and Information Sciences Dept.

 

New Graduate Seminar CIS 8590 in Fall 2007, Monday 4:40 - 7:10 PM in TL403B

 

Schedule         References

 

The goal is to introduce 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.

 

We will also learn what made Stanley (the autonomous car from Stanford Univ.) to win the second DARPA Grand Challenge, held on October 8, 2005. It drove autonomously a 212.4 km (132 mile) course in just under 7 hours and won a US$2M prize.

 

 

 

Finally we will follow the third DARPA Grand Challenge competition that will take place on November 3, 2007. It will be an urban challenge of autonomous ground vehicles in a mock urban area.

Instructor

Class

  • Meets: Monday 4:40-7:10 PM in TL 403B

Exams, Project and Grading

  • Homework: 10%
  • Class participation (including short quizzes): 20%
  • Projects: 35%
  • Presentations: 35%

Final: The final exam will be given to those students who did not complete their projects and did not give their presentations, in which case it will account for 70% of the grade.

Homework: Homework due dates will be announced. Late homework will result in a penalty. 

Class attendance: Class attendance is expected, and may be recorded from time to time. Absences for legitimate professional activities and illnesses are acceptable only if prior notice is given to the instructor by e-mail. Scheduling conflicts with your work, extra-curricular activities, or any other such activities is not a valid excuse. Although attendance is not a specific part of the course evaluation it has a direct effect on class participation. If you are not in class you cannot participate. Class participation means that you attend class regularly and have completed your assigned readings. It means that you ask relevant questions and make informed comments in class. Class participation will contribute to the final grade.

Quizzes: Each week there will be one 20 - 25 minute miniquiz based on the current homework assignment for the week. There will be no make up quizzes; however, you will be allowed to drop your lowest three quiz grades. You may bring one letter size page filled with your own notes to each miniquiz.

Exams: If you miss the final and do not make alternative arrangements before grades are turned in you will be graded F.

Honor Code

  • All work submitted for credit must be your own.
  • You may discuss the homework problems with your classmates, the teaching assistant, and the instructor. You must acknowledge the people with whom you discussed your work, and you must write up your own solutions and code. Any written sources (apart from the text) used must also be acknowledged; however, you may not consult any solutions from previous years' assignments whether they are student or faculty generated.
  • Plagiarism will be handled with severe measures.
  • Please ask if you have any questions about the Honor Code. Violations of the honor code will be treated seriously. Please check the Temple University policy on Plagiarism and Academic Cheating.

Disabilities

I encourage students with disabilities, including "invisible" disabilities such as chronic diseases and learning disabilities, to discuss with us any appropriate accommodations that we might make on their behalf. Student must provide me with a note from the office of Disability Resources and Services at in 100 Ritter Annex, 215-204-1280, regarding their disability.

Text

The course will be based on research articles and on parts of the following text books:


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

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

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