CS 545: Robotics & Intelligent Systems Spring 2011

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CS 545:Robotics & Intelligent Systems
Spring 2011
Instructor
George Dimitoglou,D.Sc.
Department of Computer Science,Hood College,Frederick,MD 21701
Office Location:HT 261
Office Hours:T-Th 12:35-13:30,17:00-18:00 other times by appointment.
E-mail:dimitoglou@hood.edu (preferred)
Telephone:301.696.3980
Lectures
Thursdays,18:20-20:50 at HT 114
Course Description
This course examines the fundamental theory and methods behind robot-building and the
deployment of intelligent systems.Topics are divided between robot architectures and cog-
nitive robotics (intelligent systems).Robot architecture topics include control paradigms,
kinematics,sensors,actuators and navigation.Cognitive robotics topics include:learning,
decision-making,coordination and cooperation.This is both a theoretical and hands-on
course.Software simulation environments and physical robots will be extensively used dur-
ing the semester as experimentation platforms to enforce student mastery of the material
Prerequisites:CS 528.
Course Objectives
By the end of the course students will:
1.Have in-depth knowledge of the fundamental principles of robot system design and
operation.
2.Be able to apply concepts of translational and rotational motion,and gears to robot
construction.
3.Be able to design and program simple autonomous robots.
4.Be able to describe,analyze and address issues related to the behavior,learning and
perception of robotic systems.
5.Be able to implement algorithms that enable the use of sensors and actuators to facil-
itate intelligent behavior,learning and perception.
6.Have an appreciation of emerging robotic applications,in elds other than computing
such as medical,transportation and space.
7.Have an appreciation of emerging robotic technologies such as micro-,and nano- robots.
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Textbook(s)
Roland Siegwart,Illah R.Nourbakhsh,Introduction to Autonomous Mobile Robots,The MIT
Press.ISBN-10:026219502X.
Additional material will be provided during the course.
Labs & Resources
Robotic kits,boards,cables,software and hardware will be provided.Access to a scientic
calculator is recommended.
Grading & Exams
Homework/Labs 50%,Mid-Term Exam 30%,Term Paper/Presentation 20%
Policies,Guidelines,Academic Honesty & Tips
 Adhering to the Academic Honesty Policy/Honor Code is student responsibility.De-
viation from the policy will not be tolerated.
 Discussions with classmates are permitted but deliverables must be your own,individ-
ual work.This means you are free (and encouraged) to discuss assignments with other
students outside of class;just don't share answers or code.
 Assignment clarication is welcome but validation (aka"pre-grading") is inappropriate.
So please,refrain from asking your instructor or lab/teaching assistant to"look over
your solutions"before submission.It is unfair to the rest of the students who are not
given any pre-submission help.
 Assignments are due in the beginning of class.No exceptions.Really.
 You are responsible for the content of reading assignments,lectures,handouts,an-
nouncements and schedule changes made in class whether or not you are present.If
you must miss a class,be sure to check Blackboard and contact your classmate(s) for
any notes.
 Attendance is expected at each class meeting.While there is no attendance grade,it
is in your own best interest to attend class,as your grade will almost certainly suer
indirectly if you choose not to attend.
 The material in the course is,inherently,cumulative.Be aware,if you fall behind,it
may be dicult to catch up.If you fall behind,ask for assistance as quickly as possible
{ I am here to help.
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Topics & Schedule (Tentative)
Date
Lecture Topics
Chapter(s)
Jan 27
Course logistics;Introduction;Locomotion
1,2
Feb 3
Mathematics Review;Kinematics
3
Feb 10
Perception-Sensors
4
Feb 17
Perception-Uncertainty
4
Feb 24
Localization-Noise,Beliefs
5
Mar 03
Localization-Noise II
Mar 10
Localization-Mapping
Mar 17
Spring Break-NO CLASS
Mar 24
Midterm Examination
Mar 31
Planning & Navigation
6
Apr 7
Planning & Navigation II
Apr 14
Robotic Simulations
Apr 21
Multi-robot coordination
Apr 28
Androids
May 5
TBA
May 13
Presentations
Grading Scale
Numeric Grade (%) Letter Grade
 93:00% A
 90:00% A-
 86:60% B+
 83:30% B
 80:00% B-
 76:60% C+
 73:30% C
 70:00% C-
 66:60% D+
 63:30% D-
 59:00% F
Reading List
There will be a number of external references (e.g.scholarly publications,magazine arti-
cles) that will be assigned during the semester.All references will be made available on
Blackboard.
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