CS 685
Intelligent Robotic Systems

Time/Location: Thursday 7:20-10:00pm,  Robison Hall B113
Instructor: Jana Kosecka
Office hours:  2-3pm Wednesday
Contact: Office 4444 Engineering Build., e-mail: kosecka@gmu.edu, 3-1876
Course web page:http://www.cs.gmu.edu/~kosecka/cs685/

The course covers basic principles of design and practice of intelligent robotics systems. We will cover algorithms for the analysis of the data obtained by vision and range sensors, basic principles of modelling kinematics and dynamics and design of basic control strategies. Notion of robot's configuration space and geometric and topological representations of the environment will be introduced and followed by overview of basic motion planning techniques. Issues of uncertainty modelling, state estimation, probabilistic inference will be introduced and examined in the context of localization and map making problems. We will study and formulate interesting robotics tasks and show how they can be accomplished by individual robot or cooperative robot teams (such as flocking, foraging as well as robotic soccer).

The topics and techniques covered are relevant for students interested in robotics, computer vision, artificial intelligence as well as modeling and programming of complex distributed embedded systems which interact with dynamically changing environments.

The course will comprise of lectures by the instructor, homeworks and presentations of the selected research publications by students. The grade will be based on homeworks and final presentation of the project. The projects will involve implementation of a systems in a mobile robot simulator and/or the actual mobile robot.


CS 580 Artificial Intelligence
optional prerequisites - Computer Vision, Analysis of Algorithms
Students taking the class should be comfortable with linear algebra, calculus and probability

Required Textbook:

R. Siegwart and I. Nourbakhsh: Autonomous Mobile Robots, Second Edition, MIT Press, 2011, http://www.mobilerobots.org

Additional Resources:

S. Thrun, W. Burghart, D. Fox: Probabilistic Robotics, http://robots.stanford.edu/probabilistic-robotics/
S. LaValle: Planning Algorithms, Cambridge Press, http://planning.cs.uiuc.edu/


Homeworks and Projects 65 %
Exam 35%  
The homeworks should be handed in on time.  Late submissions are accepted (as opposed
to no submissions) but will  incur late submission penalty.

Other recommended books:

G. Dudek and M. Jenkin: Computational Principles of Mobile Robotics. Cambridge University Press 2000
R. Murphy: Introduction to AI Robotics, MIT Press 2000
T. Dean and M. Wellman: Planning and Control. Morgan Kaufmann Publishers, 1991.

S. Russell and P. Norvig: Artificial Intelligence,  Prentice Hall, 1995

R. Arkin: Behavior-Based Robotics, MIT Press, 1998

J-C. Latombe:  Robot Motion Planning,Kluwer Academic Publishers 1991.