Time/Location: Wednesday 7:20-10p
Robison Hall B224
Instructor: Jana Kosecka
Office hours: 2-3pm Wednesday
Contact: Office 4444 Research II, e-mail: firstname.lastname@example.org, 3-1876
Course web page: http://www.cs.gmu.edu/~kosecka/cs685/
The course will cover 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 final course project. The grade will be based on homeworks, exam and final 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
R. Siegwart and I. Nourbakhsh: Introduction to Autonomous Mobile Robots, MIT Press, 2004
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 35 %
Exam 35% (there will be one exam, last week of October or first week of November)
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.
See the course web page for additional details.