CIS 480 :: Intelligent Robotics
Spring 2007
KUTZTOWN UNIVERSITY
KUTZTOWN, PENNSYLVANIA
COLLEGE OF LIBERAL ARTS AND SCIENCES
I. Course Description
This course deals with the theory and implementation of intelligent robotics and autonomous agents. The history, fundamental principles, elements, and algorithms of intelligent robots, both in simulation and in the real world, will be examined. Fundamental issues and debates regarding design and implementation and their roots in knowledge representation and theoretical computer science will be investigated. Using the knowledge gained, actual designs will be implemented.
3 s.h./3 c.h.
Prerequisites:
CSC 126 Discrete Math for Computer Science II; CSC 237 Data Structures
Intelligent robotics is one of the most active and exciting areas of research in computer science. This course provides students with an opportunity to learn the fundamentals of adding intelligence to robotics systems. They will learn the basic framework of real time sensor processing coupled with actuator control and apply the techniques studied to actual robotic systems.
III. Course Objectives
Upon satisfactory completion of this course the student will:
Understand the history of intelligent robotics and the theoretical basis for recent advances.
Understand the fundamental concepts of behavior-based robotic control systems.
Be able to write programs for intelligent control systems.
Implement an intelligent control system.
IV. Course Assessment
The course assessment will consists of homework, quizzes, tests, projects, a major project, a class presentation of that project, and the final exam.
V. Course Outline
a. History of intelligent robotics
i. The hierarchical paradigm
ii. The reactive paradigm
b. Subsumption Architecture
i. Vertical decomposition
ii. Horizontal decomposition
iii. Subsumption
c. Behavior-based control
i. Early Ethology – Lorenz & Tinbergen
ii. Recent studies in animal behavior
iii. Swarm intelligence
iv. Behaviors as plan elements
d. Knowledge representation
i. The knowledge representation debate
ii. Logic-based knowledge representation
iii. Tractability issues
iv. Localization
v. Mapping
1. Metric maps
2. Topological maps
vi. Navigation
1. Marker-based navigation
2. Cue-based navigation
3. Coastal navigation
e. Sensor Fusion
i. Basic sensor types
ii. Sensor limitations
iii. Arbitration algorithms
iv. Real time knowledge updating
f. Reasoning and Planning
i. STRIPS as a planning system
ii. Logic-based planning
iii. Planning for continuous action
iv. Planning for repetitive action
g. Actuation
i. Coupling plans to effectors
ii. Robot simulation software
iii. Basic real world actuation
1. Perimeter detection
2. Collision avoidance
3. Line following
iv. Higher level real world functions
1. Mapping an environment
2. Point to point navigation
3. Implementing a plan
VI. Instructional Resources
Bekey, G. A. (2005) Autonomous Robots : From Biological Inspiration to Implementation and Control. Cambridge, MA: MIT Press.
Bergin, J., Stehlik, M., Roberts, J., and Pattis, R.E. (1996) Karel++: A Gentle Introduction to the Art of Object-Oriented Programming. Hobeken, NJ: Wiley.
Braunl, T. (2004) Embedded Robotics : Mobile Robot Design and Applications with Embedded Systems. New York, NY: Springer.
Choset, H., Lynch, K.M., Hutchinson, S., Kantor, G., Burgard W., Kavrati, L. and Thrun, S. (2005) Principles of Robot Motion : Theory, Algorithms, and Implementations. Cambridge, MA: MIT Press.
Cook, David. (2004) Intermediate Robot Building. Berkeley, CA: Apress.
Dudek, G. and Jenkin, M. (2000) Computational Principles of Mobile Robotics.
Holland, J. M. (2003) Designing Autonomous Mobile Robots : Inside the Mind of an Intelligent Machine. Oxford, England: Newnes.
Jones, J. and Roth, D. (2003) Robot Programming : A Practical Guide to Behavior-Based Robotics. New York, NY: McGraw-Hill.
Latombe, J-C. (1990) Robot Motion Planning. New York, NY: Springer.
Maes, P. (ed.) (1991) Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back. Cambridge, MA: MIT Press.
McComb Gordon (2002) Robot Builder's Sourcebook. New York, NY: McGraw-Hill.
Predko, M. (2002) Programming Robot Controllers. New York, NY: McGraw-Hill.
Siegward, R. and Nourbakshsh, I.R. (2004) Introduction to Autonomous Mobile Robots. Cambridge, MA: MIT Press.
Thrun, S., Burgard, W., and Fox, D. (2005) Probabilistic Robotics. Cambridge, MA: MIT Press.
Williams, K. (2002) Insectronics : Build Your Own Walking Robot. New York, NY: McGraw-Hill.
Williams, K. (2003) Amphibionics : Build Your Own Biologically Inspired Reptilian Robot. New York, NY: McGraw-Hill.
Wise, E. (1999) Applied Robotics. New York, NY: Prompt.
Wise, E. (2002) Applied Robotics II. New York, NY: Prompt.