Distributed Intelligence in Autonomous Robotics

CS594, Section 30682
Claxton 205
Tuesdays and Thursdays 11:10 - 12:25

Spring 2003

Course home page Syllabus Reading List Handouts
Exam #1 Study Guide Exam #2 Study Guide Final Exam Study Guide

Instructor: Prof. Lynne E. Parker

TA (1/3-time): William Duncan

TA (1/2-time): Jeff Barnett

Class Mailing List: cs594-diar at cs.utk.edu

Course Description: This course explores the topic of distributed intelligence in the context of distributed, collective, and cooperative robotics and embedded systems. The focus is on key research issues in this field, such as multi-robot architectures and action selection; cooperative localization, mapping, and exploration; cooperative object transport; multi-robot motion coordination; reconfigurable robotics; and team learning. Emphasis in all of these focus areas is on the development of algorithms and software that enable a distributed team of intelligent mobile robots or embedded systems to achieve global goals in the physical world using only distributed, local information.

This course provides a theoretical background of these topic areas, along with a study of specific algorithms for multi-robot control and embedded systems. Programming assignments and exams are the primary means for evaluation, with programming taking place in a robot simulation environment. This course does not assume any advance knowledge of artificial intelligence, robotics, or embedded systems.

Prerequisites: CS302 (or equivalent), CS311 (or equivalent), and strong programming skills (primarily C or C++ in a Unix environment). Additionally, while the course is not math-intesive, a basic background is needed in the following areas of math in order to complete the programming exercises: geometry/trigonometry, matrices, probability and statistics, vector math.

Syllabus: Course syllabus (in pdf)

Required Textbook: Robot Teams: From Diversity to Polymorphism, edited by Tucker Balch and Lynne Parker, A K Peters Ltd Publisher, 2002.

Required Readings and Paper Presentations: Here is the list of required readings, schedule, and paper presentation assignments.

Evaluation: Grading will be based on homeworks, a paper presentation, and exams.

Handouts, Assignments, Lectures, etc: Click here for various handouts, lecture notes, downloads, etc.