Information Technology at Notre Dame
Intelligent Systems
Information Technology has long since grown from simple rote processing of
reams of data
at extremely high speeds. Today, observations are converted from raw measurements
into "information" about the environment, processed "as information," and then used
to effect how a system interacts with the outside world to achieve some
"goal." Such terms as "artificial intelligence," "expert systems," "fuzzy logic,"
"actors", and "neural nets" are common in the technology, but a bit esoteric
in terms of their perceived applicability. ND has been making great strides, as indicated
below.
CCPWNS
The Computer Controlled Power Wheelchair Navigation System
(CCPWNS) project Headed by Prof.
Steven Skaar in the AME department
provides navigational autonomy for disabled users who, due to a
mix of disabilities, which may include blindness, cannot control their own
power wheelchairs within their home or workplace setting. Based upon
estimation algorithms that apply a mix of wheel odometry and visual
detection of prepositioned wall cues, the system constructs a feasible
connection between the current chair position and a user-input destination
by piecing together previously taught path segments. The performance is
precise and robust. Ultrasound is used to avoid collision with new
obstacles (whereupon the current path is executed in reverse); and a
voice-based user interface is demonstrated.
The working chair was displayed at the Indiana State Fair in August of
2002, and it was also demonstrated in the spring of 2001 at a Dept. of
Veterans Affairs Forum at the Hines VA Hospital, Hines, IL, where the
poster discussing the project won first place.
Thermal Engineering
Prof. Mihir Sen of
AME has applied artificial neural networks and fuzzy
logic modeling to
problems in the thermal engineering area. Specific examples include the
performance prediction of heat exchangers and flow wakes as well as
dynamic control of temperature.
Artificial Intelligence and Robotics Laboratory
The Artificial
Intelligence and Robotics Laboratory, founded
by Professor
Matthias Scheutz,
continues a tradition of research in artificial intelligence that
started at Notre Dame as early as 1962. (under the guidance of Professor
Kenneth Sayre, who directed a group of researchers under NSF sponsorship
at the "Philosophic Institute").
While the efforts then were mainly concentrated on pattern recognition,
the current research focuses on the design of software architectures for simulated and robotic agents. A thorough
analysis of different types of agents, the architectures they require, and
their capabilities is the prerequisite for understanding their
potential applications in
application domains as diverse as personal assistants,
believable characters for
the entertainment industry, E-commerce, automated knowledge processing, and many
others.
Affective Agent Architectures. Work in
this area involves conceptual analyses of affect concepts in terms of functional
components of agent architectures and the kinds of processes they can bring about
as well as comparisons of different kinds of agent architectures for
affective agents, their components and functional capacities.
Complex Complete Robotic Agents. The focus
here lies on designing architectures for complete robotic agents (such as
"robotic waiters" or "soccer playing robots").
Architectures
are implemented and tested on various robots (e.g., the ActivMedia
PeopleBot
and
Pioneer 2DXE
robots) using the
AGES
agent architecture development and test environment as well as the
integrated neural network simulator
NNSIM, both under development in the AIROLAB.
AGES permits users to define agent architectures
in a generic way (at several
levels of abstraction) and can run the architectures without
modification on simulated and real robots.
Affective Agent Control. Here, the
general trade-offs of agents controlled by affective states as compared to
agent controlled by more classical deliberative methods are investigated using
simulation experiments in the artificial life simulator
SIMWORLD. SIMWORLD
is based on the free
SIMAGENT toolkit (developed by
Aaron Sloman), which provides functionality for running different
interacting agents and objects in a simulated, continuous environment. The
agents are controlled by rules written in the powerful rule interpreter
POPRULEBASE
(which is part of SIMAGENT). New behaviors of agents can be defined without any
knowledge of
POP11
the underlying programming language of S
IMAGENT and
SIMWORLD).
SIMWORLD is used together with a distributed simulation experiment server,
which dynamically schedules and supervises experiments on remote hosts. Once the
experiments have finished, the server gathers statistics and produces a summary
report in several formats (e.g., html or latex).