Page 18 - DCAP310_INTRODUCTION_TO_ARTIFICIAL_INTELLIGENCE_AND_EXPERT_SYSTEMS

Introduction to Artificial Intelligence & Expert Systems

Notes (a) Artificial Intelligence – Robotics: Robots are a practical application of artificial intelligence
of rapidly growing importance for industrial, domestic, entertainment and military tasks.
The capabilities of today’s robots go far beyond the factory robots of the last century,
whose operations depended on the strictly controlled conditions of an assembly line.
Today’s field and service robots must be able operate in the unstructured world of a shop
floor, a home, a school or a battlefield. Furthermore, the software controlling such machines
must be far more flexible, robust and autonomous than the robot programming languages
of the past. They must be able to be commanded to go about their tasks far more readily
than is today possible. In order to solve such demanding problems, it is not only necessary
to build and test new kinds machines, but also to create new and powerful classes of
algorithms, the general applicability of which can be demonstrated by the successful
operation of those machines on challenging problems. We invite research students to join
us in this important work; skills in electronics, mechanics or software development are
welcome, but an interest in robots is essential!
(b) Artificial Intelligence – Vision: Computer vision is a field that includes methods for
acquiring, processing, analyzing, and understanding images and, in general,
high-dimensional data from the real world in order to produce numerical or symbolic
information, e.g., in the forms of decisions. A theme in the development of this field has
been to duplicate the abilities of human vision by electronically perceiving and
understanding an image. This image understanding can be seen as the disentangling of
symbolic information from image data using models constructed with the aid of geometry,
physics, statistics, and learning theory. Computer vision has also been described as the
enterprise of automating and integrating a wide range of processes and representations
for vision perception.
Applications range from tasks such as industrial machine vision systems which, say,
inspect bottles speeding by on a production line, to research into artificial intelligence and
computers or robots that can comprehend the world around them. The computer vision
and machine vision fields have significant overlap. Computer vision covers the core
technology of automated image analysis which is used in many fields. Machine vision
usually refers to a process of combining automated image analysis with other methods
and technologies to provide automated inspection and robot guidance in industrial
applications.
As a scientific discipline, computer vision is concerned with the theory behind artificial
systems that extract information from images. The image data can take many forms, such
as video sequences, views from multiple cameras, or multi-dimensional data from a
medical scanner.

As a technological discipline, computer vision seeks to apply its theories and models to
the construction of computer vision systems. Examples of applications of computer vision
include systems for:
Controlling processes, e.g., an industrial robot;
Navigation, e.g., by an autonomous vehicle or mobile robot;

Detecting events, e.g., for visual surveillance or people counting;
Organizing information, e.g., for indexing databases of images and image sequences;
Modeling objects or environments, e.g., medical image analysis or topographical
modeling;

Interaction, e.g., as the input to a device for computer-human interaction, and
Automatic inspection, e.g., in manufacturing applications.

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