Page 7 - Innovations in Intelligent Machines

VI Foreword
information about their successes and failures, underpins the development of
human-like intelligence. This insight is further developed in Chapter 8 where
the authors look at the evolution-based dynamic path planning.
Chapter 5 emphasises the importance of physical constraints on the UAVs
in accomplishing a specific task. To re-phrase it in slightly more general terms,
it highlights the fact that algorithmic information processing may be numer-
ically correct but it may not be physically very meaningful if the laws of
physics are not taken fully into account. This is exactly where the importance
of empirical verification comes to fore in intelligent decision-making.
The practice of processing uncertain information at various levels of
abstraction (granulation) is now well recognised as a characteristic feature
of human information processing. By discussing the state estimation of UAVs
based on information provided by low fidelity sensors, Chapter 6 provides a ref-
erence material for dealing with uncertain data. Discussion of the continuous-
discrete extended Kalman filter placed in the context of intelligent machines
underlines the importance of information abstraction (granulation).
Chapters 7 and 9 share a theme of enhancement of sensory perception of
intelligent machines. Given that the interaction with the environment is a key
component of intelligent machines, the development of sensors providing omni
directional vision is a promising way to achieving enhanced levels of intelli-
gence. Also the ability to achieve, through appropriate sensor design, long
distance (low accuracy) and short distance (high accuracy) vision correlates
closely with the multi-resolution (granular) information processing by humans.
The book is an excellent compilation of leading-edge contributions in the
area of intelligent machines and it is likely to be on the essential reading list of
those who are keen to combine theoretical insights with practical applications.

Andrzej Bargiela
Professor of Computer Science
University of Nottingham, UK