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Neural Networks in Robotics is the first book to present an
integrated view of both the application of artificial neural
networks to robot control and the neuromuscular models from which
robots were created. The behavior of biological systems provides
both the inspiration and the challenge for robotics. The goal is to
build robots which can emulate the ability of living organisms to
integrate perceptual inputs smoothly with motor responses, even in
the presence of novel stimuli and changes in the environment. The
ability of living systems to learn and to adapt provides the
standard against which robotic systems are judged. In order to
emulate these abilities, a number of investigators have attempted
to create robot controllers which are modelled on known processes
in the brain and musculo-skeletal system. Several of these models
are described in this book. On the other hand, connectionist
(artificial neural network) formulations are attractive for the
computation of inverse kinematics and dynamics of robots, because
they can be trained for this purpose without explicit programming.
Some of the computational advantages and problems of this approach
are also presented. For any serious student of robotics, Neural
Networks in Robotics provides an indispensable reference to the
work of major researchers in the field. Similarly, since robotics
is an outstanding application area for artificial neural networks,
Neural Networks in Robotics is equally important to workers in
connectionism and to students for sensormonitor control in living
systems.
Modeling and Simulation: Theory and Practice provides a
comprehensive review of both methodologies and applications of
simulation and modeling. The methodology section includes such
topics as the philosophy of simulation, inverse problems in
simulation, simulation model compilers, treatment of ill-defined
systems, and a survey of simulation languages. The application
section covers a wide range of topics, including applications to
environmental management, biology and medicine, neural networks,
collaborative visualization and intelligent interfaces. The book
consists of 13 invited chapters written by former colleagues and
students of Professor Karplus. Also included are several short
'reminiscences' describing Professor Karplus' impact on the
professional careers of former colleagues and students who worked
closely with him over the years.
Modeling and Simulation: Theory and Practice provides a
comprehensive review of both methodologies and applications of
simulation and modeling. The methodology section includes such
topics as the philosophy of simulation, inverse problems in
simulation, simulation model compilers, treatment of ill-defined
systems, and a survey of simulation languages. The application
section covers a wide range of topics, including applications to
environmental management, biology and medicine, neural networks,
collaborative visualization and intelligent interfaces. The book
consists of 13 invited chapters written by former colleagues and
students of Professor Karplus. Also included are several short
'reminiscences' describing Professor Karplus' impact on the
professional careers of former colleagues and students who worked
closely with him over the years.
An agent is a system capable of perceiving the environment,
reasoning with the percepts and then acting upon the world. Agents
can be purely software systems, in which case their percepts and
output actions' are encoded binary strings. However, agents can
also be realized in hardware, and then they are robots. The
Artificial Intelligence community frequently views robots as
embodied intelligent agents. The First International Conference on
Autonomous Agents was held in Santa Monica, California, in February
1997. This conference brought together researchers from around the
world with interests in agents, whether implemented purely in
software or in hardware. The conference featured such topics as
intelligent software agents, agents in virtual environments, agents
in the entertainment industry, and robotic agents. Papers on
robotic agents were selected for this volume. Autonomous Agents
will be of interest to researchers and students in the area of
artificial intelligence and robotics.
Robots in groups or colonies can exhibit an enormous variety and
richness of behaviors which cannot be observed with singly
autonomous systems. Of course, this is analogous to the amazing
variety of group animal behaviors which can be observed in nature.
In recent years more and more investigators have started to study
these behaviors. The studies range from classifications and
taxonomies of behaviors, to development of architectures which
cause such group activities as flocking or swarming, and from
emphasis on the role of intelligent agents in such groups to
studies of learning and obstacle avoidance. There used to be a time
when many robotics researchers would question those who were
interested in working with teams of robots: Why are you worried
about robotic teams when it's hard enough to just get one to
work?'. This issue responds to that question. Robot Colonies
provides a new approach to task problem-solving that is similar in
many ways to distributed computing. Multiagent robotic teams offer
the possibility of spatially distributed parallel and concurrent
perception and action. A paradigm shift results when using multiple
robots, providing a different perspective on how to carry out
complex tasks. New issues such as interagent communications,
spatial task distribution, heterogeneous or homogeneous societies,
and interference management are now central to achieving
coordinated and productive activity within a colony. Fortunately
mobile robot hardware has evolved sufficiently in terms of both
cost and robustness to enable these issues to be studied on actual
robots and not merely in simulation. Robot Colonies presents a
sampling of the research in this field. While capturing a
reasonable representation of the most important work within this
area, its objective is not to be a comprehensive survey, but rather
to stimulate new research by exposing readers to the principles of
robot group behaviors, architectures and theories. Robot Colonies
is an edited volume of peer-reviewed original research comprising
eight invited contributions by leading researchers. This research
work has also been published as a special issue of Autonomous
Robots (Volume 4, Number 1).
Underwater Robots reports on the latest progress in underwater
robotics. In spite of its importance, the ocean is generally
overlooked, since we focus more of our attention on land and
atmospheric issues. We have not yet been able to explore the full
depths of the ocean and its resources. The deep oceans range
between 19000 to 36000 feet. At a mere 33-foot depth, the pressure
is twice the normal atmospheric pressure of 29.4 psi. This
obstacle, compounded with other complex issues due to the
unstructured and hazardous environment, makes it difficult to
travel in the ocean even though today's technologies allow humans
to land on the moon. Only recently, we discovered by using manned
submersibles that a large amount of carbon dioxide comes from the
sea-floor and that extraordinary groups of organisms live in
hydrothermal vent areas. On March 24, 1995 Kaiko (a remotely
operated vehicle) navigated the deepest region of the ocean, the
Mariana Trough. This vehicle successfully dived to a depth of 33000
feet and instantly showed scenes from the trench through a video
camera. New tools like this enable us to gain knowledge of
mysterious places. However, extensive use of manned submersibles
and remotely operated vehicles is limited to a few applications
because of very high operational costs, operator fatigue and safety
issues. In spite of these hindrances, the demand for advanced
underwater robot technologies is growing and will eventually arrive
at fully autonomous, specialized, reliable underwater robotic
vehicles. Underwater Robots is an edited volume of peer-reviewed
original research comprising thirteen invited contributions by
leading researchers. This research work has also been published as
a special issue of Autonomous Robots (Volume 3, Numbers 2 and 3).
Neural Networks in Robotics is the first book to present an
integrated view of both the application of artificial neural
networks to robot control and the neuromuscular models from which
robots were created. The behavior of biological systems provides
both the inspiration and the challenge for robotics. The goal is to
build robots which can emulate the ability of living organisms to
integrate perceptual inputs smoothly with motor responses, even in
the presence of novel stimuli and changes in the environment. The
ability of living systems to learn and to adapt provides the
standard against which robotic systems are judged. In order to
emulate these abilities, a number of investigators have attempted
to create robot controllers which are modelled on known processes
in the brain and musculo-skeletal system. Several of these models
are described in this book. On the other hand, connectionist
(artificial neural network) formulations are attractive for the
computation of inverse kinematics and dynamics of robots, because
they can be trained for this purpose without explicit programming.
Some of the computational advantages and problems of this approach
are also presented. For any serious student of robotics, Neural
Networks in Robotics provides an indispensable reference to the
work of major researchers in the field. Similarly, since robotics
is an outstanding application area for artificial neural networks,
Neural Networks in Robotics is equally important to workers in
connectionism and to students for sensormonitor control in living
systems.
An introduction to the science and practice of autonomous robots
that reviews over 300 current systems and examines the underlying
technology. Autonomous robots are intelligent machines capable of
performing tasks in the world by themselves, without explicit human
control. Examples range from autonomous helicopters to Roomba, the
robot vacuum cleaner. In this book, George Bekey offers an
introduction to the science and practice of autonomous robots that
can be used both in the classroom and as a reference for industry
professionals. He surveys the hardware implementations of more than
300 current systems, reviews some of their application areas, and
examines the underlying technology, including control,
architectures, learning, manipulation, grasping, navigation, and
mapping. Living systems can be considered the prototypes of
autonomous systems, and Bekey explores the biological inspiration
that forms the basis of many recent developments in robotics. He
also discusses robot control issues and the design of control
architectures. After an overview of the field that introduces some
of its fundamental concepts, the book presents background material
on hardware, control (from both biological and engineering
perspectives), software architecture, and robot intelligence. It
then examines a broad range of implementations and applications,
including locomotion (wheeled, legged, flying, swimming, and
crawling robots), manipulation (both arms and hands), localization,
navigation, and mapping. The many case studies and specific
applications include robots built for research, industry, and the
military, among them underwater robotic vehicles, walking machines
with four, six, and eight legs, and the famous humanoid robots Cog,
Kismet, ASIMO, and QRIO. The book concludes with reflections on the
future of robotics-the potential benefits as well as the possible
dangers that may arise from large numbers of increasingly
intelligent and autonomous robots.
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