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Robotics is an ever-expanding field and intelligent planning
continues to play a major role. Given that the intention of mobile
robots is to carry out tasks independent from human aid, robot
intelligence is needed to make and plan out decisions based on
various sensors. Planning is the fundamental activity that
implements this intelligence into the mobile robots to complete
such tasks. Understanding problems, challenges, and solutions to
path planning and how it fits in is important to the realm of
robotics. Intelligent Planning for Mobile Robotics: Algorithmic
Approaches presents content coverage on the basics of artificial
intelligence, search problems, and soft computing approaches. This
collection of research provides insight on both robotics and basic
algorithms and could serve as a reference book for courses related
to robotics, special topics in AI, planning, applied soft
computing, applied AI, and applied evolutionary computing. It is an
ideal choice for research students, scholars, and professors alike.
Soft Computing today is a very vast field whose extent is beyond
measure. The boundaries of this magnificent field are spreading at
an enormous rate making it possible to build computationally
intelligent systems that can do virtually anything, even after
considering the hostile practical limitations. Soft Computing,
mainly comprising of Artificial Neural Networks, Evolutionary
Computation, and Fuzzy Logic may itself be insufficient to cater to
the needs of various kinds of complex problems. In such a scenario,
we need to carry out amalgamation of same or different computing
approaches, along with heuristics, to make fabulous systems for
problem solving. There is further an attempt to make these
computing systems as adaptable as possible, where the value of any
parameter is set and continuously modified by the system itself.
This book first presents the basic computing techniques, draws
special attention towards their advantages and disadvantages, and
then motivates their fusion, in a manner to maximize the advantages
and minimize the disadvantages. Conceptualization is a key element
of the book, where emphasis is on visualizing the dynamics going
inside the technique of use, and hence noting the shortcomings. A
detailed description of different varieties of hybrid and adaptive
computing systems is given, paying special attention towards
conceptualization and motivation. Different evolutionary techniques
are discussed that hold potential for generation of fairly complex
systems. The complete book is supported by the application of these
techniques to biometrics. This not only enables better
understanding of the techniques with the added application base, it
also opens new dimensions of possibilities how multiple biometric
modalities can be fused together to make effective and scalable
systems.
Soft Computing today is a very vast field whose extent is beyond
measure. The boundaries of this magnificent field are spreading at
an enormous rate making it possible to build computationally
intelligent systems that can do virtually anything, even after
considering the hostile practical limitations. Soft Computing,
mainly comprising of Artificial Neural Networks, Evolutionary
Computation, and Fuzzy Logic may itself be insufficient to cater to
the needs of various kinds of complex problems. In such a scenario,
we need to carry out amalgamation of same or different computing
approaches, along with heuristics, to make fabulous systems for
problem solving. There is further an attempt to make these
computing systems as adaptable as possible, where the value of any
parameter is set and continuously modified by the system itself.
This book first presents the basic computing techniques, draws
special attention towards their advantages and disadvantages, and
then motivates their fusion, in a manner to maximize the advantages
and minimize the disadvantages. Conceptualization is a key element
of the book, where emphasis is on visualizing the dynamics going
inside the technique of use, and hence noting the shortcomings. A
detailed description of different varieties of hybrid and adaptive
computing systems is given, paying special attention towards
conceptualization and motivation. Different evolutionary techniques
are discussed that hold potential for generation of fairly complex
systems. The complete book is supported by the application of these
techniques to biometrics. This not only enables better
understanding of the techniques with the added application base, it
also opens new dimensions of possibilities how multiple biometric
modalities can be fused together to make effective and scalable
systems.
Autonomous Mobile Robots: Planning, Navigation, and Simulation
presents detailed coverage of the domain of robotics in motion
planning and associated topics in navigation. This book covers
numerous base planning methods from diverse schools of learning,
including deliberative planning methods, reactive planning methods,
task planning methods, fusion of different methods, and cognitive
architectures. It is a good resource for doing initial project work
in robotics, providing an overview, methods and simulation software
in one resource. For more advanced readers, it presents a variety
of planning algorithms to choose from, presenting the tradeoffs
between the algorithms to ascertain a good choice. Finally, the
book presents fusion mechanisms to design hybrid algorithms.
Rapid advancements in the application of soft computing tools and
techniques have proven valuable in the development of highly
scalable systems and resulted in brilliant applications, including
those in biometric identification, interactive voice response
systems, and data mining. Although many resources on the subject
adequately cover the theoretic concepts, few provide clear insight
into practical application. Filling this need, Real Life
Applications of Soft Computing explains such applications,
including the underlying technology and its implementation. While
these systems initially seem complex, the authors clearly
demonstrate how they can be modeled, designed, and implemented.
Written in a manner that makes it accessible to novices, the book
begins by covering the theoretical foundations of soft computing.
It supplies a concise explanation of various models, principles,
algorithms, tools, and techniques, including artificial neural
networks, fuzzy systems, evolutionary algorithms, and hybrid
algorithms. Supplying in-depth exposure to real life systems, the
text provides: Multi-dimensional coverage supported by references,
figures, and tables Warnings about common pitfalls in the
implementation process, as well as detailed examinations of
possible solutions A timely account of developments in various
areas of application Solved examples and exercises in each chapter
Detailing a wide range of contemporary applications, the text
includes coverage of those in biometric systems, including
physiological and behavioral biometrics. It also examines
applications in legal threat assessment, robotic path planning, and
navigation control. The authors consider fusion methods in
biometrics and bioinformatics and also provide effective disease
identification techniques. Co
On-Road Intelligent Vehicles: Motion Planning for Intelligent
Transportation Systems deals with the technology of autonomous
vehicles, with a special focus on the navigation and planning
aspects, presenting the information in three parts. Part One deals
with the use of different sensors to perceive the environment,
thereafter mapping the multi-domain senses to make a map of the
operational scenario, including topics such as proximity sensors
which give distances to obstacles, vision cameras, and computer
vision techniques that may be used to pre-process the image,
extract relevant features, and use classification techniques like
neural networks and support vector machines for the identification
of roads, lanes, vehicles, obstacles, traffic lights, signs, and
pedestrians. With a detailed insight into the technology behind the
vehicle, Part Two of the book focuses on the problem of motion
planning. Numerous planning techniques are discussed and adapted to
work for multi-vehicle traffic scenarios, including the use of
sampling based approaches comprised of Genetic Algorithm and
Rapidly-exploring Random Trees and Graph search based approaches,
including a hierarchical decomposition of the algorithm and
heuristic selection of nodes for limited exploration, Reactive
Planning based approaches, including Fuzzy based planning,
Potential Field based planning, and Elastic Strip and logic based
planning. Part Three of the book covers the macroscopic concepts
related to Intelligent Transportation Systems with a discussion of
various topics and concepts related to transportation systems,
including a description of traffic flow, the basic theory behind
transportation systems, and generation of shock waves.
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