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This book is the sixth volume of the successful book series on
Robot Operating System: The Complete Reference. The objective of
the book is to provide the reader with comprehensive coverage of
the Robot Operating Systems (ROS) and the latest trends and
contributed systems. ROS is currently considered as the primary
development framework for robotics applications. There are seven
chapters organized into three parts. Part I presents two chapters
on the emerging ROS 2.0 framework; in particular, ROS 2.0 is become
increasingly mature to be integrated into the industry. The first
chapter from Amazon AWS deals with the challenges that ROS 2
developers will face as they transition their system to be
commercial-grade. The second chapter deals with reactive
programming for both ROS1 and ROS. In Part II, two chapters deal
with advanced robotics, namely on the usage of robots in farms, and
the second deals with platooning systems. Part III provides three
chapters on ROS navigation. The first chapter deals with the use of
deep learning for ROS navigation. The second chapter presents a
detailed tuning guide on ROS navigation and the last chapter
discusses SLAM for ROS applications. I believe that this book is a
valuable companion for ROS users and developers to learn more ROS
capabilities and features.
This book is used at the graduate or advanced undergraduate level
and many others. Manned and unmanned ground, aerial and marine
vehicles enable many promising and revolutionary civilian and
military applications that will change our life in the near future.
These applications include, but are not limited to, surveillance,
search and rescue, environment monitoring, infrastructure
monitoring, self-driving cars, contactless last-mile delivery
vehicles, autonomous ships, precision agriculture and transmission
line inspection to name just a few. These vehicles will benefit
from advances of deep learning as a subfield of machine learning
able to endow these vehicles with different capability such as
perception, situation awareness, planning and intelligent control.
Deep learning models also have the ability to generate actionable
insights into the complex structures of large data sets. In recent
years, deep learning research has received an increasing amount of
attention from researchers in academia, government laboratories and
industry. These research activities have borne some fruit in
tackling some of the challenging problems of manned and unmanned
ground, aerial and marine vehicles that are still open. Moreover,
deep learning methods have been recently actively developed in
other areas of machine learning, including reinforcement training
and transfer/meta-learning, whereas standard, deep learning methods
such as recent neural network (RNN) and coevolutionary neural
networks (CNN). The book is primarily meant for researchers from
academia and industry, who are working on in the research areas
such as engineering, control engineering, robotics, mechatronics,
biomedical engineering, mechanical engineering and computer
science. The book chapters deal with the recent research problems
in the areas of reinforcement learning-based control of UAVs and
deep learning for unmanned aerial systems (UAS) The book chapters
present various techniques of deep learning for robotic
applications. The book chapters contain a good literature survey
with a long list of references. The book chapters are well written
with a good exposition of the research problem, methodology, block
diagrams and mathematical techniques. The book chapters are lucidly
illustrated with numerical examples and simulations. The book
chapters discuss details of applications and future research areas.
This book is the fifth volume in the successful book series Robot
Operating System: The Complete Reference. The objective of the book
is to provide the reader with comprehensive coverage on the Robot
Operating System (ROS), which is currently considered to be the
primary development framework for robotics applications, and the
latest trends and contributing systems. The content is divided into
six parts. Pat I presents for the first time the emerging ROS 2.0
framework, while Part II focuses on multi-robot systems, namely on
SLAM and Swarm coordination. Part III provides two chapters on
autonomous systems, namely self-driving cars and unmanned aerial
systems. In turn, Part IV addresses the contributions of simulation
frameworks for ROS. In Part V, two chapters explore robotic
manipulators and legged robots. Finally, Part VI presents emerging
topics in monocular SLAM and a chapter on fault tolerance systems
for ROS. Given its scope, the book will offer a valuable companion
for ROS users and developers, helping them deepen their knowledge
of ROS capabilities and features.
This book is the sixth volume of the successful book series on
Robot Operating System: The Complete Reference. The objective of
the book is to provide the reader with comprehensive coverage of
the Robot Operating Systems (ROS) and the latest trends and
contributed systems. ROS is currently considered as the primary
development framework for robotics applications. There are seven
chapters organized into three parts. Part I presents two chapters
on the emerging ROS 2.0 framework; in particular, ROS 2.0 is become
increasingly mature to be integrated into the industry. The first
chapter from Amazon AWS deals with the challenges that ROS 2
developers will face as they transition their system to be
commercial-grade. The second chapter deals with reactive
programming for both ROS1 and ROS. In Part II, two chapters deal
with advanced robotics, namely on the usage of robots in farms, and
the second deals with platooning systems. Part III provides three
chapters on ROS navigation. The first chapter deals with the use of
deep learning for ROS navigation. The second chapter presents a
detailed tuning guide on ROS navigation and the last chapter
discusses SLAM for ROS applications. I believe that this book is a
valuable companion for ROS users and developers to learn more ROS
capabilities and features.
This book is the fifth volume in the successful book series Robot
Operating System: The Complete Reference. The objective of the book
is to provide the reader with comprehensive coverage on the Robot
Operating System (ROS), which is currently considered to be the
primary development framework for robotics applications, and the
latest trends and contributing systems. The content is divided into
six parts. Pat I presents for the first time the emerging ROS 2.0
framework, while Part II focuses on multi-robot systems, namely on
SLAM and Swarm coordination. Part III provides two chapters on
autonomous systems, namely self-driving cars and unmanned aerial
systems. In turn, Part IV addresses the contributions of simulation
frameworks for ROS. In Part V, two chapters explore robotic
manipulators and legged robots. Finally, Part VI presents emerging
topics in monocular SLAM and a chapter on fault tolerance systems
for ROS. Given its scope, the book will offer a valuable companion
for ROS users and developers, helping them deepen their knowledge
of ROS capabilities and features.
This is the fourth volume of the successful series Robot Operating
Systems: The Complete Reference, providing a comprehensive overview
of robot operating systems (ROS), which is currently the main
development framework for robotics applications, as well as the
latest trends and contributed systems. The book is divided into
four parts: Part 1 features two papers on navigation, discussing
SLAM and path planning. Part 2 focuses on the integration of ROS
into quadcopters and their control. Part 3 then discusses two
emerging applications for robotics: cloud robotics, and video
stabilization. Part 4 presents tools developed for ROS; the first
is a practical alternative to the roslaunch system, and the second
is related to penetration testing. This book is a valuable resource
for ROS users and wanting to learn more about ROS capabilities and
features.
This is the fourth volume of the successful series Robot Operating
Systems: The Complete Reference, providing a comprehensive overview
of robot operating systems (ROS), which is currently the main
development framework for robotics applications, as well as the
latest trends and contributed systems. The book is divided into
four parts: Part 1 features two papers on navigation, discussing
SLAM and path planning. Part 2 focuses on the integration of ROS
into quadcopters and their control. Part 3 then discusses two
emerging applications for robotics: cloud robotics, and video
stabilization. Part 4 presents tools developed for ROS; the first
is a practical alternative to the roslaunch system, and the second
is related to penetration testing. This book is a valuable resource
for ROS users and wanting to learn more about ROS capabilities and
features.
This book presents extensive research on two main problems in
robotics: the path planning problem and the multi-robot task
allocation problem. It is the first book to provide a comprehensive
solution for using these techniques in large-scale environments
containing randomly scattered obstacles. The research conducted
resulted in tangible results both in theory and in practice. For
path planning, new algorithms for large-scale problems are devised
and implemented and integrated into the Robot Operating System
(ROS). The book also discusses the parallelism advantage of cloud
computing techniques to solve the path planning problem, and, for
multi-robot task allocation, it addresses the task assignment
problem and the multiple traveling salesman problem for mobile
robots applications. In addition, four new algorithms have been
devised to investigate the cooperation issues with extensive
simulations and comparative performance evaluation. The algorithms
are implemented and simulated in MATLAB and Webots.
This second volume is a continuation of the successful first volume
of this Springer book, and as well as addressing broader topics it
puts a particular focus on unmanned aerial vehicles (UAVs) with
Robot Operating System (ROS). Consisting of three types of
chapters: tutorials, cases studies, and research papers, it
provides comprehensive additional material on ROS and the aspects
of developing robotics systems, algorithms, frameworks, and
applications with ROS. ROS is being increasingly integrated in
almost all kinds of robots and is becoming the de-facto standard
for developing applications and systems for robotics. Although the
research community is actively developing applications with ROS and
extending its features, amount of literature references is not
representative of the huge amount of work being done. The book
includes 19 chapters organized into six parts: Part 1 presents the
control of UAVs with ROS, while in Part 2, three chapters deal with
control of mobile robots. Part 3 provides recent work toward
integrating ROS with Internet, cloud and distributed systems. Part
4 offers five case studies of service robots and field experiments.
Part 5 presents signal-processing tools for perception and sensing,
and lastly, Part 6 introduces advanced simulation frameworks. The
diversity of topics in the book makes it a unique and valuable
reference resource for ROS users, researchers, learners and
developers.
This book presents extensive research on two main problems in
robotics: the path planning problem and the multi-robot task
allocation problem. It is the first book to provide a comprehensive
solution for using these techniques in large-scale environments
containing randomly scattered obstacles. The research conducted
resulted in tangible results both in theory and in practice. For
path planning, new algorithms for large-scale problems are devised
and implemented and integrated into the Robot Operating System
(ROS). The book also discusses the parallelism advantage of cloud
computing techniques to solve the path planning problem, and, for
multi-robot task allocation, it addresses the task assignment
problem and the multiple traveling salesman problem for mobile
robots applications. In addition, four new algorithms have been
devised to investigate the cooperation issues with extensive
simulations and comparative performance evaluation. The algorithms
are implemented and simulated in MATLAB and Webots.
The objective of this book is to provide the reader with a
comprehensive coverage on the Robot Operating Systems (ROS) and
latest related systems, which is currently considered as the main
development framework for robotics applications. The book includes
twenty-seven chapters organized into eight parts. Part 1 presents
the basics and foundations of ROS. In Part 2, four chapters deal
with navigation, motion and planning. Part 3 provides four examples
of service and experimental robots. Part 4 deals with real-world
deployment of applications. Part 5 presents signal-processing tools
for perception and sensing. Part 6 provides software engineering
methodologies to design complex software with ROS. Simulations
frameworks are presented in Part 7. Finally, Part 8 presents
advanced tools and frameworks for ROS including multi-master
extension, network introspection, controllers and cognitive
systems. This book will be a valuable companion for ROS users and
developers to learn more ROS capabilities and features.
This book is the second volume on Cooperative Robots and Sensor
Networks. The primary objective of this book is to provide an
up-to-date reference for cutting-edge studies and research trends
related to mobile robots and wireless sensor networks, and in
particular for the coupling between them. Indeed, mobile robots and
wireless sensor networks have enabled great potentials and a large
space for ubiquitous and pervasive applications. Robotics and
wireless sensor networks have mostly been considered as separate
research fields and little work has investigated the marriage
between these two technologies. However, these two technologies
share several features, enable common cyber-physical applications
and provide complementary support to each other. The book consists
of ten chapters, organized into four parts. The first part of the
book presents three chapters related to localization of mobile
robots using wireless sensor networks. Two chapters presented new
solutions based Extended Kalman Filter and Particle Filter for
localizing the robots using range measurements with the sensor
network. The third chapter presents a survey on mobility-assisted
localization techniques in wireless sensor networks. The second
part of the book deals with cooperative robots and sensor networks
applications. One chapter presents a comprehensive overview of
major applications coupling between robots and sensor networks and
provides real-world examples of their cooperation. Two other
chapters present applications for underwater robots and sensor
networks.
This book comprises four chapters that address some of the latest
research in clouds robotics and sensor clouds. The first part of
the book includes two chapters on cloud robotics. The first chapter
introduces a novel resource allocation framework for cloud robotics
and proposes a Stackelberg game model and the corresponding task
oriented pricing mechanism for resource allocation. In the second
chapter, the authors apply Cloud Computing for building a
Cloud-Based 3D Point Cloud extractor for stereo images. Their
objective is to have a dynamically scalable and applicable to near
real-time scenarios.
The objective of this book is to provide the reader with a
comprehensive coverage on the Robot Operating Systems (ROS) and
latest related systems, which is currently considered as the main
development framework for robotics applications. The book includes
twenty-seven chapters organized into eight parts. Part 1 presents
the basics and foundations of ROS. In Part 2, four chapters deal
with navigation, motion and planning. Part 3 provides four examples
of service and experimental robots. Part 4 deals with real-world
deployment of applications. Part 5 presents signal-processing tools
for perception and sensing. Part 6 provides software engineering
methodologies to design complex software with ROS. Simulations
frameworks are presented in Part 7. Finally, Part 8 presents
advanced tools and frameworks for ROS including multi-master
extension, network introspection, controllers and cognitive
systems. This book will be a valuable companion for ROS users and
developers to learn more ROS capabilities and features.
This book comprises four chapters that address some of the latest
research in clouds robotics and sensor clouds. The first part of
the book includes two chapters on cloud robotics. The first chapter
introduces a novel resource allocation framework for cloud robotics
and proposes a Stackelberg game model and the corresponding task
oriented pricing mechanism for resource allocation. In the second
chapter, the authors apply Cloud Computing for building a
Cloud-Based 3D Point Cloud extractor for stereo images. Their
objective is to have a dynamically scalable and applicable to near
real-time scenarios.
This book compiles some of the latest research in cooperation
between robots and sensor networks. Structured in twelve chapters,
this book addresses fundamental, theoretical, implementation and
experimentation issues. The chapters are organized into four parts
namely multi-robots systems, data fusion and localization, security
and dependability, and mobility.
This book outlines the most important characteristics of IEEE
802.15.4 and ZigBee and how they can be used to engineer Wireless
Sensor Network (WSN) systems and applications, with a particular
focus on Quality-of-Service (QoS) aspects. It starts by providing a
snapshot of the most relevant features of these two protocols,
identifying some gaps in the standard specifications. Then it
describes several state-of-the-art open-source implementations,
models and tools that have been designed by the authors and have
been widely used by the international community. The book also
outlines the fundamental performance limits of IEEE 802.15.4/ZigBee
networks, based on well-sustained analytical, simulation and
experimental models, including how to dimension such networks to
optimize delay/energy trade-offs.
This book is used at the graduate or advanced undergraduate level
and many others. Manned and unmanned ground, aerial and marine
vehicles enable many promising and revolutionary civilian and
military applications that will change our life in the near future.
These applications include, but are not limited to, surveillance,
search and rescue, environment monitoring, infrastructure
monitoring, self-driving cars, contactless last-mile delivery
vehicles, autonomous ships, precision agriculture and transmission
line inspection to name just a few. These vehicles will benefit
from advances of deep learning as a subfield of machine learning
able to endow these vehicles with different capability such as
perception, situation awareness, planning and intelligent control.
Deep learning models also have the ability to generate actionable
insights into the complex structures of large data sets. In recent
years, deep learning research has received an increasing amount of
attention from researchers in academia, government laboratories and
industry. These research activities have borne some fruit in
tackling some of the challenging problems of manned and unmanned
ground, aerial and marine vehicles that are still open. Moreover,
deep learning methods have been recently actively developed in
other areas of machine learning, including reinforcement training
and transfer/meta-learning, whereas standard, deep learning methods
such as recent neural network (RNN) and coevolutionary neural
networks (CNN). The book is primarily meant for researchers from
academia and industry, who are working on in the research areas
such as engineering, control engineering, robotics, mechatronics,
biomedical engineering, mechanical engineering and computer
science. The book chapters deal with the recent research problems
in the areas of reinforcement learning-based control of UAVs and
deep learning for unmanned aerial systems (UAS) The book chapters
present various techniques of deep learning for robotic
applications. The book chapters contain a good literature survey
with a long list of references. The book chapters are well written
with a good exposition of the research problem, methodology, block
diagrams and mathematical techniques. The book chapters are lucidly
illustrated with numerical examples and simulations. The book
chapters discuss details of applications and future research areas.
Unmanned Aerial Systems: Theoretical Foundation and Applications
presents some of the latest innovative approaches to drones from
the point-of-view of dynamic modeling, system analysis,
optimization, control, communications, 3D-mapping, search and
rescue, surveillance, farmland and construction monitoring, and
more. With the emergence of low-cost UAS, a vast array of research
works in academia and products in the industrial sectors have
evolved. The book covers the safe operation of UAS, including, but
not limited to, fundamental design, mission and path planning,
control theory, computer vision, artificial intelligence,
applications requirements, and more. This book provides a unique
reference of the state-of-the-art research and development of
unmanned aerial systems, making it an essential resource for
researchers, instructors and practitioners.
Building on the successful first and second volumes, this book is
the third volume of the Springer book on the Robot Operating System
(ROS): The Complete Reference. The Robot Operating System is
evolving from year to year with a wealth of new contributed
packages and enhanced capabilities. Further, the ROS is being
integrated into various robots and systems and is becoming an
embedded technology in emerging robotics platforms. The objective
of this third volume is to provide readers with additional and
comprehensive coverage of the ROS and an overview of the latest
achievements, trends and packages developed with and for it.
Combining tutorials, case studies, and research papers, the book
consists of sixteen chapters and is divided into five parts. Part 1
presents multi-robot systems with the ROS. In Part 2, four chapters
deal with the development of unmanned aerial systems and their
applications. In turn, Part 3 highlights recent work related to
navigation, motion planning and control. Part 4 discusses recently
contributed ROS packages for security, ROS2, GPU usage, and
real-time processing. Lastly, Part 5 deals with new interfaces
allowing users to interact with robots. Taken together, the three
volumes of this book offer a valuable reference guide for ROS
users, researchers, learners and developers alike. Its breadth of
coverage makes it a unique resource.
Building on the successful first and second volumes, this book is
the third volume of the Springer book on the Robot Operating System
(ROS): The Complete Reference. The Robot Operating System is
evolving from year to year with a wealth of new contributed
packages and enhanced capabilities. Further, the ROS is being
integrated into various robots and systems and is becoming an
embedded technology in emerging robotics platforms. The objective
of this third volume is to provide readers with additional and
comprehensive coverage of the ROS and an overview of the latest
achievements, trends and packages developed with and for it.
Combining tutorials, case studies, and research papers, the book
consists of sixteen chapters and is divided into five parts. Part 1
presents multi-robot systems with the ROS. In Part 2, four chapters
deal with the development of unmanned aerial systems and their
applications. In turn, Part 3 highlights recent work related to
navigation, motion planning and control. Part 4 discusses recently
contributed ROS packages for security, ROS2, GPU usage, and
real-time processing. Lastly, Part 5 deals with new interfaces
allowing users to interact with robots. Taken together, the three
volumes of this book offer a valuable reference guide for ROS
users, researchers, learners and developers alike. Its breadth of
coverage makes it a unique resource.
This second volume is a continuation of the successful first volume
of this Springer book, and as well as addressing broader topics it
puts a particular focus on unmanned aerial vehicles (UAVs) with
Robot Operating System (ROS). Consisting of three types of
chapters: tutorials, cases studies, and research papers, it
provides comprehensive additional material on ROS and the aspects
of developing robotics systems, algorithms, frameworks, and
applications with ROS. ROS is being increasingly integrated in
almost all kinds of robots and is becoming the de-facto standard
for developing applications and systems for robotics. Although the
research community is actively developing applications with ROS and
extending its features, amount of literature references is not
representative of the huge amount of work being done. The book
includes 19 chapters organized into six parts: Part 1 presents the
control of UAVs with ROS, while in Part 2, three chapters deal with
control of mobile robots. Part 3 provides recent work toward
integrating ROS with Internet, cloud and distributed systems. Part
4 offers five case studies of service robots and field experiments.
Part 5 presents signal-processing tools for perception and sensing,
and lastly, Part 6 introduces advanced simulation frameworks. The
diversity of topics in the book makes it a unique and valuable
reference resource for ROS users, researchers, learners and
developers.
This book provides a comprehensive survey on related work for radio
link quality estimation, which covers the characteristics of
low-power links, the fundamental concepts of link quality
estimation in wireless sensor networks, a taxonomy of existing link
quality estimators and their performance analysis. It then shows
how link quality estimation can be used for designing protocols and
mechanisms such as routing and hand-off. The final part is
dedicated to radio interference estimation, generation and
mitigation.
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