Networking Humans, Robots and Environments


by

Nak Y. Chong

DOI: 10.2174/97816080573131130101
eISBN: 978-1-60805-731-3, 2013
ISBN: 978-1-60805-732-0



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This book dives into the heart of how to design distributed control architectures for heterogeneous teams of humans, robots, and autom...[view complete introduction]

Table of Contents

Foreword

- Pp. i-ii (2)

Lynne E. Parker

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Preface

- Pp. iii-v (3)

Nak Young Chong

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List of Contributors

- Pp. vi-vii (2)

Nak Young Chong

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Keywords

- Pp. viii-xi (4)

Nak Young Chong

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Networked Robotics: Developments and Opportunities

- Pp. 3-17 (15)

Gerard McKee and Blesson Varghese

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Collaborative Crowd Surveillance Using Networked Robotic Cameras

- Pp. 18-42 (25)

Yiliang Xu and Dezhen Song

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Distributed Sensing and Human-Aware Robot Reasoning Mechanisms

- Pp. 43-58 (16)

Fulvio Mastrogiovanni, Antonio Sgorbissa and Renato Zaccaria

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Self-Configurable Mobile Robot Swarms: Adaptive Triangular Mesh Generation

- Pp. 59-75 (17)

Geunho Lee and Nak Young Chong

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Experimental Validation of Multi-Agent Coordination by Decentralized Estimation and Control

- Pp. 76-100 (25)

Michael Hwang, Matthew L. Elwin, Peng Yang, Randy A. Freeman and Kevin M. Lynch

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Extending Lifetime of the Network and Crucial Node by Multiple Diversity Combining

- Pp. 101-117 (17)

Lichuan Liu

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Intelligent Space: A Platform for Integration of Robot Technology

- Pp. 118-143 (26)

Takeshi Sasaki and Hideki Hashimoto

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Universal Design of Ubiquitous Robotic Space

- Pp. 144-164 (21)

Bong Keun Kim, Hyun Min Do, Hideyiki Tanaka, Yasushi Sumi, Hiromu Onda, Tamio Tanikawa, Kohtaro Ohba and Tetsuo Tomizawa

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Ubiquitous Robotic Space and Its Real-world Applications

- Pp. 165-192 (28)

Wonpil Yu, Jae-Yeong Lee, Heesung Chae, Yu-Cheol Lee, Minsu Jang, Joo-Chan Sohn, Hyosung Ahn, Young-Guk Ha and Yong-Moo Kwon

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Toward High-Performance Stable Haptic Teleoperation over the Internet: Passive Set-Position Modulation (PSPM) Approach

- Pp. 193-213 (21)

Dongjun Lee and Ke Huang

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STABLE TELEOPERATION WITH TIME DOMAIN PASSIVITY CONTROL

- Pp. 214-228 (15)

Jee-Hwan Ryu, Dong-Soo Kwon and Blake Hannaford

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Index

- Pp. 229-241 (13)

Nak Young Chong

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Foreword

When I began my research in multi-robot systems over two decades ago, I had many discussions with prominent roboticists who thought that it was preposterous for anyone to attempt work on multi-robot teams. “Why explore multiple robot teams when we don’t even yet understand how to build a single intelligent robot?”, some said. Others said: “We will never use more than one autonomous robot for challenging applications such as space exploration – it is just too hard.”

Clearly, time has proven these naysayers wrong. Robot team capabilities have now evolved from swarms of homogeneous agents that exhibit emergent group behavior to heterogeneous teams that intelligently exploit the unique competences of each team member. The potential of these robot teams has been successfully demonstrated in many laboratory and real-world applications around the world. In fact, the advances in multi-robot cooperation have been so dramatic in the past decade that many aspects of multi-robot control are now nearly solved problems.

Of course, the story does not end there. Progress in the domain of multi-robot teams has led to a new frontier – a world in which robots no longer work only with other robot teammates that are in close proximity. Instead, these latest robots are now beginning to interact with each other, with humans, and with their environments, using the power of the network. These networked systems of interacting entities can take advantage of information not only in close physical proximity, but also information that is within networked communication proximity. This opens up a broad spectrum of new possibilities for networked humans, robots, and environments. In effect, the network extends the knowledge and reach of the individuals in the system, enabling them to have a more wide-reaching impact on the space in which they operate, and to have increased situational awareness of their surroundings and of the entities that share that space.

The research community has recognized the importance and potential of networked humans, robots, and environments, evidenced by the numerous research projects, workshops, symposia, technical committees, and special issues devoted to this topic over the past decade. This is a quickly growing community, ii which is achieving both theoretical and practical advances in the field. We now have examples of networked entities working together in outdoor urban environments, in home and office spaces, and in medical applications, just to name a few. Clearly, progress is being made.

Achieving this progress, however, requires answers to many new research questions regarding the networking of humans, robots, and environments, several of which are addressed in this book. First, what are the opportunities presented by networked robot systems (Ch. 1)? How do we model and design spaces that include networked humans, robots, and environments (Ch. 3, 7, 8, 9)? How should the networked sensors and robots interact (Ch. 2, 4, 5)? How should the network itself be designed to facilitate this interaction (Ch. 6)? How do humans interface with networked robots (Ch. 10, 11)?

This book presents interesting ideas for addressing these questions, and sheds light on new opportunities in this realm. While much remains to be studied, this book makes important advances that help us to better understand how to achieve highly productive, networked interactions between humans, robots, and environments.

Lynne E. Parker
Computer Science University of Tennessee
Knoxville
USA


Preface

How do robots interact with each other and their environment? How do they interact with humans? Questions abound when robots form a constituent of our daily life and natural environment. This book dives into the heart of how to design a novel distributed robot control and interaction architecture for achieving autonomous decision making and task execution in dynamic, human-in-the-loop environments. Over the past decades, a variety of architectures have been proposed for generating and controlling intelligent behavior of robots within a single robot platform mostly under centralized control. Responding to the growing need for large-scale service robotics applications under varying environmental conditions, new paradigms for the coordination and control of robots have been required in recent years. This book will examine several possible paradigms and explore their distinguishing features that enable robots to create emergent cooperative behavior in a fully or human-assisted semi-autonomous way. Those paradigms are investigated and analyzed on the theoretical grounds and experimental confirmation under real world conditions. As standalone autonomy is still more of a far-reaching goal, we shift our focus of attention toward networked autonomy. Provided that the compatibility and interoperability of network elements are guaranteed, networked autonomy could be considered to be more efficient and scalable at implementing various sophisticated robot applications than standalone autonomy. It will also exhibit high potential for future scientific breakthrough related to inter-robot and human-robot interaction and cooperation

This book focuses primarily on latest techniques that proved successful for the control of robots in the current and near future networked environments, as well as try to bring to light difficulties that traditional standalone control approaches have faced due to lack of information available through the network. It has recently been demonstrated that a pervasive network environment can be used to give robots the ability to integrate information from diverse data sources both within and outside their own platforms into a single coherent framework. An integrated information infrastructure can then be built and shared by robots cooperating with each other and/or with humans. Specifically, the contributors discuss the principles and techniques that enable distributed, yet structured information to control the behavior of robots in the real world in more efficient and systematic ways. A notable example of network-based smart infrastructures includes cyber-physical systems that integrate the system’s computational and physical resources. Along these lines, this book will show some of the most recent and breathtaking examples of inter-robot and human-robot networks operating in real environments. I believe that those examples will help readers understand and examine how and why various forms of cooperative interactions emerge and flourish in the robot-robot and robot-human environment.

Specifically, when robots are expected to exhibit some form of intelligence, they must be provided with information with regard to the state of the world, either at a local or global level, from which they make the best possible decisions about executions. The traditional approach integrates a priori information presumed by users or programmers, as well as acquired information through onboard sensing, to aid the robot’s decision making process. It overburdens processing power, as entities in the world increase in complexity and require a vast amount of storage of data. Ubiquitous computing technologies provide a more convenient and efficient environment that facilitates the reshaping of the current monolithic architecture of behavior control. If the world becomes structurized in the sense of information management by tagging with appropriate information, robots will be effortlessly connected to the intrinsic features of the world. Moreover, if robots are aware of all the changing states of the world, then they will be able to exhibit an autonomous intelligence. The technical challenge is 1) how to build a network infrastructure that will let robots share information about the world in which they exist, 2) how to develop flexible control architectures and networking technologies for coordinating the actions of large numbers of distributed sensors and devices interacting with the world, 3) how to attain control over all the states of the entities in the world, and 4) how to automate the process of controlling behavior of robots in the world pre-populated with various types of information. The features of the coordinated control and information architectures proposed in this book will push robots toward achieving greater autonomy and decision that enable them to configure and adapt their behavior on demand in accordance with the directions of information management embedded in the surrounding environment. Those proposed architectures can be readily adopted in dynamically varying environments, helping ease the cost and complexity of real-time planning and execution of robot missions. Furthermore, robots can respond more effectively to hidden or explicit intentions of human interaction. Practical strategies for implementation build upon such emerging areas as ubiquitous computing, ambient intelligence, smart environments, distributed systems, wireless sensor networks, ontology, cloud computing, and so on.

This book will be of interest to the academic and industry professionals from the field of network control architecture, distributed multi-agent systems, artificial intelligence, behavior generation and control, robot-robot and human-robot interactions, and network applications design, whose attention is devoted specifically to the integration of heterogeneous information systems.

However, the author confirms that this eBook has no acknowledgment and conflict of interest.

Nak Young Chong
Japan Advanced Institute of Science and Technology
Japan

List of Contributors

Editor(s):
Nak Y. Chong
Japan Advanced Institute of Science and Technology
Japan




Contributor(s):
Gerard McKee
School of Systems Engineering
University of Reading, Whiteknights Campus, Reading
Berkshire, RG6 6AY
United Kingdom


Gerard McKee
Faculty of Computer Science and IT
University of Baze
Abuja
Nigeria


Dezhen Song
Department of Computer Science and Engineering
Texas A&M University
College Station
TX, 77843
USA


Fulvio Mastrogiovanni
Department of Computer, Communication and System Sciences
Faculty of Engineering, University of Genova
Via Opera Pia 13
Genova, 16145
Italy


Geunho Lee
School of Information Science
Japan Advanced Institute of Science and Technology
Ishikawa
Japan


Kevin Lynch
Department of Mechanical Engineering
Northwestern University
Evanston
IL, 60208
USA


Lichuan Liu
Department of Electrical Engineering
Northern Illinois University
DeKlab
IL, DeKlab
USA


Takeshi Sasaki
Institute of Industrial Science
The University of Tokyo
Tokyo, 108-8548
Japan


Bong K. Kim
Intelligent Systems Research Institute
National Institute of Advanced Industrial Science and Technology (AIST)
Tsukuba
Ibaraki, 305-8561
Japan


Wonpil Yu
Robot Research Department
Electronics and Telecommunications Research Institut
Daejeon
Korea


Dongjun Lee
Department of Mechanical, Aerospace & Biomedical Engineering
University of Tennessee
Knoxville
TN, 37996
USA


Jee-Hwan Ryu
School of Mechanical Engineering
Korea University of Technology and Education
Cheonan
Chungnam
Korea


Nak Y. Chong
School of Information Science
Japan Advanced Institute of Science and Technology
1-1 Asahidai
Nomi
Ishikawa, 923-1292
Japan




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