Author: Ronald C. Arkin
Publisher: MIT Press
Release Date: 1998
foreword by Michael Arbib "Hard to put down and necessary to know -- Arkin's book provides a comprehensive intellectual history of robots and a thorough compilation of robotic organizational paradigms from reflexes through social interaction." -- Chris Brown, Professor of Computer Science, University of Rochester This introduction to the principles, design, and practice of intelligent behavior-based autonomous robotic systems is the first true survey of this robotics field. The author presents the tools and techniques central to the development of this class of systems in a clear and thorough manner. Following a discussion of the relevant biological and psychological models of behavior, he covers the use of knowledge and learning in autonomous robots, behavior-based and hybrid robot architectures, modular perception, robot colonies, and future trends in robot intelligence. The text throughout refers to actual implemented robots and includes many pictures and descriptions of hardware, making it clear that these are not abstract simulations, but real machines capable of perception, cognition, and action.
Risk detection and cyber security play a vital role in the use and success of contemporary computing. By utilizing the latest technological advances, more effective prevention techniques can be developed to protect against cyber threats. Detecting and Mitigating Robotic Cyber Security Risks is an essential reference publication for the latest research on new methodologies and applications in the areas of robotic and digital security. Featuring extensive coverage on a broad range of topics, such as authentication techniques, cloud security, and mobile robotics, this book is ideally designed for students, researchers, scientists, and engineers seeking current research on methods, models, and implementations of optimized security in digital contexts.
Author: David McFarland
Publisher: MIT Press
Release Date: 1993
Intelligence takes many forms. This exciting study explores the novel insight, basedon well-established ethological principles, that animals, humans, and autonomous robots can all beanalyzed as multi-task autonomous control systems. Biological adaptive systems, the authors argue,can in fact provide a better understanding of intelligence and rationality than that provided bytraditional AI.In this technically sophisticated, clearly written investigation of robot-animalanalogies, McFarland and Bösser show that a bee's accuracy in navigating on a cloudy day and amoth's simple but effective hearing mechanisms have as much to teach us about intelligent behavioras human models. In defining intelligent behavior, what matters is the behavioral outcome, not thenature of the mechanism by which the outcome is achieved. Similarly, in designing robots capable ofintelligent behavior, what matters is the behavioral outcome.McFarland and Bösser address theproblem of how to assess the consequences of robot behavior in a way that is meaningful in terms ofthe robot's intended role, comparing animal and robot in relation to rational behavior, goalseeking, task accomplishment, learning, and other important theoretical issues.David McFarland isReader in Animal Behaviour at the University of Oxford. Thomas Bösser is Head of the Man MachineResearch Group at Westfälische Wilhelms Universität, in Münster, and a partner in the consultingfirm Advanced Concepts.
Author: Luc Steels
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
The NATO sponsored Advanced Study Institute 'The Biology and Tech nology of Intelligent Autonomous Agents' was an extraordinary event. For two weeks it brought together the leading proponents of the new behavior oriented approach to Artificial Intelligence in Castel Ivano near Trento. The goal of the meeting was to establish a solid scientific and technological foun dation for the field of intelligent autonomous agents with a bias towards the new methodologies and techniques that have recently been developed in Ar tificial Intelligence under the strong influence of biology. Major themes of the conference were: bottom-up AI research, artificial life, neural networks and techniques of emergent functionality. The meeting was such an extraordinary event because it not only featured very high quality lectures on autonomous agents and the various fields feeding it, but also robot laboratories which were set up by the MIT AI laboratory (with a lab led by Rodney Brooks) and the VUB AI laboratory (with labs led by Tim Smithers and Luc Steels). This way the participants could also gain practical experience and discuss in concreto what the difficulties and achievements were of different approaches. In fact, the meeting has been such a success that a follow up meeting is planned for September 1995 in Monte Verita (Switzerland). This meeting is organised by Rolf Pfeifer (University of Zurich).
Author: Robin Murphy
Publisher: MIT Press
Release Date: 2000
A comprehensive introduction to the AI approach to robotics, combining theoretical rigor and practical applications; with case studies and exercises. This text covers all the material needed to understand the principles behind the AI approach to robotics and to program an artificially intelligent robot for applications involving sensing, navigation, planning, and uncertainty. Robin Murphy is extremely effective at combining theoretical and practical rigor with a light narrative touch. In the overview, for example, she touches upon anthropomorphic robots from classic films and science fiction stories before delving into the nuts and bolts of organizing intelligence in robots. Following the overview, Murphy contrasts AI and engineering approaches and discusses what she calls the three paradigms of AI robotics: hierarchical, reactive, and hybrid deliberative/reactive. Later chapters explore multiagent scenarios, navigation and path-planning for mobile robots, and the basics of computer vision and range sensing. Each chapter includes objectives, review questions, and exercises. Many chapters contain one or more case studies showing how the concepts were implemented on real robots. Murphy, who is well known for her classroom teaching, conveys the intellectual adventure of mastering complex theoretical and technical material. An Instructor's Manual including slides, solutions, sample tests, and programming assignments is available to qualified professors who are considering using the book or who are using the book for class use.
Designing Autonomous Agents provides a summary and overview of the radically different architectures that have been developed over the past few years for organizing robots. These architectures have led to major breakthroughs that promise to revolutionize the study of autonomous agents and perhaps artificial intelligence in general.The new architectures emphasize more direct coupling of sensing to action, distributedness and decentralization, dynamic interaction with the environment, and intrinsic mechanisms to cope with limited resources and incomplete knowledge. The research discussed here encompasses such important ideas as emergent functionality, task-level decomposition, and reasoning methods such as analogical representations and visual operations that make the task of perception more realistic.Pattie Maes is Research Associate at the Artificial Intelligence Laboratory of the University of Brussels and Visiting Faculty Member at the Artificial Intelligence Laboratory at MIT.Contents: A Biological Perspective on Autonomous Agent Design, Randall D. Beer, Hillel J. Chiel, Leon S. Sterling. Elephants Don't Play Chess, Rodney A. Brooks. What Are Plans For? Philip E. Agre and David Chapman. Action and Planning in Embedded Agents, Leslie Pack Kaelbling and Stanley J. Rosenschein. Situated Agents Can Have Goals, Pattie Maes. Exploiting Analogical Representations, Luc Steels. Internalized Plans: A Representation for Action Resources, David W. Payton. Integrating Behavioral, Perceptual, and World Knowledge in Reactive Navigation, Ronald C. Arkin. Symbol Grounding via a Hybrid Architecture in an Autonomous Assembly System, Chris Malcolm and Tim Smithers. Animal Behavior as a Paradigm for Developing Robot Autonomy, Tracy L. Anderson and Max Donath.
Author: Rodney Allen Brooks
Publisher: MIT Press
Release Date: 1999
Until the mid-1980s, AI researchers assumed that an intelligent system doing high-level reasoning was necessary for the coupling of perception and action. In this traditional model, cognition mediates between perception and plans of action. Realizing that this core AI, as it was known, was illusory, Rodney A. Brooks turned the field of AI on its head by introducing the behavior-based approach to robotics. The cornerstone of behavior-based robotics is the realization that the coupling of perception and action gives rise to all the power of intelligence and that cognition is only in the eye of an observer. Behavior-based robotics has been the basis of successful applications in entertainment, service industries, agriculture, mining, and the home. It has given rise to both autonomous mobile robots and more recent humanoid robots such as Brooks' Cog. This book represents Brooks' initial formulation of and contributions to the development of the behavior-based approach to robotics. It presents all of the key philosophical and technical ideas that put this "bottom-up" approach at the forefront of current research in not only AI but all of cognitive science.
Author: Maja J. Matarić
Publisher: MIT Press
Release Date: 2007
1. What is a robot? 2. Where do robots come from? 3. What's in a robot? 4. Arms, legs, wheels, tracks, and really drives them 5. Move it! 6. Grasping at straws 7. What's going on? 8. Switch on ghe light 9. Sonars, lasers, and cameras 10. Stay in control 11. The building bolcks of control 12. What's in your head? 13. Think hard, act later 14. Don't think, react! 15. Think and act separately, in parallel 16. Think the way you act 17. Making your robot behave 18. When the unexpected happens 19. Going places 20. Go, team! 21. Things keep getting better 22. Where to next?
The second edition of this handbook provides a state-of-the-art cover view on the various aspects in the rapidly developing field of robotics. Reaching for the human frontier, robotics is vigorously engaged in the growing challenges of new emerging domains. Interacting, exploring, and working with humans, the new generation of robots will increasingly touch people and their lives. The credible prospect of practical robots among humans is the result of the scientific endeavour of a half a century of robotic developments that established robotics as a modern scientific discipline. The ongoing vibrant expansion and strong growth of the field during the last decade has fueled this second edition of the Springer Handbook of Robotics. The first edition of the handbook soon became a landmark in robotics publishing and won the American Association of Publishers PROSE Award for Excellence in Physical Sciences & Mathematics as well as the organization’s Award for Engineering & Technology. The second edition of the handbook, edited by two internationally renowned scientists with the support of an outstanding team of seven part editors and more than 200 authors, continues to be an authoritative reference for robotics researchers, newcomers to the field, and scholars from related disciplines. The contents have been restructured to achieve four main objectives: the enlargement of foundational topics for robotics, the enlightenment of design of various types of robotic systems, the extension of the treatment on robots moving in the environment, and the enrichment of advanced robotics applications. Further to an extensive update, fifteen new chapters have been introduced on emerging topics, and a new generation of authors have joined the handbook’s team. A novel addition to the second edition is a comprehensive collection of multimedia references to more than 700 videos, which bring valuable insight into the contents. The videos can be viewed directly augmented into the text with a smartphone or tablet using a unique and specially designed app. Springer Handbook of Robotics Multimedia Extension Portal: http://handbookofrobotics.org/
Author: Been-Chian Chien
Publisher: Springer Science & Business Media
Release Date: 2009-06-09
The International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems (IEA/AIE), always sponsored by the International So- ety of Applied Intelligence (ISAI), emphasizes applications of applied intelligent systems to solve real-life problems in all areas. It is held every year and has become one of the biggest and most important academic activities concerning the theory and applications of intelligent systems in the world. The IEA/AIE 2009 conference was hosted by the National University of Tainan and National University of Kaohsiung in Taiwan. This was the first time that the IEA/AIE conference was held in Taiwan. We received 286 papers from all parts of the world. Only 84 papers were selected for publication in this volume of LNAI proceedings. Each paper was reviewed by at least two anonymous referees to assure the high quality. We would like to express our sincere thanks to the Program Committee members and all the reviewers for their hard work, which helped us to select the highest quality papers for the conference. These papers highlight opportunities and challenges for the next generation of applied int- ligence and reveal technological innovations in real applications.
By the mid-1980s researchers from artificial intelligence, computer science, brain and cognitive science, and psychology realized that the idea of computers as intelligent machines was inappropriate. The brain does not run "programs"; it does something entirely different. But what? Evolutionary theory says that the brain has evolved not to do mathematical proofs but to control our behavior, to ensure our survival. Researchers now agree that intelligence always manifests itself in behavior -- thus it is behavior that we must understand. An exciting new field has grown around the study of behavior-based intelligence, also known as embodied cognitive science, "new AI," and "behavior-based AI."This book provides a systematic introduction to this new way of thinking. After discussing concepts and approaches such as subsumption architecture, Braitenberg vehicles, evolutionary robotics, artificial life, self-organization, and learning, the authors derive a set of principles and a coherent framework for the study of naturally and artificially intelligent systems, or autonomous agents. This framework is based on a synthetic methodology whose goal is understanding by designing and building.The book includes all the background material required to understand the principles underlying intelligence, as well as enough detailed information on intelligent robotics and simulated agents so readers can begin experiments and projects on their own. The reader is guided through a series of case studies that illustrate the design principles of embodied cognitive science.
Providing a guided tour of the pioneering work and major technical issues, Multiagent Robotic Systems addresses learning and adaptation in decentralized autonomous robots. Its systematic examination demonstrates the interrelationships between the autonomy of individual robots and the emerged global behavior properties of a group performing a cooperative task. The author also includes descriptions of the essential building blocks of the architecture of autonomous mobile robots with respect to their requirement on local behavioral conditioning and group behavioral evolution. After reading this book you will be able to fully appreciate the strengths and usefulness of various approaches in the development and application of multiagent robotic systems. It covers: Why and how to develop and experimentally test the computational mechanisms for learning and evolving sensory-motor control behaviors in autonomous robots How to design and develop evolutionary algorithm-based group behavioral learning mechanisms for the optimal emergence of group behaviors How to enable group robots to converge to a finite number of desirable task states through group learning What are the effects of the local learning mechanisms on the emergent global behaviors How to use decentralized, self-organizing autonomous robots to perform cooperative tasks in an unknown environment Earlier works have focused primarily on how to navigate in a spatially unknown environment, given certain predefined motion behaviors. What is missing, however, is an in-depth look at the important issues on how to effectively obtain such behaviors in group robots and how to enable behavioral learning and adaptation at the group level. Multiagent Robotic Systems examines the key methodological issues and gives you an understanding of the underlying computational models and techniques for multiagent systems.