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Author: Olivier Sigaud
Publisher: Springer Science & Business Media
ISBN: 3642051804
Category : Computers
Languages : en
Pages : 534
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Book Description
From an engineering standpoint, the increasing complexity of robotic systems and the increasing demand for more autonomously learning robots, has become essential. This book is largely based on the successful workshop “From motor to interaction learning in robots” held at the IEEE/RSJ International Conference on Intelligent Robot Systems. The major aim of the book is to give students interested the topics described above a chance to get started faster and researchers a helpful compandium.
Author: Olivier Sigaud
Publisher: Springer Science & Business Media
ISBN: 3642051804
Category : Computers
Languages : en
Pages : 534
Get Book Here
Book Description
From an engineering standpoint, the increasing complexity of robotic systems and the increasing demand for more autonomously learning robots, has become essential. This book is largely based on the successful workshop “From motor to interaction learning in robots” held at the IEEE/RSJ International Conference on Intelligent Robot Systems. The major aim of the book is to give students interested the topics described above a chance to get started faster and researchers a helpful compandium.
Author: Olivier Sigaud
Publisher: Springer
ISBN: 9783642262326
Category : Computers
Languages : en
Pages : 538
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Book Description
From an engineering standpoint, the increasing complexity of robotic systems and the increasing demand for more autonomously learning robots, has become essential. This book is largely based on the successful workshop “From motor to interaction learning in robots” held at the IEEE/RSJ International Conference on Intelligent Robot Systems. The major aim of the book is to give students interested the topics described above a chance to get started faster and researchers a helpful compandium.
Author: Aude Billard
Publisher: MIT Press
ISBN: 0262367017
Category : Technology & Engineering
Languages : en
Pages : 425
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Book Description
Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.
Author: Nehal Bhuta
Publisher: Cambridge University Press
ISBN: 1316720993
Category : Law
Languages : en
Pages : 421
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Book Description
The intense and polemical debate over the legality and morality of weapons systems to which human cognitive functions are delegated (up to and including the capacity to select targets and release weapons without further human intervention) addresses a phenomena which does not yet exist but which is widely claimed to be emergent. This groundbreaking collection combines contributions from roboticists, legal scholars, philosophers and sociologists of science in order to recast the debate in a manner that clarifies key areas and articulates questions for future research. The contributors develop insights with direct policy relevance, including who bears responsibility for autonomous weapons systems, whether they would violate fundamental ethical and legal norms, and how to regulate their development. It is essential reading for those concerned about this emerging phenomenon and its consequences for the future of humanity.
Author: Sonia Chernova
Publisher: Morgan & Claypool Publishers
ISBN: 1627052003
Category : Computers
Languages : en
Pages : 123
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Book Description
Learning from Demonstration (LfD) explores techniques for learning a task policy from examples provided by a human teacher. The field of LfD has grown into an extensive body of literature over the past 30 years, with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks. Additionally, we have recently seen a focus on gathering data from non-expert human teachers (i.e., domain experts but not robotics experts). In this book, we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers. We begin, in the introduction, with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system. Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners. Chapter 3 walks through an LfD interaction, surveying the design choices one makes and state of the art approaches in prior work. First, is the choice of input, how the human teacher interacts with the robot to provide demonstrations. Next, is the choice of modeling technique. Currently, there is a dichotomy in the field between approaches that model low-level motor skills and those that model high-level tasks composed of primitive actions. We devote a chapter to each of these. Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model. And finally, Chapter 8 provides best practices for evaluation of LfD systems, with a focus on how to approach experiments with human subjects in this domain.
Author: Angelo Cangelosi
Publisher: MIT Press
ISBN: 0262028018
Category : Technology & Engineering
Languages : en
Pages : 427
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Book Description
A comprehensive overview of an interdisciplinary approach to robotics that takes direct inspiration from the developmental and learning phenomena observed in children's cognitive development. Developmental robotics is a collaborative and interdisciplinary approach to robotics that is directly inspired by the developmental principles and mechanisms observed in children's cognitive development. It builds on the idea that the robot, using a set of intrinsic developmental principles regulating the real-time interaction of its body, brain, and environment, can autonomously acquire an increasingly complex set of sensorimotor and mental capabilities. This volume, drawing on insights from psychology, computer science, linguistics, neuroscience, and robotics, offers the first comprehensive overview of a rapidly growing field. After providing some essential background information on robotics and developmental psychology, the book looks in detail at how developmental robotics models and experiments have attempted to realize a range of behavioral and cognitive capabilities. The examples in these chapters were chosen because of their direct correspondence with specific issues in child psychology research; each chapter begins with a concise and accessible overview of relevant empirical and theoretical findings in developmental psychology. The chapters cover intrinsic motivation and curiosity; motor development, examining both manipulation and locomotion; perceptual development, including face recognition and perception of space; social learning, emphasizing such phenomena as joint attention and cooperation; language, from phonetic babbling to syntactic processing; and abstract knowledge, including models of number learning and reasoning strategies. Boxed text offers technical and methodological details for both psychology and robotics experiments.
Author: Albert Ali Salah
Publisher: Springer
ISBN: 3642340148
Category : Computers
Languages : en
Pages : 184
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Book Description
This book constitutes the refereed proceedings of the Third Workshop on Human Behavior Understanding, HBU 2012, held in Vilamoura, Portugal, in October 2012. The 14 revised papers presented were carefully reviewed and selected from 31 submissions. The papers are organized in topical sections on sensing human behavior; social and affective signals; human-robot interaction; imitation and learning from demonstration.
Author: Roland Pfister
Publisher: Frontiers E-books
ISBN: 288919146X
Category :
Languages : en
Pages : 181
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Book Description
Author: Norbert M. Seel
Publisher: Springer Science & Business Media
ISBN: 1441914277
Category : Education
Languages : en
Pages : 3643
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Book Description
Over the past century, educational psychologists and researchers have posited many theories to explain how individuals learn, i.e. how they acquire, organize and deploy knowledge and skills. The 20th century can be considered the century of psychology on learning and related fields of interest (such as motivation, cognition, metacognition etc.) and it is fascinating to see the various mainstreams of learning, remembered and forgotten over the 20th century and note that basic assumptions of early theories survived several paradigm shifts of psychology and epistemology. Beyond folk psychology and its naïve theories of learning, psychological learning theories can be grouped into some basic categories, such as behaviorist learning theories, connectionist learning theories, cognitive learning theories, constructivist learning theories, and social learning theories. Learning theories are not limited to psychology and related fields of interest but rather we can find the topic of learning in various disciplines, such as philosophy and epistemology, education, information science, biology, and – as a result of the emergence of computer technologies – especially also in the field of computer sciences and artificial intelligence. As a consequence, machine learning struck a chord in the 1980s and became an important field of the learning sciences in general. As the learning sciences became more specialized and complex, the various fields of interest were widely spread and separated from each other; as a consequence, even presently, there is no comprehensive overview of the sciences of learning or the central theoretical concepts and vocabulary on which researchers rely. The Encyclopedia of the Sciences of Learning provides an up-to-date, broad and authoritative coverage of the specific terms mostly used in the sciences of learning and its related fields, including relevant areas of instruction, pedagogy, cognitive sciences, and especially machine learning and knowledge engineering. This modern compendium will be an indispensable source of information for scientists, educators, engineers, and technical staff active in all fields of learning. More specifically, the Encyclopedia provides fast access to the most relevant theoretical terms provides up-to-date, broad and authoritative coverage of the most important theories within the various fields of the learning sciences and adjacent sciences and communication technologies; supplies clear and precise explanations of the theoretical terms, cross-references to related entries and up-to-date references to important research and publications. The Encyclopedia also contains biographical entries of individuals who have substantially contributed to the sciences of learning; the entries are written by a distinguished panel of researchers in the various fields of the learning sciences.
Author: Jean-Paul Laumond
Publisher: Springer
ISBN: 3319257390
Category : Technology & Engineering
Languages : en
Pages : 433
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Book Description
How and why to write a movement? Who is the writer? Who is the reader? They may be choreographers working with dancers. They may be roboticists programming robots. They may be artists designing cartoons in computer animation. In all such fields the purpose is to express an intention about a dance, a specific motion or an action to perform, in terms of intelligible sequences of elementary movements, as a music score that would be devoted to motion representation. Unfortunately there is no universal language to write a motion. Motion languages live together in a Babel tower populated by biomechanists, dance notators, neuroscientists, computer scientists, choreographers, roboticists. Each community handles its own concepts and speaks its own language. The book accounts for this diversity. Its origin is a unique workshop held at LAAS-CNRS in Toulouse in 2014. Worldwide representatives of various communities met there. Their challenge was to reach a mutual understanding allowing a choreographer to access robotics concepts, or a computer scientist to understand the subtleties of dance notation. The liveliness of this multidisciplinary meeting is reflected by the book thank to the willingness of authors to share their own experiences with others.
