Approaches to Probabilistic Model Learning for Mobile Manipulation Robots, J?rgen Sturm
Автор: Thrun, Sebastian Название: Probabilistic robotics ISBN: 0262201623 ISBN-13(EAN): 9780262201629 Издательство: MIT Press Рейтинг: Цена: 14390.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An introduction to the techniques and algorithms of the newest field in robotics.
Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.
Автор: Judea Pearl Название: Probabilistic Reasoning in Intelligent Systems, ISBN: 1558604790 ISBN-13(EAN): 9781558604797 Издательство: Elsevier Science Рейтинг: Цена: 9599.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Probabilistic Reasoning in Intelligent Systems is a complete and accessible account of the theoretical foundations and computational methods that underlie plausible reasoning under uncertainty. The author provides a coherent explication of probability as a language for reasoning with partial belief and offers a unifying perspective on other AI approaches to uncertainty, such as the Dempster-Shafer formalism, truth maintenance systems, and nonmonotonic logic.
The author distinguishes syntactic and semantic approaches to uncertainty--and offers techniques, based on belief networks, that provide a mechanism for making semantics-based systems operational. Specifically, network-propagation techniques serve as a mechanism for combining the theoretical coherence of probability theory with modern demands of reasoning-systems technology: modular declarative inputs, conceptually meaningful inferences, and parallel distributed computation. Application areas include diagnosis, forecasting, image interpretation, multi-sensor fusion, decision support systems, plan recognition, planning, speech recognition--in short, almost every task requiring that conclusions be drawn from uncertain clues and incomplete information.
Probabilistic Reasoning in Intelligent Systems will be of special interest to scholars and researchers in AI, decision theory, statistics, logic, philosophy, cognitive psychology, and the management sciences. Professionals in the areas of knowledge-based systems, operations research, engineering, and statistics will find theoretical and computational tools of immediate practical use. The book can also be used as an excellent text for graduate-level courses in AI, operations research, or applied probability.
Описание: Dealing with visual perception in robots and its applications to manipulation and imitation, this monograph focuses on stereo-based methods and systems for object recognition and 6 DoF pose estimation as well as for marker-less human motion capture.
Описание: Dealing with visual perception in robots and its applications to manipulation and imitation, this monograph focuses on stereo-based methods and systems for object recognition and 6 DoF pose estimation as well as for marker-less human motion capture.
The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts and methodologies adopted in dependability analysis, the book discusses the main features of PGM formalisms (like Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model languages.
Methodologies for deriving PGMs from standard dependability formalisms will be introduced, by pointing out tools able to support such a process. Several case studies will be presented and analyzed to support the suitability of the use of PGMs in the study of dependable systems.
Автор: Pierre Bessi?re; Christian Laugier; Roland Siegwar Название: Probabilistic Reasoning and Decision Making in Sensory-Motor Systems ISBN: 3642097847 ISBN-13(EAN): 9783642097843 Издательство: Springer Рейтинг: Цена: 26120.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The chapters contain a sizable segment of cognitive systems research in Europe. Contributions come from leading academic institutions within the European projects Bayesian Inspired Brain and Artifact (BIBA) and Bayesian Approach to Cognitive Systems (BACS).
Описание: This book proposes the formulation of an efficient methodology that estimates energy system uncertainty and predicts Remaining Useful Life (RUL) accurately with significantly reduced RUL prediction uncertainty.
Автор: Manfred Dietrich; Joachim Haase Название: Process Variations and Probabilistic Integrated Circuit Design ISBN: 1489988602 ISBN-13(EAN): 9781489988607 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on qualitative and quantitative insight, this volume presents the technological, physical, and mathematical fundamentals for a design paradigm shift for microelectronic circuits. The text explores design flow variations to establish different variants while optimizing the overall design.
Описание: This book presents novel learning techniques that enable mobile platforms with one or more robotic manipulators to autonomously adapt to new or changing situations.
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