Articles liés à Probabilistic Approaches for Robotic Perception
Synopsis
This book tries to address the following questions: How should the uncertainty and incompleteness inherent to sensing the environment be represented and modelled in a way that will increase the autonomy of a robot? How should a robotic system perceive, infer, decide and act efficiently? These are two of the challenging questions robotics community and robotic researchers have been facing.
The development of robotic domain by the 1980s spurred the convergence of automation to autonomy, and the field of robotics has consequently converged towards the field of artificial intelligence (AI). Since the end of that decade, the general public's imagination has been stimulated by high expectations on autonomy, where AI and robotics try to solve difficult cognitive problems through algorithms developed from either philosophical and anthropological conjectures or incomplete notions of cognitive reasoning. Many of these developments do not unveil even a few of the processes through which biological organisms solve these same problems with little energy and computing resources. The tangible results of this research tendency were many robotic devices demonstrating good performance, but only under well-defined and constrained environments. The adaptability to different and more complex scenarios was very limited.
In this book, the application of Bayesian models and approaches are described in order to develop artificial cognitive systems that carry out complex tasks in real world environments, spurring the design of autonomous, intelligent and adaptive artificial systems, inherently dealing with uncertainty and the "irreducible incompleteness of models".
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Présentation de l'éditeur
In this book, the application of Bayesian models are described in order to develop artificial cognitive systems that carry out complex tasks in real world environments, spurring the design of autonomous, intelligent and adaptive artificial systems.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Probabilistic Approaches to Robotic Perception
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Springer International Publishing, 2013
ISBN 10 : 3319020056
ISBN 13 : 9783319020051
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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides an overview of robotic perception systems and how human behavior has been a challenge for robotic researchersIntroduction to the use of probabilistic tools to implement robotic perception, adding to it working examples and case studies. N° de réf. du vendeur 4496323
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Probabilistic approaches to robotic perception
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Springer, 2014
ISBN 10 : 3319020056
ISBN 13 : 9783319020051
Ancien ou d'occasion
Couverture rigide
Vendeur : Cotswold Internet Books, Cheltenham, Royaume-Uni
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1st edition. A nice copy in tight binding. Used - Very Good. VG hardback in laminated boards (no dust jacket). N° de réf. du vendeur BOOKS243699I
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Probabilistic Approaches to Robotic Perception (Springer Tracts in Advanced Robotics, 91)
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hardcover. Etat : New. Brand New Book. N° de réf. du vendeur 64208
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Probabilistic Approaches to Robotic Perception
Edité par
Springer International Publishing, 2013
ISBN 10 : 3319020056
ISBN 13 : 9783319020051
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book tries to address the following questions: How should the uncertainty and incompleteness inherent to sensing the environment be represented and modelled in a way that will increase the autonomy of a robot How should a robotic system perceive, infer, decide and act efficiently These are two of the challenging questions robotics community and robotic researchers have been facing.The development of robotic domain by the 1980s spurred the convergence of automation to autonomy, and the field of robotics has consequently converged towards the field of artificial intelligence (AI). Since the end of that decade, the general public's imagination has been stimulated by high expectations on autonomy, where AI and robotics try to solve difficult cognitive problems through algorithms developed from either philosophical and anthropological conjectures or incomplete notions of cognitive reasoning. Many of these developments do not unveil even a few of the processes through which biological organisms solve these same problems with little energy and computing resources. The tangible results of this research tendency were many robotic devices demonstrating good performance, but only under well-defined and constrained environments. The adaptability to different and more complex scenarios was very limited.In this book, the application of Bayesian models and approaches are described in order to develop artificial cognitive systems that carry out complex tasks in real world environments, spurring the design of autonomous, intelligent and adaptive artificial systems, inherently dealing with uncertainty and the 'irreducible incompleteness of models'. N° de réf. du vendeur 9783319020051
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Probabilistic Approaches to Robotic Perception
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Springer International Publishing Sep 2013, 2013
ISBN 10 : 3319020056
ISBN 13 : 9783319020051
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book tries to address the following questions: How should the uncertainty and incompleteness inherent to sensing the environment be represented and modelled in a way that will increase the autonomy of a robot How should a robotic system perceive, infer, decide and act efficiently These are two of the challenging questions robotics community and robotic researchers have been facing.The development of robotic domain by the 1980s spurred the convergence of automation to autonomy, and the field of robotics has consequently converged towards the field of artificial intelligence (AI). Since the end of that decade, the general public's imagination has been stimulated by high expectations on autonomy, where AI and robotics try to solve difficult cognitive problems through algorithms developed from either philosophical and anthropological conjectures or incomplete notions of cognitive reasoning. Many of these developments do not unveil even a few of the processes through which biological organisms solve these same problems with little energy and computing resources. The tangible results of this research tendency were many robotic devices demonstrating good performance, but only under well-defined and constrained environments. The adaptability to different and more complex scenarios was very limited.In this book, the application of Bayesian models and approaches are described in order to develop artificial cognitive systems that carry out complex tasks in real world environments, spurring the design of autonomous, intelligent and adaptive artificial systems, inherently dealing with uncertainty and the 'irreducible incompleteness of models'. 272 pp. Englisch. N° de réf. du vendeur 9783319020051
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Probabilistic Approaches to Robotic Perception
ISBN 10 : 3319020056
ISBN 13 : 9783319020051
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Buch. Etat : Neu. Neuware -This book tries to address the following questions: How should the uncertainty and incompleteness inherent to sensing the environment be represented and modelled in a way that will increase the autonomy of a robot How should a robotic system perceive, infer, decide and act efficiently These are two of the challenging questions robotics community and robotic researchers have been facing.The development of robotic domain by the 1980s spurred the convergence of automation to autonomy, and the field of robotics has consequently converged towards the field of artificial intelligence (AI). Since the end of that decade, the general public¿s imagination has been stimulated by high expectations on autonomy, where AI and robotics try to solve difficult cognitive problems through algorithms developed from either philosophical and anthropological conjectures or incomplete notions of cognitive reasoning. Many of these developments do not unveil even a few of the processes through which biological organisms solve these same problems with little energy and computing resources. The tangible results of this research tendency were many robotic devices demonstrating good performance, but only under well-defined and constrained environments. The adaptability to different and more complex scenarios was very limited. In this book, the application of Bayesian models and approaches are described in order to develop artificial cognitive systems that carry out complex tasks in real world environments, spurring the design of autonomous, intelligent and adaptive artificial systems, inherently dealing with uncertainty and the ¿irreducible incompleteness of models¿.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 272 pp. Englisch. N° de réf. du vendeur 9783319020051
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Probabilistic Approaches to Robotic Perception (Springer Tracts in Advanced Robotics (91))
Edité par
Springer, 2013
ISBN 10 : 3319020056
ISBN 13 : 9783319020051
Ancien ou d'occasion
Couverture rigide
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
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Hardcover. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA79733190200566
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