ISBN: 9783319020051 - probabilistic approaches for robotic perception: 91 (11 risultati)

hardcover. Condizione: New. Brand New Book.

1st edition. A nice copy in tight binding. Used - Very Good. VG hardback in laminated boards (no dust jacket) Used - Very Good. VG hardback in laminated boards (no dust jacket).

Buch. Condizione: 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'.…

Condizione: New. pp. xxx + 242.

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Condizione: new. Questo è un articolo print on demand.

Buch. Condizione: 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.…

Gebunden. Condizione: 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.…

Buch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 272 pp. Englisch.…

Condizione: New. Print on Demand pp. xxx + 242 89 Illus. (79 Col.).

Condizione: New. PRINT ON DEMAND pp. xxx + 242.