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In den WarenkorbZustand: New. In.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 114,52
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
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In den WarenkorbPaperback. Zustand: Brand New. 2011 edition. 172 pages. 8.43x5.85x0.73 inches. In Stock.
Taschenbuch. Zustand: Neu. Random Finite Sets for Robot Mapping & SLAM | New Concepts in Autonomous Robotic Map Representations | John Stephen Mullane (u. a.) | Taschenbuch | xxiv | Englisch | 2013 | Springer | EAN 9783642268311 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer, Berlin, Springer, 2013
ISBN 10: 3642268315 ISBN 13: 9783642268311
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The monograph written by John Mullane, Ba-Ngu Vo, Martin Adams and Ba-Tuong Vo is devoted to the field of autonomous robot systems, which have been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the problem of representing the environment and its uncertainty in terms of feature based maps. Random Finite Sets are adopted as the fundamental tool to represent a map, and a general framework is proposed for feature management, data association and state estimation. The approaches are tested in a number of experiments on both ground based and marine based facilities.
Sprache: Englisch
Verlag: Springer, Springer Spektrum, 2011
ISBN 10: 3642213898 ISBN 13: 9783642213892
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - The monograph written by John Mullane, Ba-Ngu Vo, Martin Adams and Ba-Tuong Vo is devoted to the field of autonomous robot systems, which have been receiving a great deal of attention by the research community in the latest few years. The contents are focused on the problem of representing the environment and its uncertainty in terms of feature based maps. Random Finite Sets are adopted as the fundamental tool to represent a map, and a general framework is proposed for feature management, data association and state estimation. The approaches are tested in a number of experiments on both ground based and marine based facilities.