This work examines the challenges of distributed map merging and localization in multi-robot systems, which enables robots to acquire the knowledge of their surroundings needed to carry out coordinated tasks. After identifying the main issues associated with this problem, each chapter introduces a different distributed strategy for solving them.
In addition to presenting a review of distributed algorithms for perception in localization and map merging, the text also provides the reader with the necessary tools for proposing new solutions to problems of multi-robot perception, as well as other interesting topics related to multi-robot scenarios.
The coverage is largely self-contained, supported by numerous explanations and demonstrations, although references for further study are also supplied. The reader will not require any prior background knowledge, other than a basic understanding of mathematics at a graduate-student level.Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
This work examines the challenges of distributed map merging and localization in multi-robot systems, which enables robots to acquire the knowledge of their surroundings needed to carry out coordinated tasks. After identifying the main issues associated with this problem, each chapter introduces a different distributed strategy for solving them.
In addition to presenting a review of distributed algorithms for perception in localization and map merging, the text also provides the reader with the necessary tools for proposing new solutions to problems of multi-robot perception, as well as other interesting topics related to multi-robot scenarios.
This work will be of interest to postgraduate students and researchers in the robotics and control communities, and will appeal to anyone with a general interest in multi-robot systems. The reader will not require any prior background knowledge, other than a basic understanding of mathematics at a graduate-student level. The coverage is largely self-contained, supported by numerous explanations and demonstrations, although references for further study are also supplied.„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This work examines the challenges of distributed map merging and localization in multi-robot systems, which enables robots to acquire the knowledge of their surroundings needed to carry out coordinated tasks. After identifying the main issues associated with this problem, each chapter introduces a different distributed strategy for solving them. In addition to presenting a review of distributed algorithms for perception in localization and map merging, the text also provides the reader with the necessary tools for proposing new solutions to problems of multi-robot perception, as well as other interesting topics related to multi-robot scenarios. The coverage is largely self-contained, supported by numerous explanations and demonstrations, although references for further study are also supplied. The reader will not require any prior background knowledge, other than a basic understanding of mathematics at a graduate-student level. Artikel-Nr. 9783319258843
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Taschenbuch. Zustand: Neu. Parallel and Distributed Map Merging and Localization | Algorithms, Tools and Strategies for Robotic Networks | Rosario Aragues (u. a.) | Taschenbuch | SpringerBriefs in Computer Science | viii | Englisch | 2015 | Springer | EAN 9783319258843 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Artikel-Nr. 104209380
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