Parallel and Distributed Map Merging and Localization [electronic resource] : Algorithms, Tools and Strategies for Robotic Networks / by Rosario Aragues, Carlos Sag�u�es, Youcef Mezouar.
By: Aragues, Rosario [author.].
Contributor(s): Sag�u�es, Carlos [author.] | Mezouar, Youcef [author.] | SpringerLink (Online service).
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BookSeries: SpringerBriefs in Computer Science: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Description: VIII, 116 p. 34 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319258867.Subject(s): Computer science | Computer communication systems | Artificial intelligence | Image processing | Robotics | Automation | Computer Science | Artificial Intelligence (incl. Robotics) | Robotics and Automation | Computer Communication Networks | Image Processing and Computer VisionAdditional physical formats: Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
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Springer eBooksSummary: 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.
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.
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