Parallel and Distributed Map Merging and Localization electronic resource Algorithms, Tools and Strategies for Robotic Networks / by Rosario Aragues, Carlos Sagues, Youcef Mezouar.
Material type: TextSeries: SpringerBriefs in Computer SciencePublication details: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: VIII, 116 p. 34 illus. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9783319258867Subject(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 VisionDDC classification: 006.3 LOC classification: Q334-342TJ210.2-211.495Online resources: Click here to access online In: 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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