Parallel and Distributed Map Merging and Localization Algorithms, Tools and Strategies for Robotic Networks

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 d...

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Bibliographic Details
Main Authors: Aragues, Rosario, Sagüés, Carlos (Author), Mezouar, Youcef (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2015, 2015
Edition:1st ed. 2015
Series:SpringerBriefs in Computer Science
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Description
Summary: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
Physical Description:VIII, 116 p. 34 illus online resource
ISBN:9783319258867