Parallel and Distributed Map Merging and Localization - Algorithms, Tools and Strategies for Robotic Networks (Paperback, 1st ed. 2015)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Computer Science
Release date:	November 2015
First published:	2015
Authors:	Rosario Aragues • Carlos Sagues • Youcef Mezouar
Dimensions:	235 x 155 x 7mm (L x W x T)
Format:	Paperback
Pages:	116
Edition:	1st ed. 2015
ISBN-13:	978-3-319-25884-3
Categories:	Books > Computing & IT > Internet > Network computers Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Computing & IT > Applications of computing > Image processing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics Promotions
LSN:	3-319-25884-2
Barcode:	9783319258843

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