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

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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.
Genre: Computers + Internet, Technology
Sub-Genre: Hardware / Network Hardware, Artificial Intelligence, Robotics
Series Title: Springerbriefs in Computer Science
Format: Paperback
Publisher: Springer Verlag
Author: Rosario Aragues & Carlos Sagues & Youcef Mezouar
Language: English
Street Date: November 10, 2015
TCIN: 50628769
UPC: 9783319258843
Item Number (DPCI): 248-09-4775
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