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

di Rosario Aragues (Autore)

Carlos Sagüés (Autore)

Youcef Mezouar (Autore)

Springer International Publishing AG, 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.

• Autore: Rosario Aragues, Carlos Sagüés, Youcef Mezouar
• Editore: Springer International Publishing AG
• Collana: SpringerBriefs in Computer Science
• Anno: 2015
• Rilegatura: Paperback / softback
• Pagine: 116 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319258843

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