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Parallel and Distributed Map Merging and Localization: Algorithms, Tools and Strategies for Robotic Networks: SpringerBriefs in Computer Science

Autor Rosario Aragues, Carlos Sagüés, Youcef Mezouar
en Limba Engleză Paperback – 10 noi 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.
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Specificații

ISBN-13: 9783319258843
ISBN-10: 3319258842
Pagini: 116
Ilustrații: VIII, 116 p. 34 illus.
Dimensiuni: 155 x 235 x 10 mm
Greutate: 0.19 kg
Ediția:1st ed. 2015
Editura: Springer International Publishing
Colecția Springer
Seria SpringerBriefs in Computer Science

Locul publicării:Cham, Switzerland

Public țintă

Research

Cuprins

Introduction.- Distributed Data Association.- Distributed Localization.- Map Merging.- Real Experiments.- Conclusions.- Appendix A: Averaging Algorithms and Metropolis Weights.- Appendix B: Auxiliary Results for Distributed Localization.

Textul de pe ultima copertă

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.

Caracteristici

Highlights the unique challenges and possibilities introduced by multi-robot systems and distributed strategies Provides tools for developing new approaches to multi-robot perception and other related challenges Presents strategies for distributed map merging and localization in multi-robot systems Includes supplementary material: sn.pub/extras