Aragues / Sagüés / Sagues Parallel and Distributed Map Merging and Localization

Algorithms, Tools and Strategies for Robotic Networks
1. Auflage 2015
ISBN: 978-3-319-25886-7
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 122 Seiten, eBook

Reihe: SpringerBriefs in Computer Science

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.

Zielgruppe

Research

Autoren/Hrsg.

Aragues, Rosario

Sagüés, Carlos

Sagues, Carlos

Mezouar, Youcef

Inhaltsverzeichnis

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