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

✍ Scribed by Rosario Aragues, Carlos Sagues, Youcef Mezouar (auth.)

• Publisher: Springer International Publishing
• Year: 2015
• Tongue: English
• Leaves: 122
• Series: SpringerBriefs in Computer Science
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-viii
Introduction....Pages 1-10
Distributed Data Association....Pages 11-36
Distributed Localization....Pages 37-64
Map Merging....Pages 65-87
Real Experiments....Pages 89-105
Conclusions....Pages 107-108
Back Matter....Pages 109-116

✦ Subjects

Artificial Intelligence (incl. Robotics); Robotics and Automation; Computer Communication Networks; Image Processing and Computer Vision