Cluster-based Localization and Tracking in Ubiquitous Computing Systems

by José Ramiro Martínez-de Dios, Alberto de San Bernabé-Clemente, Arturo Torres-González, Anibal Ollero

Overview

Localization and tracking are key functionalities in ubiquitous computing systems and techniques. In recent years a very high variety of approaches, sensors and techniques for indoor and GPS-denied environments have been developed. This book briefly summarizes the current state of the art in localization and tracking in ubiquitous computing systems focusing on cluster-based schemes. Additionally, existing techniques for measurement integration, node inclusion/exclusion and cluster head selection are also described in this book.

Product Details

ISBN-13:	9783662547595
Publisher:	Springer Berlin Heidelberg
Publication date:	05/17/2017
Series:	SpringerBriefs in Electrical and Computer Engineering
Edition description:	1st ed. 2017
Pages:	82
Product dimensions:	6.10(w) x 9.25(h) x (d)

About the Author

Prof. Martinez-de Dios is Professor (Full Prof. enabled) at the University of Seville, Spain. His main research topics are cooperative perception, localization and tracking, sensor fusion, robot-sensor network cooperation and multi-robot systems. In these topics he has he coordinated 10 R&D projects and has participated in other 40 projects, including 18 EU-funded in FPs IV, V, VI, VII and H2020 Programmes. He has also coordinated and participated in other 20 technology transfer projects to companies. He is author or co-author of over 110 publications, has served as co-chair and TPC member in 20 international conferences and is or has been member of the editorial board of 5 international journals. His R&D activities have obtained 5 international awards including one 2010 EURON/EUROP Technology Transfer Awards and the 2017 Special Innovative Award 1st EU Drones Award.

Table of Contents

1 Introduction.- 2 Architectures for target localization and tracking.- 3 Measurement integration for localization and tracking.- 4 Node inclusion/exclusion in cluster-based tracking.- 5 Cluster head selection for target tracking.