Cooperative Robots and Sensor Networks

ISBN-13: 9783662512609 / Angielski / Miękka / 2016 / 98 str.

Anis Koubaa; Abdelmajid Khelil

Opis

This book features recent research in cooperative robots and sensor networks. It includes selected best papers of the International Workshop on Cooperative Robots and Sensor Networks (RoboSense) as well as other peer-reviewed invited chapters.

Spis treści

Gustavo Medeiros de Araujo, A.R. Pinto, J org Kaiser, and Leandro Buss Becker, Genetic Machine Learning Approach for Link Quality Prediction in Mobile Wireless Sensor Networks.- Bernardo Ordonez, Ubirajara F. Moreno, Jes Cerqueira, and Luis Almeida Generation of trajectories using predictive control for tracking consensus with sensing and connectivity constraint.- Balajee Kannan, Nisarg Kothari, Chet Gnegy, Hend Gedaway, M. Freddie Dias and M. Bernardine Dias Localization, Route Planning, and Smartphone Interface for Indoor Navigation.- Dongsik Chang, Xiaolin Liang, Wencen Wu, Catherine R. Edwards, and Fumin Zhang Real-time Modeling of Ocean Currents for Navigating Underwater Glider Sensing Networks.- Maissa Ben Jamaa, Anis Koubaa, Nouha Baccour, Yasir Kayani, Khaled Al-Shalfan, and Mohamed Jmaiel EasyLoc: Plug-and-Play RSS-based Localization in Wireless Sensor Networks.

Blurb

Mobile robots and Wireless Sensor Networks (WSNs) have enabled great potentials and a large space for ubiquitous and pervasive applications. Robotics and WSNs have mostly been considered as separate research fields and little work has investigated the marriage between these two technologies. However, these two technologies share several features, enable common cyber-physical applications and provide complementary support to each other. The primary objective of book is to provide a reference for cutting-edge studies and research trends pertaining to robotics and sensor networks, and in particular for the coupling between them.

The book consists of five chapters. The first chapter presents a cooperation strategy for teams of multiple autonomous vehicles to solve the rendezvous problem. The second chapter is motivated by the need to improve existing solutions that deal with connectivity prediction, and proposed a genetic machine learning approach for link-quality prediction. The third chapter presents an architecture for indoor navigation using an Android smartphone for guiding a variety of users, from sighted to the visually impaired, to their intended destination. In chapter four, the authors deal with accurate prediction modeling of ocean currents for underwater glider navigation. In chapter five, the authors discuss the challenges and limitations of RSS-based localization mechanisms and propose, EasyLoc, an autonomous and practical RSS-based localization technique that satisfies ease of deployment and implementation.