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Titlebook: Cooperative Robots and Sensor Networks; Anis Koubaa,Abdelmajid Khelil Book 2014 Springer-Verlag Berlin Heidelberg 2014 Computational Intel

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發(fā)表于 2025-3-21 16:42:38 | 只看該作者 |倒序瀏覽 |閱讀模式
書目名稱Cooperative Robots and Sensor Networks
編輯Anis Koubaa,Abdelmajid Khelil
視頻videohttp://file.papertrans.cn/239/238007/238007.mp4
概述Recent research in Cooperative Robots and Sensor Networks.Includes selected best papers of the International Workshop on Cooperative Robots and Sensor Networks (RoboSense) as well as other peer-review
叢書名稱Studies in Computational Intelligence
圖書封面Titlebook: Cooperative Robots and Sensor Networks;  Anis Koubaa,Abdelmajid Khelil Book 2014 Springer-Verlag Berlin Heidelberg 2014 Computational Intel
描述.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,
出版日期Book 2014
關鍵詞Computational Intelligence; Cooperative Robots; Sensor Networks; Wireless Sensor Networks
版次1
doihttps://doi.org/10.1007/978-3-642-39301-3
isbn_softcover978-3-662-51260-9
isbn_ebook978-3-642-39301-3Series ISSN 1860-949X Series E-ISSN 1860-9503
issn_series 1860-949X
copyrightSpringer-Verlag Berlin Heidelberg 2014
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nk quality. As the Markov model parameters are discovered on-the-fly, there is no need of a previous history to feed the Markov model. Obtained simulation results show that GMLA is a very suitable solution, as it outperforms approaches that use geographical positioning systems (GPS) and also approac
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Guiding the International Community, and WiFi signal strength fingerprinting (SSI) with enhanced route-planning algorithms to account for the sensory and mobility constraints of the user to efficiently plan safe routes and communicate the route information with sufficient resolution to address the needs of the users. To evaluate the f
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Guiding the International Community, reasonable accuracy. EasyLoc is a plug-and-play and fully distributed RSS-based localization method that requires zero pre-deployment configuration. The idea consists in exploiting the available distance information between anchors to derive an online and anchor-specific RSS to distance mapping. We
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Genetic Machine Learning Approach for Link Quality Prediction in Mobile Wireless Sensor Networks,nk quality. As the Markov model parameters are discovered on-the-fly, there is no need of a previous history to feed the Markov model. Obtained simulation results show that GMLA is a very suitable solution, as it outperforms approaches that use geographical positioning systems (GPS) and also approac
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Localization, Route Planning, and Smartphone Interface for Indoor Navigation, and WiFi signal strength fingerprinting (SSI) with enhanced route-planning algorithms to account for the sensory and mobility constraints of the user to efficiently plan safe routes and communicate the route information with sufficient resolution to address the needs of the users. To evaluate the f
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