SemanticSLAM: Using Environment Landmarks for Unsupervised Indoor Localization

Indoor localization using mobile sensors has gained momentum lately. Most of the current systems rely on an extensive calibration step to achieve high accuracy. We propose SemanticSLAM, a novel unsupervised indoor localization scheme that bypasses the need for war-driving. SemanticSLAM leverages the...

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Veröffentlicht in:	IEEE transactions on mobile computing 2016-07, Vol.15 (7), p.1770-1782
Hauptverfasser:	Abdelnasser, Heba, Mohamed, Reham, Elgohary, Ahmed, Alzantot, Moustafa Farid, He Wang, Sen, Souvik, Choudhury, Romit Roy, Youssef, Moustafa
Format:	Magazinearticle
Sprache:	eng
Schlagworte:	Acceleration Elevators indoor localization Legged locomotion Localization Mobile computing semantic SLAM Sensors Simultaneous localization and mapping Unconventional localization unsupervised localization
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