İnsansız hava araçları için eşanlı konumlandırma ve haritalama

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2D_simultaneous_localization_and_mapping_for_unmanned_aerial_vehicles.pdf (1.36 MB)

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2008-04

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IEEE 16th Signal Processing, Communication and Applications Conference, SIU 2008

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IEEE

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1 - 4

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Turkish

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Conference Paper

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Abstract

Sabit yükseklikte uçtuğu varsayılan insansız Hava Araçları ( İHA) için görü-tabanlı bir Eşanlı Konumlandırma ve Haritalama (EKVH) algoritması sunulmaktadır. Araç üzerindeki kameradan elde edilen görüntülerin öznitelikleri kullanılarak farklı yer işaretleri saptanmaktadır. Yer işaretlerine Genişletilmiş¸ Kalman Süzgeci (GKS) uygulanmış ve EKVH probleminin çözümü için bazı benzetim sonuçları sunulmuştur.


In this work, a 2D vision-based simultaneous localization and mapping algorithm is developed for an unmanned aerial vehicle flying at a constant altitude. We use visual features of images obtained from an on-board camera to identify different landmarks. Using these landmarks we apply the well-known extended Kalman filter to the SLAM problem and present some simulation results.

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2d visions, Constant altitudes, Simulation results, Simultaneous localization and mapping algorithms, Simultaneous localization and mappings, SLAM problems, Unmanned aerial vehicle], Visual features, Cellular radio systems, Conformal mapping, Control theory, Military applications, Signal processing, Unmanned aerial vehicles (UAV), Unmanned vehicles

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http://hdl.handle.net/11693/26829

Published Version (Please cite this version)

http://dx.doi.org/10.1109/SIU.2008.4632709

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Scholarly Publications - Electrical and Electronics Engineering