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Diver tracking in open waters: A low‐cost approach based on visual and acoustic sensor fusion

Mohamed Walid Remmas 1, 2 Ahmed Chemori 1 Maarja Kruusmaa 2 
1 DEXTER - Robotique médicale et mécanismes parallèles
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : The design of a robust perception method is a substantial component towards achieving underwater human–robot collaboration. However, in complex environments such as the oceans, perception is still a challenging issue. Data‐fusion of different sensing modalities can improve perception in dynamic and unstructured ocean environments. This study addresses the control of a highly maneuverable autonomous underwater vehicle for diver tracking based on visual and acoustic signals data fusion measured by low‐cost sensors. The underwater vehicle U‐CAT tracks a diver using a 3‐degree‐of‐freedom fuzzy logic Mamdani controller. The proposed tracking approach was validated through open water real‐time experiments. Combining acoustic and visual signals for underwater target tracking provides several advantages compared to previously done related research. The obtained results suggest that the proposed solution ensures effective detection and tracking in poor visibility operating conditions.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-03009795
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Submitted on : Friday, November 27, 2020 - 10:52:29 AM
Last modification on : Friday, August 5, 2022 - 3:03:30 PM

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Mohamed Walid Remmas, Ahmed Chemori, Maarja Kruusmaa. Diver tracking in open waters: A low‐cost approach based on visual and acoustic sensor fusion. Journal of Field Robotics, Wiley, 2021, 38 (3), pp.494-508. ⟨10.1002/rob.21999⟩. ⟨lirmm-03009795v2⟩

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