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UAV Downwash-Based Terrain Classification Using Wiener-Khinchin and EMD Filters

Abstract : Knowing how to identify terrain types is especially important in the autonomous navigation, mapping, decision making and detect landings areas. A recent area is in cooperation and improvement of autonomous behavior between robots. For example, an unmanned aerial vehicle (UAV) is used to identify a possible landing area or used in cooperation with other robots to navigate in unknown terrains. This paper presents a computer vision algorithm capable of identifying the terrain type where the UAV is flying, using its rotors’ downwash effect. The algorithm is a fusion between the frequency Wiener-Khinchin adapted and spatial Empirical Mode Decomposition (EMD) domains. In order to increase certainty in terrain identification, machine learning is also used. The system is validated using videos acquired onboard of a UAV with an RGB camera.
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Submitted on : Tuesday, September 24, 2019 - 9:57:26 AM
Last modification on : Tuesday, June 29, 2021 - 12:20:09 PM
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João Matos-Carvalho, André Mora, Raúl Rato, Ricardo Mendonça, José Fonseca. UAV Downwash-Based Terrain Classification Using Wiener-Khinchin and EMD Filters. 10th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), May 2019, Costa de Caparica, Portugal. pp.83-90, ⟨10.1007/978-3-030-17771-3_7⟩. ⟨hal-02295250⟩



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