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UAV Downwash-Based Terrain Classification Using Wiener-Khinchin and EMD Filters
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Orientador(es)
Resumo(s)
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.
Descrição
This work was partially funded by FCT Strategic Program UID/EEA/00066/203 of the Center of Technologies and System (CTS) of UNINOVA - Institute for the Development of new Technologies.
Palavras-chave
EMD Image processing IMF Machine learning Terrain classification UAV Wiener-Khinchin Information Systems Computer Networks and Communications Information Systems and Management
Contexto Educativo
Citação
Editora
Springer