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@InCollection{BragaCampShig:2020:LiNoPa,
               author = "Braga, Jos{\'e} Renato Garcia and Campos Velho, Haroldo Fraga de 
                         and Shiguemori, Elcio H.",
                title = "Lidar and non-extensive particle filter for UAV autonomous 
                         navigation",
            booktitle = "Computational intelligence in emerging technologies for 
                         engineering applications",
            publisher = "Springer",
                 year = "2020",
               editor = "Santiago, O. L. and Corona, C. C. and Silva Neto, A. J. and 
                         Verdegay, J. L.",
                pages = "227--238",
             keywords = "Unmanned aerial vehicle (UAV)  Autonomous navigation  LiDAR data 
                          Non-extensive particle filter  Data fusion.",
             abstract = "Unmanned aerial vehicle (UAV) is a technology employed for several 
                         applications nowadays. One important UAV research topic is the 
                         autonomous navigation (AN). The standard procedure for AN is to 
                         fuse the signals from an inertial navigation system (INS) and from 
                         a global navigation satellite system (GNSS). Our approach to 
                         perform the autonomous navigation uses a computer vision system, 
                         instead of GNSS signal, associated to the visual odometry. The two 
                         techniques applied to estimate the UAV position are combined by a 
                         non-extensive particle filter. However, the development of a 
                         computer vision system for estimating the UAV position in a 
                         situation of flight over water-covered areas and flight in low 
                         light conditions is a challenge. Our approach uses images from an 
                         active sensor called light detection and ranging (LiDAR) to allow 
                         the flight in such conditions.",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto de Estudos 
                         Avan{\c{c}}ados (IEAv)}",
                 isbn = "978-3-030-34409-2",
             language = "en",
           targetfile = "braga_lidar.pdf",
        urlaccessdate = "27 jan. 2021"
}


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