@Article{BragaCampShigDohe:2019:DrAuNa,
               author = "Braga, J. R. G. and Campos Velho, Haroldo Fraga de and Shiguemori, 
                         Elcio Hieiti and Dohert, P.",
          affiliation = "{} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
                title = "Drone autonomous navigation by hardware image processing",
              journal = "Mec{\'a}nica Computacional",
                 year = "2019",
               volume = "37",
               number = "51",
                pages = "2033--2043",
                 note = "Congreso sobre M{\'e}todos Num{\'e}ricos y sus Aplicaciones, 
                         24",
             keywords = "UAV autonomous navigation, Visual odometry, Computer vision, FPGA, 
                         Nonextensive particle filter.",
             abstract = "Our approach for autonomous navigation is to apply image 
                         processing for estimating the drone position. Two techniques are 
                         employed: visual odometry and computer vision. Edge detection is 
                         one important step for computer vision and it is performed by 
                         neural network implemented on FPGA. After image segmentation, a 
                         correlation between the satellite image or reference image and the 
                         image obtained by the drone is computed. Finally, the positioning 
                         by visual odometry and computer vision are combined using a new 
                         formulation of particle filter, called non-extensite particle 
                         filter. Our results show better results in comparison with other 
                         edge identification procedures, implying a more precise trajectory 
                         correction.",
             language = "en",
           targetfile = "braga_drone.pdf",
        urlaccessdate = "25 abr. 2024"
}