Volume IV-2/W3
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W3, 89-94, 2017
https://doi.org/10.5194/isprs-annals-IV-2-W3-89-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-2/W3, 89-94, 2017
https://doi.org/10.5194/isprs-annals-IV-2-W3-89-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  18 Aug 2017

18 Aug 2017

UAV VISUAL AUTOLOCALIZATON BASED ON AUTOMATIC LANDMARK RECOGNITION

P. Silva Filho1, E. H. Shiguemori1, and O. Saotome2 P. Silva Filho et al.
  • 1IEAV – Instituto de Estudos Avançados, São José dos Campos-SP, Brazil
  • 2ITA – Instituto Tecnológico de Aeronáutica, São José dos Campos-SP, Brazil

Keywords: ORB, AKAZE, Position, Estimation, GNSS, GPS-denied, Visual navigation

Abstract. Deploying an autonomous unmanned aerial vehicle in GPS-denied areas is a highly discussed problem in the scientific community. There are several approaches being developed, but the main strategies yet considered are computer vision based navigation systems. This work presents a new real-time computer-vision position estimator for UAV navigation. The estimator uses images captured during flight to recognize specific, well-known, landmarks in order to estimate the latitude and longitude of the aircraft. The method was tested in a simulated environment, using a dataset of real aerial images obtained in previous flights, with synchronized images, GPS and IMU data. The estimated position in each landmark recognition was compatible with the GPS data, stating that the developed method can be used as an alternative navigation system.