Localization Fusion for Aerial Vehicles in Partially GNSS Denied Environments

  • Jan BayerEmail author
  • Jan Faigl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11472)


In this paper, we report on early results of the experimental deployment of localization techniques for a multi-rotor Micro Aerial Vehicle (MAV). In particular, we focus on deployment scenarios where the Global Navigation Satellite System (GNSS) does not provide a reliable signal, and thus it is not desirable to rely solely on the GNSS. Therefore, we consider recent advancements in the visual localization, and we employ an onboard RGB-D camera to develop a robust and reliable solution for the MAV localization in partially GNSS denied operational environments. We consider a localization method based on Kalman filter for data fusion of the vision-based localization with the signal from the GNSS. Based on the reported experimental results, the proposed solution supports the localization of the MAV for the temporarily unavailable GNSS, but also improves the position estimation provided by the incremental vision-based localization system while it can run using onboard computational resources of the small vehicle.



This work has been supported by the Technology Agency of the Czech Republic (TAČR) under research Project No. TH03010362.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Faculty of Electrical EngineeringCzech Technical University in PraguePragueCzech Republic

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