Unmanned Aerial Vehicles (UAV) is a technology under strong development, with application on several fields. For the UAV autonomous navigation, a standard scheme is to use signal from a Global Navigation System by Satellite (GNSS) onboard. However, such signal can suffer natural or human interference. Our approach applies image processing procedure for the UAV positioning: image edge extraction and correlation between drone image and georeferenced satellite image. A data fusion is also applied, for combining the inertial sensor data and positioning by image. The data fusion is performed by using neural network. The output from the data fusion neural network is the correction for the UAV trajectory. Here, the variance of the trajectory error is also predicted to quantify the uncertainty.
UAV Autonomous Navigation by Image Processing with Uncertainty Trajectory Estimation
Lect.Notes Mechanical Engineering
International Symposium on Uncertainty Quantification and Stochastic Modeling ; 2020 ; Rouen, France June 29, 2020 - July 03, 2020
Proceedings of the 5th International Symposium on Uncertainty Quantification and Stochastic Modelling ; Chapter : 16 ; 211-221
2020-08-20
11 pages
Article/Chapter (Book)
Electronic Resource
English
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