UAV Navigation System Autonomous Correction Algorithm Based on Road and River Network Recognition
https://doi.org/10.17285/0869-7035.0038
Abstract
The paper considers an original autonomous correction algorithm for UAV navigation system based on comparison between terrain images obtained by onboard machine vision system and vector topographic map images. Comparison is performed by calculating the homography of vision system images segmented using the convolutional neural network and the vector map images. The presented results of mathematical and flight experiments confirm the algorithm effectiveness for navigation applications.
About the Authors
A. P. Tanchenko
KT Unmanned Systems, St. Petersburg, Russia
Russian Federation
Russian Federation
A. M. Fedulin
KT Unmanned Systems
Russian Federation
Russian Federation
R. R. Bikmaev
Institute of Engineering Physics, Serpukhov, Russia
Russian Federation
Russian Federation
R. N. Sadekov
ERA Military Innovation Technopolis, Anapa, Russia; National Institute of Science and Technology MISiS, Moscow, Russia
Russian Federation
Russian Federation
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Review
For citations:
Tanchenko A.P., Fedulin A.M., Bikmaev R.R., Sadekov R.N. UAV Navigation System Autonomous Correction Algorithm Based on Road and River Network Recognition. Giroskopiya i Navigatsiya. 2020;28(3):32-42. (In Russ.) https://doi.org/10.17285/0869-7035.0038
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