Open AccessDetection and localization of helipad in autonomous UAV landing: a coupled visual-inertial approach with artificial intelligence
Author(s) -
Thinh Hoang Dinh,
Hieu Le Thi Hong
Publication year - 2020
Publication title -
tạp chí khoa học giao thông vận tải/transport and communications science journal
Language(s) - English
Resource type - Journals
eISSN - 2615-9554
pISSN - 1859-2724
DOI - 10.47869/tcsj.71.7.8
Subject(s) - artificial intelligence , computer science , inertial measurement unit , position (finance) , computer vision , set (abstract data type) , key (lock) , artificial neural network , fiducial marker , computer security , finance , economics , programming language
Autonomous landing of rotary wing type unmanned aerial vehicles is a challenging problem and key to autonomous aerial fleet operation. We propose a method for localizing the UAV around the helipad, that is to estimate the relative position of the helipad with respect to the UAV. This data is highly desirable to design controllers that have robust and consistent control characteristics and can find applications in search – rescue operations. AI-based neural network is set up for helipad detection, followed by optimization by the localization algorithm. The performance of this approach is compared against fiducial marker approach, demonstrating good consensus between two estimations