Autonomous Flight in GPS-Denied Environments Using Monocular Vision and Inertial Sensors
Author(s) -
Allen Wu,
Eric N. Johnson,
Michael Kaess,
Frank Dellaert,
Girish Chowdhary
Publication year - 2013
Publication title -
journal of aerospace information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 33
ISSN - 2327-3097
DOI - 10.2514/1.i010023
Subject(s) - astronautics , global positioning system , permission , inertial navigation system , inertial measurement unit , aeronautics , computer science , attitude and heading reference system , inertial frame of reference , artificial intelligence , computer vision , engineering , aerospace engineering , law , physics , telecommunications , quantum mechanics , political science
Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.DOI: 10.2514/1.I010023A vision-aided inertial navigation system that enables autonomous flight of an aerial vehicle in GPS-denied
environments is presented. Particularly, feature point information from a monocular vision sensor are used
to bound the drift resulting from integrating accelerations and angular rate measurements from an Inertial
Measurement Unit (IMU) forward in time. An Extended Kalman filter framework is proposed for performing
the tasks of vision-based mapping and navigation separately. When GPS is available, multiple observations of
a single landmark point from the vision sensor are used to estimate the point’s location in inertial space. When
GPS is not available, points that have been sufficiently mapped out can be used for estimating vehicle position
and attitude. Simulation and flight test results of a vehicle operating autonomously in a simplified loss-of-GPS
scenario verify the presented method
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