Monocular Visual Mapping for Obstacle Avoidance on UAVs

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Date
2013-05Author
Magree, Daniel
Mooney, John G.
Johnson, Eric N.
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Show full item recordAbstract
An unmanned aerial vehicle requires adequate knowledge of its surroundings in order to operate in close proximity to obstacles. UAVs also have strict
payload and power constraints which limit the number and variety of sensors available to gather this information.
It is desirable, therefore, to enable a UAV to gather
information about potential obstacles or interesting landmarks
using common and lightweight sensor systems. This paper presents a method of fast terrain mapping
with a monocular camera. Features are extracted from
camera images and used to update a sequential extended
Kalman filter. The features locations are parameterized
in inverse depth to enable fast depth convergence. Converged
features are added to a persistent terrain map
which can be used for obstacle avoidance and additional
vehicle guidance. Simulation results and results from recorded flight test data are presented to validate the algorithm.