(Georgia Institute of Technology, 2013-04)
Wu, Allen D.; Johnson, Eric N.; Kaess, Michael; Dellaert, Frank; Chowdhary, Girish
A 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.