(Georgia Institute of Technology, 2015-05)
Ok, Kyel; Gamage, Dinesh; Drummond, Tom; Dellaert, Frank; Roy, Nicholas
We propose a method of monocular camera-inertial based navigation for computationally limited micro air vehicles (MAVs). Our approach is derived from the recent
development of parallel tracking and mapping algorithms, but unlike previous results, we show how the tracking and
mapping processes operate using different representations.The separation of representations allows us not only to move the
computational load of full map inference to a ground station, but to further reduce the computational cost of on-board tracking for pose estimation. Our primary contribution is to
show how the cost of tracking the vehicle pose on-board can be
substantially reduced by estimating the camera motion directly in the image frame, rather than in the world co-ordinate frame. We demonstrate our method on an Ascending Technologies
Pelican quad-rotor, and show that we can track the vehicle pose
with reduced on-board computation but without compromised navigation accuracy.