  In monocular vision systems, lack of knowledge about metric distances caused
by the inherent scale ambiguity can be a strong limitation for some
applications. We offer a method for fusing inertial measurements with monocular
odometry or tracking to estimate metric distances in inertial-monocular systems
and to increase the rate of pose estimates. As we performed the fusion in a
loosely-coupled manner, each input block can be easily replaced with one's
preference, which makes our method quite flexible. We experimented our method
using the ORB-SLAM algorithm for the monocular tracking input and Euler forward
integration to process the inertial measurements. We chose sets of data
recorded on UAVs to design a suitable system for flying robots.
