  In this paper, we present a novel stereo visual inertial pose estimation
method. Compared to the widely used filter-based or optimization-based
approaches, the pose estimation process is modeled as a control system.
Designed feedback or feedforward loops are introduced to achieve the stable
control of the system, which include a gradient decreased feedback loop, a
roll-pitch feed forward loop and a bias estimation feedback loop. This system,
named FLVIS (Feedforward-feedback Loop-based Visual Inertial System), is
evaluated on the popular EuRoc MAV dataset. FLVIS achieves high accuracy and
robustness with respect to other state-of-the-art visual SLAM approaches. The
system has also been implemented and tested on a UAV platform. The source code
of this research is public to the research community.
