mainpage.dox

/*! \mainpage Documentation
 *
 * \section intro_sec Introduction
 *   ROVIO is a visual-inertial odometry framework which, by directly using pixel
 *   intensity errors of image patches, achieves accurate tracking
 *   performance while exhibiting a very high level of robustness.
 *
 *   After detection, the tracking of the multilevel patch features is
 *   closely coupled to the underlying extended Kalman filter (EKF)
 *   by directly using the intensity errors as innovation term during
 *   the update step.  A purely robocentric approach is followed,
 *   where the location of 3D landmarks are always estimated
 *   with respect to the current camera pose. Furthermore, the landmark 
 *   positions are decomposed into a bearing vector and
 *   a distance parametrization whereby a minimal
 *   representation of differences on a corresponding σ-Algebra is employed
 *   in order to achieve better consistency and to improve the
 *   computational performance. 
 *   
 *   Due to the robocentric, inverse-
 *   distance (selectable) landmark parametrization, the framework does not
 *   require any initialization procedure, leading to a truly power-
 *   up-and-go state estimation system. 
 *
 *
 * 
 */
 
 \cond ----------- Document the the rovio namespace. ------------   \endcond
 /*! \namespace rovio */