  In this paper we propose a novel observer to solve the problem of visual
simultaneous localization and mapping (SLAM), only using the information from a
single monocular camera and an inertial measurement unit (IMU). The system
state evolves on the manifold $SE(3)\times \mathbb{R}^{3n}$, on which we design
dynamic extensions carefully in order to generate an invariant foliation, such
that the problem is reformulated into online \emph{constant parameter}
identification. Then, following the recently introduced parameter
estimation-based observer (PEBO) and the dynamic regressor extension and mixing
(DREM) procedure, we provide a new simple solution. A notable merit is that the
proposed observer guarantees almost global asymptotic stability requiring
neither persistency of excitation nor uniform complete observability, which,
however, are widely adopted in most existing works with guaranteed stability.
