This paper addresses the problem of obtaining an inertial trajectory and map, with the associated uncertainty, using the sensor-based map provided by a globally asymptotically stable SLAM filter. An optimization problem with a closed-form solution is formulated, and its uncertainty description is derived resorting to perturbation theory. The combination of the algorithm proposed in this paper with the sensor-based SLAM filter results in a complete SLAM methodology, which can be directly applied to unmanned aerial vehicles (UAVs). Both simulation and preliminary experimental results, using an instrumented quadrotor equipped with a RGB-D camera, are included in this work to illustrate the performance of the proposed algorithm under realistic conditions.