This paper addresses the problem of obtaining an Earth-fixed trajectory and map (ETM), with the as-sociated uncertainty, using the sensor-based map provided by a globally asymptotically/exponentiallystable(GES)SLAMfilter.Thealgorithmbuildsonanoptimizationproblemwithaclosed-formsolution,and its uncertainty description is derived resorting to perturbation theory. The combination of thealgorithm proposed in this paper with sensor-based SLAM filtering results in a complete SLAMmethodology, which is directly applied to the three main different formulations: range-and-bearing,range-only, and bearing-only. Simulation and experimental results for all these formulations areincludedinthisworktoillustratetheperformanceoftheproposedalgorithmunderrealisticconditions.The ETM algorithm proposed in this paper is truly sensor-agnostic, as it only requires a sensor-basedmapandimposesnoconstraintsonhowthismapisacquirednorhowegomotioniscaptured.However,in the experiments presented herein, all the sensor-based filters use a sensor to measure the angularvelocityand,fortherange-onlyandbearing-onlyformulations,asensortomeasurethelinearvelocity.