Solving The SLAM Problem for Unmanned Aerial Vehicles Using Smoothed Estimates

摘要

Abstract—In this paper we present a solution to the simultaneous localization and mapping (SLAM) problem for unmanned aerial vehicles (UAV) using a camera and inertial sensors. A good SLAM solution is an important enabler for autonomous robots. Our approach is based on an optimization based formulation of the problem, which results in a smoother, rather than a filter. The proposed algorithm is evaluated on experimental data and the results are compared with accurate ground truth data. The results from this comparisons are encouraging. I.