Automatic LADAR calibration methods using geometric optimization

This paper proposes an estimation algorithm for the determination of attitude installation matrix for laser detection and ranging systems (LADAR) mounted onboard autonomous vehicles, without requiring any prior knowledge on the terrain where the calibration mission is performed. The use of autonomous vehicles equipped with LADAR systems to conduct fully automatic surveys of terrain, infrastructures, or just to navigate safely in unknown environments, motivates the research on increasingly precise LADAR data acquisition and processing algorithms, for which the determination of the correct installation matrix is critical. The proposed methods rely on the minimization of the errors between several acquired data sets, by comparing each measured data set and a surface representation of the others. This error functional is minimized resorting to optimization tools for Riemannian manifolds enabling direct estimation of the installation matrix on the group of special orthogonal matrices SO(3). The proposed technique is extensively tested using simulated LADAR data sets under realistic acquisition conditions.