Visually Navigating the RMS Titanic with SLAM Information Filters

TitleVisually Navigating the RMS Titanic with SLAM Information Filters
Publication TypeConference Paper
Year of Publication2005
AuthorsEustice R, Singh H, Leonard JJ, Walter M, Ballard R

This paper describes a vision-based large-area simultaneous localization and mapping (SLAM) algorithm that respects the constraints of low-overlap imagery typical of underwater vehicles while exploiting the information associated with the inertial sensors that are routinely available on such platforms. We present a novel strategy for efficiently accessing and maintaining consistent covariance bounds within a SLAM information filter, greatly increasing the reliability of data association. The technique is based upon solving a sparse system of linear equations coupled with the application of constant-time Kalman updates. The method is shown to produce consistent covariance estimates suitable for robot planning and data association. Realworld results are presented for a vision-based 6 DOF SLAM implementation using data from a recent ROV survey of the wreck of the RMS Titanic.