R. Eustice, H. Singh, J. Leonard, M. Walter, and R. Ballard, Visually Navigating the RMS Titanic with SLAM Information Filters, In Proceedings of Robotics: Science and Systems (RSS), Cambridge, MA, USA, June 2005. |
||
| Abstract | 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. Real-world 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. | |
| Download | [pdf] |
@inproceedings{eustice05b,
AUTHOR = {R. Eustice, and H. Singh, and J. Leonard, and M. Walter,
and R. Ballard},
TITLE = {Visually Navigating the {RMS} Titanic with {SLAM}
Information Filters},
BOOKTITLE = {Proceedings of Robotics: Science and Systems ({RSS})},
YEAR = {2005},
MONTH = {June},
ADDRESS = {Cambridge, MA, USA}
}
|
|
|
|