Visually Mapping The RMS Titanic: Conservative Covariance Estimates For SLAM Information Filters  

Oleh:

[s.n]

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: The International Journal of Robotics Research vol. 25 no. 12 (Dec. 2006), page 1223-1242.
Topik: SLAM; data association; information filters; mobile robotics; computer vision; and underwater vehicles
Fulltext: 1223.pdf (1.31MB)

Isi artikel

This paper describes a vision-based, large-area, simultaneous localization and mapping (SLAM) algorithm that respects the low-overlap imagery constraints typical of underwater vehicles while exploiting the inertial sensor information that is routinely available on such platforms. We present a novel strategy for efficiently accessing and maintaining consistent covariance bounds within a SLAM information filter, thereby 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 reported for a vision-based, six degree of freedom SLAM implementation using data from a recent survey of the wreck of the RMS Titanic.

Opini Anda

Klik untuk menuliskan opini Anda tentang koleksi ini!

Kembali