A Single-Step Maximum A Posteriori Update for Bearing-Only SLAM - Robotics Institute Carnegie Mellon University

A Single-Step Maximum A Posteriori Update for Bearing-Only SLAM

Stephen T. Tully, George A. Kantor, and Howie Choset
Conference Paper, Proceedings of 24th AAAI Conference on Artificial Intelligence (AAAI '10), pp. 1252 - 1257, July, 2010

Abstract

This paper presents a novel recursive maximum a posteriori update for the Kalman formulation of undelayed bearing-only SLAM. The estimation update step is cast as an optimization problem for which we can prove the global minimum is reachable via a bidirectional search using Gauss-Newton's method along a one-dimensional manifold. While the filter is designed for mapping just one landmark, it is easily extended to full-scale multiple-landmark SLAM. We provide this extension via a formulation of bearing-only FastSLAM. With experiments, we demonstrate accurate and convergent estimation in situations where an EKF solution would diverge.

BibTeX

@conference{Tully-2010-10505,
author = {Stephen T. Tully and George A. Kantor and Howie Choset},
title = {A Single-Step Maximum A Posteriori Update for Bearing-Only SLAM},
booktitle = {Proceedings of 24th AAAI Conference on Artificial Intelligence (AAAI '10)},
year = {2010},
month = {July},
pages = {1252 - 1257},
}