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

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journal contribution
posted on 2010-07-01, 00:00 authored by Stephen Tully, George Kantor, Howie Choset
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.




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