/Bingham Distribution-Based Linear Filter for Online Pose Estimation

Bingham Distribution-Based Linear Filter for Online Pose Estimation

Arun Srivatsan Rangaprasad, Mengyun Xu, Nicolas Zevallos and Howie Choset
Conference Paper, Robotics: Science and Systems, 2017, July, 2017

Download Publication (PDF)

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

Pose estimation is central to several robotics applications such as registration, hand-eye calibration, SLAM, etc. Online pose estimation methods typically use Gaussian distributions to describe the uncertainty in the pose parameters. Such a description can be inadequate when using parameters such as unit-quaternions that are not unimodally distributed. A Bingham distribution can effectively model the uncertainty in unit-quaternions, as it has antipodal symmetry and is defined on a unit-hypersphere. A combination of Gaussian and Bingham distributions is used to develop a linear filter that accurately estimates the distribution of the pose parameters, in their true space. To the best of our knowledge our approach is the first implementation to use a Bingham distribution for 6 DoF pose estimation. Experiments assert that this approach is robust to initial estimation errors as well as sensor noise. Compared to state of the art methods, our approach takes fewer iterations to converge onto the correct pose estimate. The efficacy of the formulation is illustrated with a number of simulated examples on standard datasets as well as real-world experiments.

BibTeX Reference
@conference{Rangaprasad-2017-25805,
author = {Arun Srivatsan Rangaprasad and Mengyun Xu and Nicolas Zevallos and Howie Choset},
title = {Bingham Distribution-Based Linear Filter for Online Pose Estimation},
booktitle = {Robotics: Science and Systems, 2017},
year = {2017},
month = {July},
}
2018-02-07T14:33:20+00:00