IROS 2018poster36 citations

Invariant smoothing on Lie Groups

Paul Chauchat, Axel Barrau, Silvere Bonnabel

Abstract

In this paper we propose a (non-linear) smoothing algorithm for group-affine observation systems, a recently introduced class of estimation problems on Lie groups that bear a particular structure. As most non-linear smoothing methods, the proposed algorithm is based on a maximum a posteriori estimator, determined by optimization. But owing to the specific properties of the considered class of problems, the involved linearizations are proved to have a form of independence with respect to the current estimates, leveraged to avoid (partially or sometimes totally) the need to relinearize. The method is validated on a robot localization example, both in simulations and on real experimental data.

BibTeX
@inproceedings{iros2018_invariantsmoothi,
  title = {Invariant smoothing on Lie Groups},
  author = {Paul Chauchat and Axel Barrau and Silvere Bonnabel},
  booktitle = {IROS 2018},
  year = {2018}
}
Invariant smoothing on Lie Groups · IROS 2018