Distributed Bayesian Tracking on the Special Euclidean Group Using Lie Algebra Parametric Approximations

Claudio J. Bordin; Caio Gomes de Figueredo; Marcelo G. S. Bruno

ICASSP 2023accepted0 citations

Distributed Bayesian Tracking on the Special Euclidean Group Using Lie Algebra Parametric Approximations

Claudio J. Bordin, Caio Gomes de Figueredo, Marcelo G. S. Bruno

Abstract

This paper proposes new distributed particle filters for tracking the state of a dynamic system that evolves on the Special Euclidean Group. The algorithms are based on the Random Exchange diffusion technique and build compressed parametric approximations to the particles using Lie algebras. Via numerical simulations, we observe that the proposed methods perform similarly to a centralized particle filter, surpassing an extended Kalman filter by a large margin.

BibTeX

@inproceedings{icassp2023_distributedbayes,
  title = {Distributed Bayesian Tracking on the Special Euclidean Group Using Lie Algebra Parametric Approximations},
  author = {Claudio J. Bordin and Caio Gomes de Figueredo and Marcelo G. S. Bruno},
  booktitle = {ICASSP 2023},
  year = {2023}
}