Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

Evaluation of the Discrete Time Feedback Particle Filter for IMU-Driven Systems Configured on SE(2)

Greiff, Marcus LU and Berntorp, Karl LU (2018) 2018 Annual American Control Conference, ACC 2018 2018-June. p.5683-5689
Abstract

This paper evaluates the utility of the feedback particle filter (FPF) for state estimation of SE(2)-configured dynamics in a real-time context. The filter is implemented in discrete time to fuse gyroscopic-and accelerometer measurements with Ultra-Wideband (UWB) and camera measurements. With this state information, the FPF is compared to other common filters in terms of the estimate mean square error (MSE) and robustness to initial conditions. An analysis is done on how these metrics scale with utilization of computational resources, concluding that the FPF should be considered for embedded applications with CPUs on par with the Cortex M4 processor.

Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
host publication
Proceedings of the American Control Conference
volume
2018-June
article number
8431134
pages
5683 - 5689
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
2018 Annual American Control Conference, ACC 2018
conference location
Milwauke, United States
conference dates
2018-06-27 - 2018-06-29
external identifiers
  • scopus:85052578777
ISBN
9781538654286
DOI
10.23919/ACC.2018.8431134
language
English
LU publication?
yes
id
8526d3f3-ca0e-4b04-b6ce-b19f584c4912
date added to LUP
2018-10-17 13:29:30
date last changed
2022-05-03 06:54:25
@inproceedings{8526d3f3-ca0e-4b04-b6ce-b19f584c4912,
  abstract     = {{<p>This paper evaluates the utility of the feedback particle filter (FPF) for state estimation of SE(2)-configured dynamics in a real-time context. The filter is implemented in discrete time to fuse gyroscopic-and accelerometer measurements with Ultra-Wideband (UWB) and camera measurements. With this state information, the FPF is compared to other common filters in terms of the estimate mean square error (MSE) and robustness to initial conditions. An analysis is done on how these metrics scale with utilization of computational resources, concluding that the FPF should be considered for embedded applications with CPUs on par with the Cortex M4 processor.</p>}},
  author       = {{Greiff, Marcus and Berntorp, Karl}},
  booktitle    = {{Proceedings of the American Control Conference}},
  isbn         = {{9781538654286}},
  language     = {{eng}},
  month        = {{08}},
  pages        = {{5683--5689}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Evaluation of the Discrete Time Feedback Particle Filter for IMU-Driven Systems Configured on SE(2)}},
  url          = {{http://dx.doi.org/10.23919/ACC.2018.8431134}},
  doi          = {{10.23919/ACC.2018.8431134}},
  volume       = {{2018-June}},
  year         = {{2018}},
}