Constrained, networked inertial navigation for human and humanoid robot feet pose estimation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

This paper analyzes algorithms and sensor fusion architectures used to mechanize a self-contained, pose-estimation for the feet of humans or humanoid robots. The approaches makes use of a network of low-cost, inertial measurement units (IMUs) affixed to the feet. By leveraging known equality and inequality constraints between the motion and location of the IMUs, drift due to inertial sensor output errors are reduced or eliminated. Two sensor fusion approaches are evaluated; a de-centralized estimator and centralized estimator. Experimental results demonstrating the performance of these fusion schemes are presented. Issues associated with tuning the de-centralized and centralized estimators are discussed in detail.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE/ION Position, Location and Navigation Symposium, PLANS 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages76-84
Number of pages9
ISBN (Electronic)9781509020423
DOIs
StatePublished - May 26 2016
EventIEEE/ION Position, Location and Navigation Symposium, PLANS 2016 - Savannah, Georgia
Duration: Apr 11 2016Apr 14 2016

Publication series

NameProceedings of the IEEE/ION Position, Location and Navigation Symposium, PLANS 2016

Other

OtherIEEE/ION Position, Location and Navigation Symposium, PLANS 2016
CountryGeorgia
CitySavannah
Period4/11/164/14/16

Bibliographical note

Funding Information:
This material is based upon work supported by the National Science Foundation under Grant No. 1328722. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.

Keywords

  • Personal navigation
  • constrained filtering
  • inertial navigation

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