Cumulative Error Estimation from Noisy Relative Measurements

Odometry is important for an autonomous vehicle in scenarios where GPS is either unavailable or only intermittently available. However, in a large scale environment, it often generalizes unbounded cumulative error when the vehicle unconsciously moves. This paper analyzes how the cumulative error grows according to the noisy relative measurements. An unbounded drift model is proposed to represent the cumulative error, where its probability distribution is described by the corresponding expectation and variance. Compared to other approaches, it presents a recursive cumulative error expression in absence of the true positions, which has great potential in various domains, e. g. path planning and odmetry based localization. Both experiments and cases are conducted to not only verify the accuracy of the proposed model, but also illustrate the potential in related domains.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Appendices; Figures; References; Tables;
  • Pagination: pp 1422-1429
  • Monograph Title: 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

Subject/Index Terms

Filing Info

  • Accession Number: 01564817
  • Record Type: Publication
  • ISBN: 9781479929146
  • Files: TRIS
  • Created Date: May 5 2015 10:56AM