Jump to : Download | Abstract | Contact | BibTex reference | EndNote reference |


V. Drevelle, P. Bonnifait. Localization Confidence Domains via Set Inversion on Short-Term Trajectory. IEEE Trans. on Robotics, 29(5):1244-1256, October 2013.

Download [help]

Download paper: Doi page

Download Hal paper: Hal : Hyper Archive en ligne

Download paper: Adobe portable document (pdf) pdf

Copyright notice:

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder. This page is automatically generated by bib2html v217, Inria 2002-2015, Projet Lagadic


The knowledge of localization uncertainties is of prime importance when the navigation of intelligent vehicles has to deal with safety issues. This paper presents a robust estimation method that is able to quantify the localization confidence based on interval analysis and constraint propagation. First, tightly coupled position domains are computed by constraint propagation on Global Positioning System (GPS) measurements and a precise 3-D map of the drivable area. Since GPS is prone to satellite masking and wrong measurements in urban areas, a second stage provides localization integrity and information availability by the use of a position and proprioceptive data history. A robust constraint propagation algorithm is employed to compute the current vehicle pose. It is able to handle erroneous positions with a chosen integrity risk. Experiments carried out in urban canyons illustrate the performance of the method in comparison with a particle filter. Despite bad satellite visibility, full positioning availability is obtained, and errors are less than 5.1 m during 95\% of the trial. In opposition to the particle filter, confidence domains are consistent with ground truth, which confirms the high integrity of the method


Vincent Drevelle

BibTex Reference

   Author = {Drevelle, V. and Bonnifait, P.},
   Title = {{Localization Confidence Domains via Set Inversion on Short-Term Trajectory}},
   Journal = {{IEEE Trans. on Robotics}},
   Volume = {29},
   Number = {5},
   Pages = {1244--1256},
   Month = {October},
   Year = {2013}

EndNote Reference [help]

Get EndNote Reference (.ref)

| Lagadic | Map | Team | Publications | Demonstrations |
Irisa - Inria - Copyright 2009 Lagadic Project