Reliable Computing

, Volume 6, Issue 3, pp 337–362 | Cite as

Robust Autonomous Robot Localization Using Interval Analysis

  • Michel Kieffer
  • Luc Jaulin
  • Éric Walter
  • Dominique Meizel

Abstract

This paper deals with the determination of the position and orientation of a mobile robot from distance measurements provided by a belt of onboard ultrasonic sensors. The environment is assumed to be two-dimensional, and a map of its landmarks is available to the robot. In this context, classical localization methods have three main limitations. First, each data point provided by a sensor must be associated with a given landmark. This data-association step turns out to be extremely complex and time-consuming, and its results can usually not be guaranteed. The second limitation is that these methods are based on linearization, which makes them inherently local. The third limitation is their lack of robustness to outliers due, e.g., to sensor malfunctions or outdated maps. By contrast, the method proposed here, based on interval analysis, bypasses the data-association step, handles the problem as nonlinear and in a global way and is (extraordinarily) robust to outliers.

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Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  • Michel Kieffer
    • 1
  • Luc Jaulin
    • 2
  • Éric Walter
    • 3
  • Dominique Meizel
    • 4
  1. 1.Laboratoire des Signaux et SystèmesCNRS-Supélec, Plateau de MoulonGif-sur-YvetteFrance
  2. 2.Laboratoire des Signaux et SystèmesCNRS-Supélec, Plateau de MoulonGif-sur-YvetteFrance
  3. 3.Laboratoire des Signaux et SystèmesCNRS-Supélec, Plateau de MoulonGif-sur-YvetteFrance
  4. 4.Beudiasyc, CNRSUniversité de Technologie de CompiègneCompiègneFrance

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