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Outdoor Downward-Facing Optical Flow Odometry with Commodity Sensors

  • Michael Dille
  • Ben Grocholsky
  • Sanjiv Singh
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 62)

Abstract

Positioning is a key task in most field robotics applications but can be very challenging in GPS-denied or high-slip environments. A common tactic in such cases is to position visually, and we present a visual odometry implementation with the unusual reliance on optical mouse sensors to report vehicle velocity. Using multiple kilometers of data from a lunar rover prototype,we demonstrate that, in conjunction with a moderate-grade inertial measurement unit, such a sensor can provide an integrated pose stream that is at times more accurate than that achievable by wheel odometry and visibly more desirable for perception purposes than that provided by a high-end GPS-INS system. A discussion of the sensor’s limitations and several drift mitigating strategies attempted are presented.

Keywords

Mobile Robot Drift Rate Angular Rate Optical Integration Visual Odometry 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Michael Dille
    • 1
  • Ben Grocholsky
    • 1
  • Sanjiv Singh
    • 1
  1. 1.The Robotics InstituteCarnegie Mellon UniversityPittsburghUSA

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