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Carnegie Mellon Robotics Institute

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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.

Notes

Associated Center(s) / Consortia: Field Robotics Center

Number of pages: 10

Text Reference

Michael Dille, Benjamin P. Grocholsky, and Sanjiv Singh, "Outdoor Downward-facing Optical Flow Odometry with Commodity Sensors ," Proceedings Field & Service Robotics (FSR '09), July, 2009.

BibTeX Reference

@inproceedings{Dille_2009_6430,
   author = "Michael Dille and Benjamin P Grocholsky and Sanjiv Singh",
   title = "Outdoor Downward-facing Optical Flow Odometry with Commodity Sensors ",
   booktitle = "Proceedings Field & Service Robotics (FSR '09)",
   month = "July",
   year = "2009",
}

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