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Outdoor Downward-facing Optical Flow Odometry with Commodity Sensors

Michael Dille, Benjamin P. Grocholsky and Sanjiv Singh
Conference Paper, Carnegie Mellon University, Proceedings Field & Service Robotics (FSR '09), July, 2009

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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.

BibTeX Reference
title = {Outdoor Downward-facing Optical Flow Odometry with Commodity Sensors},
author = {Michael Dille and Benjamin P. Grocholsky and Sanjiv Singh},
booktitle = {Proceedings Field & Service Robotics (FSR '09)},
school = {Robotics Institute , Carnegie Mellon University},
month = {July},
year = {2009},
address = {Pittsburgh, PA},