Efficient off-road localization using visually corrected odometry

Authors:
Matthew Grimes;Yann LeCun
Affiliations:
Courant Institute of Mathematical Sciences, New York University, New York, NY;Faculty of Courant Institute of Mathematical Sciences, New York University, New York, NY
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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Abstract

We describe an efficient, low-cost, low-overhead system for robot localization in complex visual environments. Our system augments wheel odometry with visual orientation tracking to yield localization accuracy comparable with "pure" visual odometry at a fraction of the cost. Such a system is well-suited to consumer-level robots, small form-factor robots, extraterrestrial rovers, and other platforms with limited computational resources. Our system also benefits high-end multiprocessor robots by leaving ample processor time on all camera-computer pairs to perform other critical visual tasks, such as obstacle detection. Experimental results are shown for outdoor, off-road loops on the order of 200 meters. Comparisons are made with corresponding results from a state-of-the-art pure visual odometer.