Optical Flow Odometry with Robustness to Self-shadowing

Neal Seegmiller and David Wettergreen
IEEE International Conference on Intelligent Robots and Systems, September, 2011.


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Abstract
An optical flow odometry method for mobile robots using a single downward-looking camera is presented. The method is robust to the robot's own moving shadow and other sources of error. Robustness derives from two techniques: prevention of feature selection on or near shadow edges and elimination of outliers based on inconsistent motion. In tests where the robot's shadow dominated the image, prevention of feature selection near shadow edges allowed accurate velocity estimation when outlier rejection alone failed. Performance was evaluated on two robot platforms and on multiple terrain types at speeds up to 2 m/s.

Keywords
computer vision, visual odometry, space robotics, optical flow

Notes
Associated Center(s) / Consortia: Field Robotics Center

Text Reference
Neal Seegmiller and David Wettergreen, "Optical Flow Odometry with Robustness to Self-shadowing," IEEE International Conference on Intelligent Robots and Systems, September, 2011.

BibTeX Reference
@inproceedings{Seegmiller_2011_6940,
   author = "Neal Seegmiller and David Wettergreen",
   title = "Optical Flow Odometry with Robustness to Self-shadowing",
   booktitle = "IEEE International Conference on Intelligent Robots and Systems",
   month = "September",
   year = "2011",
}