The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

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",
}

The Robotics Institute

Menu