DocumentCode :
2545682
Title :
Optical flow odometry with robustness to self-shadowing
Author :
Seegmiller, Neal ; Wettergreen, David
Author_Institution :
Carnegie Mellon University, Robotics Institute, USA
fYear :
2011
fDate :
25-30 Sept. 2011
Firstpage :
613
Lastpage :
618
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 :
Adaptive optics; Cameras; Feature extraction; Image edge detection; Robot vision systems; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems (IROS), 2011 IEEE/RSJ International Conference on
Conference_Location :
San Francisco, CA
ISSN :
2153-0858
Print_ISBN :
978-1-61284-454-1
Type :
conf
DOI :
10.1109/IROS.2011.6094670
Filename :
6094670
Link To Document :
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