@inproceedings{abe6ec6343b84312a05d5c558171453f,
title = "Visual qdometry for velocity estimation of UGVs",
abstract = "An accurate and robust velocity estimation method based on an optical flow technique is presented in this paper. Using image sequences captured by a monocular camera mounted under an UGV (unmanned ground vehicle), image velocities are obtained from the optical flow technique. Combining with a camera model, the velocities of the UGV are directly estimated. This velocity estimation method is validated over various types of terrain surfaces, such as coarse sand, fine sand and mixture of coarse sand and gravel. Experimental results show that estimated velocities have very good agreement with measured velocities. Height between the projection center of camera and the terrain surface is proved to be a key parameter in velocity estimation. Height compensation is implemented to give accurate velocity estimation results. Velocity estimation method proposed has many potential applications including localization and slip estimation for UGVs.",
keywords = "Camera, Optical flow, UGV, Velocity estimation, Visual odometry",
author = "Xiaojing Song and Seneviratne, \{Lakmal D.\} and Kaspar Althoefer and Zibin Song and Zweiri, \{Yahya H.\}",
year = "2007",
doi = "10.1109/ICMA.2007.4303790",
language = "British English",
isbn = "1424408288",
series = "Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007",
pages = "1611--1616",
booktitle = "Proceedings of the 2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007",
note = "2007 IEEE International Conference on Mechatronics and Automation, ICMA 2007 ; Conference date: 05-08-2007 Through 08-08-2007",
}