Local and global localization for mobile robots using visual landmarks (2001) [28 citations — 7 self]
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by Stephen Se, David Lowe, Jim Little
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS
http://www.cs.ubc.ca/spider/se/papers/iros01.ps.gz
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@INPROCEEDINGS{Se01localand,author = {Stephen Se and David Lowe and Jim Little},
title = {Local and global localization for mobile robots using visual landmarks},
booktitle = {In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS},
year = {2001},
pages = {414--420}
}
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Abstract:
Our mobile robot system uses scale-invariant visual landmarks to localize itself and build a 3D map of the environment simultaneously. As image features are not noise-free, we carry out error analysis and use Kalman Filters to track the 3D landmarks, resulting in a database map with landmark positional uncertainty. By matching a set of landmarks as a whole, our robot can localize itself globally based on the database containing landmarks of sucient distinctiveness. Experiments show that recognition of position within a map without any prior estimate can be achieved using the scale-invariant landmarks.
