Summary
Autonomous navigation using natural landmarks in an unexplored environment is a very difficult problem to handle. While there are many techniques capable of matching pre-defined objects correctly, few of them can be used for real-time navigation in an unexplored environment. One important unsolved problem is to efficiently select a minimum set of usable landmarks for localisation purposes. This paper presents a method which minimises the number of landmarks selected based on texture descriptors. This enables localisation based on only a few distinctive landmarks rather than handling hundreds of irrelevant landmarks per image. The distinctness of a landmark is calculated based on the mean and covariance matrix of the feature descriptors of landmarks from an entire history of images. The matrices are calculated in a training process and updated during real-time navigation.
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© 2006 Springer-Verlag Berlin Heidelberg
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Kiang, KM., Willgoss, R., Blair, A. (2006). Distinctness Analysis on Natural Landmark Descriptors. In: Corke, P., Sukkariah, S. (eds) Field and Service Robotics. Springer Tracts in Advanced Robotics, vol 25. Springer, Berlin, Heidelberg . https://doi.org/10.1007/978-3-540-33453-8_7
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DOI: https://doi.org/10.1007/978-3-540-33453-8_7
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