Abstract
In this paper descriptive visual features based on integral invariants are proposed to solve the global localization of indoor mobile robots. These descriptive features are locally extracted by applying a set of non-linear kernel functions around a set ofinterest points in the image. To investigate the approach thoroughly, we use a set of images taken by re-assigning the robot position many times near a set of reference locations. Also, the presence of illumination variations is encountered many times inthe images. Compared to a well-known approach, our approach has better localization rate with moderate computational overhead.
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Tamimi, H., Halawani, A., Burkhardt, H., Zell, A. (2006). Using Descriptive Image Features for Global Localization of Mobile Robots. In: Levi, P., Schanz, M., Lafrenz, R., Avrutin, V. (eds) Autonome Mobile Systeme 2005. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-30292-1_18
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DOI: https://doi.org/10.1007/3-540-30292-1_18
Publisher Name: Springer, Berlin, Heidelberg
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