In this contribution we present a framework for an embodied robotic system that is capable of appearance-based self-localization. Specifically, we concentrate on the issues of robustness, flexibility, and scalability of the system. The framework presented is based on a panoramic eigenspace model of the environment. Its main feature is that it allows for simultaneous localization and map building using an incremental learning algorithm. Further, both the learning and the training processes are designed in a way to achieve robustness and adaptability to changes in the environment. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Jogan, M., Artač, M., Skočaj, D., & Leonardis, A. (2003). A framework for robust and incremental self-localization of a mobile robot. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2626, pp. 460–469). Springer Verlag. https://doi.org/10.1007/3-540-36592-3_44
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