Abstract
A basic task of rescue robot systems is mapping of the environment. Localizing injured persons, guiding rescue workers and excavation equipment requires a precise 3D map of the environment. This paper presents a new 3D laser range finder and novel scan matching method for the robot Kurt3D [9]. Compared to previous machinery [12], the apex angle is enlarged to 360°. The matching is based on semantic information. Surface attributes are extracted and incorporated in a forest of search trees in order to associate the data, i.e., to establish correspondences. The new approach results in advances in speed and reliability.
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Nüchter, A., Wulf, O., Lingemann, K., Hertzberg, J., Wagner, B., Surmann, H. (2006). 3D Mapping with Semantic Knowledge. In: Bredenfeld, A., Jacoff, A., Noda, I., Takahashi, Y. (eds) RoboCup 2005: Robot Soccer World Cup IX. RoboCup 2005. Lecture Notes in Computer Science(), vol 4020. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11780519_30
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DOI: https://doi.org/10.1007/11780519_30
Publisher Name: Springer, Berlin, Heidelberg
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