In this paper, we present a new parallel self-organizing technique for three dimensional shape reconstruction for mobile robotics. The method is based on adaptive input data decomposition, parallel shape reconstruction in decomposed clusters using Kohonen Self-Organizing Map, which creates mesh representation of the input data. Afterwards, the sub-maps are joined together and the final mesh is re-optimized. Our method overcomes a problem of fitting one mesh to complex non-continuous shapes like building interiors. The method allows to process unordered data collected by mobile robots. The method is easily paralelizable and gives promising results. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Koutník, J., Mázl, R., & Kulich, M. (2006). Building of 3D environment models for mobile robotics using Self-Organization. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4193 LNCS, pp. 721–730). Springer Verlag. https://doi.org/10.1007/11844297_73
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