Infinite, Sparse 3D Modelling Volumes

Modern research in mobile robotics proposes to combine localization and perception in order to recognize previously visited locations and thus to improve localization as well as the object recognition processes recursively. A crucial issue is to perform updates of the scene geometry when novel observations become available. The reason is that a practical application often requires a system to model large 3D environments at high resolution which exceeds the storage of the local memory. The underlying work presents an optimized volume data structure for infinite 3D environments which facilitates (i) successive world model updates without the need to recompute the full dataset, (ii) very fast in memory data access scheme enabling the integration of high resolution 3D sensors in real-time, (iii) efficient level-of-detail for visualization and coarse geometry updates. The technique is finally demonstrated on real world application scenarios which underpin the feasibility of the research outcomes.