Although our implementations use overlapping grids, the approach outperforms its direct competitor regarding accuracy and memory consumption, while being comparably fast. Regarding accuracy, it also outperforms OctoMap, the current state-of-the-art in 3D mapping.
We already successfully used our ONDT maps with a newly developed sensor model for 2D Monte Carlo Localization with laser data on 2D maps and stereo camera data on 3D maps. More information thereabout can be found on the related research page.
|||Cornelia Schulz, Richard Hanten, and Andreas Zell. "Efficient Map Representations for Multi-Dimensional Normal Distributions Transforms". In 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 2679--2686, Madrid, Spain, October 2018. [ details ]|