Efficient and Distributed Large-Scale 3D Map Registration using Tomographic Features
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Abstract (arXiv)
A robust, resource-efficient, distributed, and minimally parameterized 3D map matching and merging algorithm is proposed. The suggested algorithm utilizes tomographic features from 2D projections of horizontal cross-sections of gravity-aligned local maps, and matches these projection slices at all possible height differences, enabling the estimation of four degrees of freedom in an efficient and parallelizable manner. The advocated algorithm improves state-of-the-art feature extraction and registration pipelines by an order of magnitude in memory use and execution time. Experimental studies are offered to investigate the efficiency of this 3D map merging scheme.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 28 of its 67 references that are in the map. First posted on arXiv 27 Jun 2024.
Builds on
28 of 67 references.
References · 28
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16 more
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