Corpus ID: 236881554

Comparison of modern open-source visual SLAM approaches

@article{Sharafutdinov2021ComparisonOM,
  title={Comparison of modern open-source visual SLAM approaches},
  author={Dinar Sharafutdinov and Mark Griguletskii and Pavel Kopanev and Mikhail Kurenkov and Gonzalo Ferrer and Aleksey Fedorovich Burkov and Aleksei Gonnochenko and Dzmitry Tsetserukou},
  journal={ArXiv},
  year={2021},
  volume={abs/2108.01654}
}
SLAM is one of the most fundamental areas of research in robotics and computer vision. State of the art solutions has advanced significantly in terms of accuracy and stability. Unfortunately, not all the approaches are available as open-source solutions and free to use. The results of some of them are difficult to reproduce, and there is a lack of comparison on common datasets. In our work, we make a comparative analysis of state-of-the-art open-source methods. We assess the algorithms based on… Expand
TomoSLAM: factor graph optimization for rotation angle refinement in microtomography
TLDR
The scientific novelty of this work is to consider the problem of trajectory refinement in microtomography as a SLAM problem by extracting Speeded Up Robust Features (SURF) features from X-ray projections, filtering matches with Random Sample Consensus, calculating angles between projections, and using them in factor graph in combination with stepper motor control signals in order to refine rotation angles. Expand

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