Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Comparison of modern open-source visual SLAM approaches   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 accuracy, computational performance,
robustness, and fault tolerance. Moreover, we present a comparison of datasets
as well as an analysis of algorithms from a practical point of view. The
findings of the work raise several crucial questions for SLAM researchers.

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The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
0
The categories of this paper are: hep-ph
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The categories of this paper are: quant-ph
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The categories of this paper are: q-bio
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The categories of this paper are: nucl-ex
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The categories of this paper are: chao-dyn
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The categories of this paper are: acc-phys
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The categories of this paper are: comp-gas
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The categories of this paper are: econ
3
The categories of this paper are: physics
32
The categories of this paper are: atom-ph
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The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-th