ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)

For citation:

Malishev Y. A., Lobov S. A., Yakhno V. G. Study of a two-threshold modification of a biomorphic navigation system. Izvestiya VUZ. Applied Nonlinear Dynamics, 2026, vol. 34, iss. 2, pp. 314-330. DOI: 10.18500/0869-6632-003204, EDN: OYKEHL

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Language: 
Russian
Heading: 
Nonlinear Dynamics and Neuroscience
Article type: 
Article
UDC: 
57.024
DOI: 
10.18500/0869-6632-003204
EDN: 
OYKEHL

Study of a two-threshold modification of a biomorphic navigation system

Autors: 
Malishev Yuri Aleksandrovich, A. V. Gaponov-Grekhov Institute of Applied Physics RAS
Lobov Sergey Anatolyevich, A. V. Gaponov-Grekhov Institute of Applied Physics RAS
Yakhno Vladimir Grigorevich, A. V. Gaponov-Grekhov Institute of Applied Physics RAS
Abstract: 

The purpose of this work is to implement and study the dynamics of a modified version of a biomorphic visual navigation system.

Methods. The paper uses the RatSLAM simultaneous navigation and mapping system. The RatSLAM system is a biomorphic model of visual navigation in the rodent hippocampus. In this study, we investigate a modified version of the RatSLAM system in which visual landmarks are processed using a two-threshold algorithm.

Results. This article presents a modified version of the visual navigation system. Using a two-threshold algorithm for determining visual landmarks allows for a reduction in the size of the resulting map without loss of accuracy. Using the constructed system, location estimates and clustering metrics for visual landmarks were obtained on publicly available datasets.

Conclusion. The constructed visual navigation system provides an estimate of the location of an object (video camera) in space that is in good agreement with the true location data. Using a two-threshold algorithm, the map size can be reduced without increasing map accuracy.

Key words: 
simultaneous localization and mapping systems
integration paths
landmarks
neural networks
clustering
Acknowledgments: 
This work was supported by the Ministry of Science and Higher Education of the Russian Federation under a state assignment (Project Nos. FFUF-2024-0037 — system development, FSMG-2024-0047 — research of clustering).
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Received: 
11.10.2025
Accepted: 
25.11.2025
Available online: 
09.12.2025
Published: 
31.03.2026
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