Bioinspired SLAM Approach for Unmanned Surface Vehicle

Fuente: arXiv
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Main Authors: Coelho, Fabio, Borges, Joao Victor T., Padrao, Paulo, Fuentes, Jose, Costa, Ramon R., Hsu, Liu, Bobadilla, Leonardo
Format: Preprint
Published: 2025
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author Coelho, Fabio
Borges, Joao Victor T.
Padrao, Paulo
Fuentes, Jose
Costa, Ramon R.
Hsu, Liu
Bobadilla, Leonardo
author_facet Coelho, Fabio
Borges, Joao Victor T.
Padrao, Paulo
Fuentes, Jose
Costa, Ramon R.
Hsu, Liu
Bobadilla, Leonardo
contents This paper presents OpenRatSLAM2, a new version of OpenRatSLAM - a bioinspired SLAM framework based on computational models of the rodent hippocampus. OpenRatSLAM2 delivers low-computation-cost visual-inertial based SLAM, suitable for GPS-denied environments. Our contributions include a ROS2-based architecture, experimental results on new waterway datasets, and insights into system parameter tuning. This work represents the first known application of RatSLAM on USVs. The estimated trajectory was compared with ground truth data using the Hausdorff distance. The results show that the algorithm can generate a semimetric map with an error margin acceptable for most robotic applications.
format Preprint
id arxiv_https___arxiv_org_abs_2509_19522
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Bioinspired SLAM Approach for Unmanned Surface Vehicle
Coelho, Fabio
Borges, Joao Victor T.
Padrao, Paulo
Fuentes, Jose
Costa, Ramon R.
Hsu, Liu
Bobadilla, Leonardo
Robotics
This paper presents OpenRatSLAM2, a new version of OpenRatSLAM - a bioinspired SLAM framework based on computational models of the rodent hippocampus. OpenRatSLAM2 delivers low-computation-cost visual-inertial based SLAM, suitable for GPS-denied environments. Our contributions include a ROS2-based architecture, experimental results on new waterway datasets, and insights into system parameter tuning. This work represents the first known application of RatSLAM on USVs. The estimated trajectory was compared with ground truth data using the Hausdorff distance. The results show that the algorithm can generate a semimetric map with an error margin acceptable for most robotic applications.
title Bioinspired SLAM Approach for Unmanned Surface Vehicle
topic Robotics
url https://arxiv.org/abs/2509.19522