Bioinspired SLAM Approach for Unmanned Surface Vehicle

Abstract

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.