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In this paper we propose an approach to SLAM suitable for bathymetric mapping by an autonomous underwater vehicle (AUV). AUVs typically do not have access to GPS while underway and the survey areas of interest are unlikely to contain features that can easily be identified and tracked using bathymetric sonar. We demonstrate how the uncertainty in the vehicle state can be modeled using a particle filter...
We propose a method to improve the geo-referenced accuracy and self-consistency of bathymetric maps generated by autonomous underwater vehicles (AUVs), where the navigation solution is prone to drift when GPS or other methods of absolute positioning are unavailable. This is accomplished using a non-feature based approach to simultaneous localization and mapping (SLAM) that utilizes a 2D grid structure...
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