Communication-constrained cooperative bathymetric simultaneous localisation and mapping with efficient bathymetric data transmission method

Abstract

Bathymetric simultaneous localisation and mapping (SLAM) methods yield accurate navigation results for autonomous underwater vehicles (AUVs) and can construct consistent seabed terrain maps. Multiple independently working vehicles can complete tasks like surveying and mapping efficiently, which means cooperative bathymetric SLAM using multiple AUVs is suitable for large-scale seabed mapping. However, the transmission of bathymetric measurements collected using a multi-beam echo sounder over a low bandwidth, noisy, and unreliable acoustic channel is difficult, making cooperative bathymetric SLAM very challenging. This paper develops a graph-based cooperative bathymetric SLAM system that can compress many bathymetric measurements into small-scale acoustic packets and yield accurate navigation results with a 10% loss of acoustic packets caused by unreliable acoustic communication. According to the simulation conducted using the field data, the new algorithm is shown to be robust and capable of providing accurate location and mapping results over a low bandwidth, noisy, and unreliable acoustic channel.

An Underwater Distributed SLAM Approach Based on Improved GMRBnB Framework

“…Consequently, special update strategies have been devised to collaboratively maintain a pose graph, transmitting the most relevant information within the constraints of communication bandwidth to optimize the quality of the collaborative map [23]. Measurement results can be condensed into small-scale acoustic data packets, providing precise localization and mapping outcomes in acoustic channels of low bandwidth, high noise levels, and unreliability [24]. The exchange of visual data between agents can be minimized by utilizing low-dimensional hashes, thereby curtailing data transmission time [25].…”