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

Published online by Cambridge University Press:  04 April 2022

Teng Ma
Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China. Laboratory of Science and Technology on Marine Navigation and Control, China State Shipbuilding Corporation, Tianjin, China
Wenjun Zhang*
Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China.
Ye Li
Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China.
Yuxin Zhao*
College of Automation, Harbin Engineering University, Harbin, China.
Qiang Zhang
Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China.
Xiaojun Mei
Laboratory of Robotics and Systems in Engineering and Science (LARSyS), ISR/IST, University of Lisbon, Lisbon, Portugal. College of Information Engineering, Shanghai Maritime University, China
Jiajia Fan
Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin, China.
*Corresponding author. E-mail:;
*Corresponding author. E-mail:;


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.

Research Article
Copyright © The Author(s), 2022. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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