Robust Underwater Visual SLAM Fusing Acoustic Sensing

Elizabeth Vargas*, Raluca Scona, Jonatan Scharff Willners, Tomasz Luczynski, Yu Cao, Sen Wang, Yvan R. Petillot

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

24 Citations (Scopus)


In this paper, we propose an approach for robust visual Simultaneous Localisation and Mapping (SLAM) in underwater environments leveraging acoustic, inertial and altimeter/depth sensors. Underwater visual SLAM is challenging due to factors including poor visibility caused by suspended particles in water, a lack of light and insufficient texture in the scene. Because of this, many state-of-the-art approaches rely on acoustic sensing instead of vision for underwater navigation. Building on the sparse visual SLAM system ORB-SLAM2, this paper proposes to improve the robustness of camera pose estimation in underwater environments by leveraging acoustic odometry, which derives a drifting estimate of the 6-DoF robot pose from fusion of a Doppler Velocity Log (DVL), a gyroscope and an altimeter or depth sensor. Acoustic odometry estimates are used as motion priors and we formulate pose residuals that are integrated within the camera pose tracking, local and global bundle adjustment procedures of ORB-SLAM2. The original design of ORB-SLAM2 supports a single map and it enters relocalisation when tracking is lost. This is a significant problem for scenarios where a robot does a continuous scanning motion without returning to a previously visited location. One of our main contributions is to enable the system to create a new map whenever it encounters a new scene where visual odometry can work. This new map is connected with its predecessor in a common graph using estimates from the proposed acoustic odometry. Experimental results on two underwater vehicles demonstrate the increased robustness of our approach compared to baseline ORB-SLAM2 in both controlled, uncontrolled and field environments.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Robotics and Automation
Number of pages7
ISBN (Electronic)9781728190778
Publication statusPublished - 18 Oct 2021
Event2021 IEEE International Conference on Robotics and Automation - Xi'an, China
Duration: 30 May 20215 Jun 2021


Conference2021 IEEE International Conference on Robotics and Automation
Abbreviated titleICRA 2021

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering


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