Iterative Smoothing and Outlier Detection for Underwater Navigation

09/29/2021
by   Sajad Hassan, et al.
0

Underwater visual-inertial navigation is challenging due to the poor visibility and presence of outliers in underwater environments. The navigation performance is closely related to outlier detection and elimination. Existing methods assume the inertial odometry is accurate enough for outlier detection, which is not valid for low-cost inertial applications. We propose a novel iterative smoothing and outlier detection method aiming for underwater navigation. Using the dataset collected from an underwater robot and fiducial markers, experimental results confirm that the method can successfully eliminate the outliers and enhance navigation accuracy.

READ FULL TEXT

page 1

page 4

research
10/07/2018

SVIn2: Sonar Visual-Inertial SLAM with Loop Closure for Underwater Navigation

This paper presents a novel tightly-coupled keyframe based Simultaneous ...
research
10/12/2022

Unscented Kalman Filtering on Manifolds for AUV Navigation – Experimental Results

In this work, we present an aided inertial navigation system for an auto...
research
04/25/2023

Real-time Autonomous Glider Navigation Software

Underwater gliders are widely utilized for ocean sampling, surveillance,...
research
12/08/2022

Monocular Camera and Single-Beam Sonar-Based Underwater Collision-Free Navigation with Domain Randomization

Underwater navigation presents several challenges, including unstructure...
research
04/04/2023

SM/VIO: Robust Underwater State Estimation Switching Between Model-based and Visual Inertial Odometry

This paper addresses the robustness problem of visual-inertial state est...
research
10/13/2021

Hyperspectral 3D Mapping of Underwater Environments

Hyperspectral imaging has been increasingly used for underwater survey a...
research
10/14/2020

Underwater Augmented Reality for improving the diving experience in submerged archaeological sites

The Mediterranean Sea has a vast maritime heritage which exploitation is...

Please sign up or login with your details

Forgot password? Click here to reset