Mar 20, 2020 · In this paper, we proposed a deep framework - NavNet - by taking AUV navigation as a deep sequential learning problem.

Experimental results show that NavNet has an excellent performance in terms of both the navigation accuracy and fault tolerance. In addition, a reliable fusion ...

Apr 8, 2020 · To avoid these problems, in this paper, we proposed a deep framework — NavNet — by taking AUV navigation as a deep sequential learning problem.

Jun 15, 2023 · This paper proposes a general correction model based on the sequential learning method to correct the errors of various state estimation techniques.

AUVs usually employ an inertial navigation system (INS), aided by a Doppler velocity log (DVL), to provide the required navigation accuracy. The DVL transmits ...

Apr 15, 2023 · A Deep Learning (DL) -based approach has been developed to estimate the vehicle's body-frame velocity, without canonically employing DVL measurements.

Vinet: Visual-inertial odometry as a sequence-to-sequence learning problem. ... Zhang, NavNet: AUV navigation through deep sequential learning, IEEE Access, № 8, ...

This git repo contains the dataset, code and weights of the deep learning architecture, BeamsNet, which was introduced in the paper BeamsNet.

A Recurrent Neural Network (RNN) was developed to predict the relative horizontal velocities of an Autonomous Underwater Vehicle (AUV) using data from an IMU, ...

Feb 25, 2024 · This paper provides an in-depth review of deep learning methods for inertial sensing and sensor fusion.