scholarly journals A Research on the Simultaneous Localization Method in the Process of Autonomous Underwater Vehicle Homing with Unknown Varying Measurement Error

2019 ◽  
Vol 9 (21) ◽  
pp. 4614
Author(s):  
Lingyan Dong ◽  
Hongli Xu ◽  
Xisheng Feng ◽  
Xiaojun Han ◽  
Chuang Yu
Keyword(s):  
Measurement Error ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Gaussian Mixture ◽  
Statistical Characteristics ◽  
Observation System ◽  
Support Vector ◽  
Position Information ◽  
Localization Method ◽  
Working Distance

We propose an acoustic-based framework for automatically homing an Autonomous Underwater Vehicle (AUV) to the fixed docking station (F-DS) and mobile docking station (M-DS). The proposed framework contains a simultaneous localization method of AUV and docking station (DS) and a guidance method based on the position information. The Simultaneous localization and mapping (SLAM) algorithm is not available as the statistical characteristics of the measurement error of the observation system are unknown. To solve this problem, we propose a data pre-processing method. Firstly, the measurement error data of acoustic sensor are collected. Then, We propose a Variational Auto-Encoder (VAE) based Gaussian mixture model (GMM) for estimating the statistical characteristics of measurement error. Finally, we propose a support vector regression (SVR) algorithm to fit the non-linear relationship between the statistical characteristics of measurement error and its corresponding working distance. We adopt a guidance method based on line-of-sight (LOS) and path tracking method for homing an AUV to the fixed docking station (F-DS) and mobile docking station (M-DS). The lake experimental data are used to verify the performance of the localization with the estimated statistical characteristics of measurement error.

1P1-E34 Wreck Observation System for Autonomous Underwater Vehicle : Terrain Navigation for Underwater Vehicle

2006 ◽  
Vol 2006 (0) ◽  
pp. _1P1-E34_1-_1P1-E34_4
Author(s):  
Takeshi NAKATANI ◽  
Tamaki URA ◽  
Yoshiaki NOSE ◽  
Takashi SAKAMAKI ◽  
Yuzuru ITO ◽  
...  
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Observation System

Fault Diagnosis of AUV’s Thrusters Based on SVM

2015 ◽  
Vol 738-739 ◽  
pp. 858-862
Author(s):  
Lei Wan ◽  
Ying Hao Zhang ◽  
Yu Shan Sun ◽  
Yue Ming Li
Keyword(s):  
Support Vector Machine ◽  
Fault Diagnosis ◽  
Marine Environment ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Small Sample ◽  
High Dimensional ◽  
Support Vector ◽  
Simulation Results

An autonomous underwater vehicle (AUV) should have the ability of adapting the complexity and unpredictability of the marine environment, which means that the technology of AUV’s fault diagnosis is very significant, especially the part of thrusters. In order to make it possible, one fault diagnosis strategy of AUV’s thrusters is proposed, which is based on the support vector machine (SVM). SVM has many unique advantages in solving small-sample, nonlinear and high dimensional problems. In this paper, different character signal is inputted SVM to train and test it. The simulation results show that the fault diagnosis of AUV’s thrusters based on offline SVM can classify the fault styles successfully, which proves its feasibility and effectiveness. This method offers a new way to solve the fault diagnosis of AUVs.

Application of Kalman Filter in AUV Acoustic Navigation

2014 ◽  
Vol 525 ◽  
pp. 695-701 ◽  
Author(s):  
Chang Lin Ji ◽  
Ning Zhang ◽  
Hai Hui Wang ◽  
Cui E Zheng
Keyword(s):  
Autonomous Navigation ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Underwater Acoustic Channel ◽  
Positioning Accuracy ◽  
Position Information ◽  
Long Baseline ◽  
Acoustic Navigation ◽  
Time Information ◽  
Navigation Method

LBL(Long Baseline) positioning provides an important positioning and navigation method for AUV(Autonomous Underwater Vehicle)’s underwater task. Due to the complex underwater acoustic channel, and its poor anti-interference ability, a new feedback Kalman fiter algorithm was present in this paper. By combining travel time information with position information, the state of AUV was estimated accurately. By analyzing experimental results, it showed that the LBL positioning accuracy was improved, and the algorithm ensured AUV complete its autonomous navigation with high precision.

scholarly journals Autonomous-underwater-vehicle-based marine multicomponent self-potential method: observation scheme and navigational correction

2021 ◽  
Vol 10 (1) ◽  
pp. 35-43
Author(s):  
Zhongmin Zhu ◽  
Jinsong Shen ◽  
Chunhui Tao ◽  
Xianming Deng ◽  
Tao Wu ◽  
...  
Keyword(s):  
Hydrothermal Vents ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Potential Method ◽  
Low Noise ◽  
Observation System ◽  
Seafloor Topography ◽  
Sulfide Deposits ◽  
Self Potential ◽  
Acquisition Method

Abstract. Marine self-potential (SP) investigation is an effective method to study deep-sea hydrothermal vents and seafloor sulfide deposits. At present, one of the commonly used marine self-potential systems is a towed array of electrodes. Large noises are recorded when great changes in electrode distance and array attitude occur due to the complex seafloor topography. In this paper, a new multicomponent electrical field observation system based on an autonomous underwater vehicle (AUV) was introduced for the measurement of seafloor self-potential signals. The system was tested in a lake, and the multicomponent self-potential data were collected from there. Observed data involve the navigational information of the AUV, which could be corrected using a rotation transform. After navigational correction, measured data can recover the location of the artificial source using self-potential tomography. The experimental results showed that the new SP system can be applied to marine SP observations, providing an efficient and low-noise SP acquisition method for marine resources and environmental investigations.

scholarly journals Autonomous Underwater Vehicle Localization Using Sound Measurements of Passing Ships

2020 ◽  
Vol 10 (24) ◽  
pp. 9139
Author(s):  
Jonghoek Kim
Keyword(s):  
Autonomous Underwater Vehicle ◽  
A Priori ◽  
Underwater Vehicle ◽  
Vehicle Localization ◽  
Inertial Measurement ◽  
Localization Method ◽  
Long Time ◽  
Measurement Units ◽  
Source Level

This paper introduces the localization method of an Autonomous Underwater Vehicle (AUV) in environments (such as harbors or ports) where there can be passing ships near the AUV. It is assumed that the AUV can access the trajectory and approximate source level of a passing ship, while identifying the ship by processing the ship’s sound. This paper considers an AUV which can localize itself by integrating propeller and Inertial Measurement Units (IMU). Suppose that the AUV has been moving in underwater environments for a long time, under the IMU-only localization. To fix long-term drift in the IMU-only localization, we propose that the AUV localization uses sound measurements of passing ships whose trajectories are known a priori. As far as we know, this AUV localization method is novel in using sound measurements of passing ships of which the trajectories are known a priori. The performance of the proposed localization method is verified utilizing MATLAB simulations. The simulation results show significant estimation improvements, compared to IMU-only localization. Moreover, using measurements from multiple ships gives better estimation results, compared to the case where the measurement of a single ship is used.

scholarly journals Autonomous underwater vehicle based marine multi-component self-potential method: observation scheme and navigational correction

2020 ◽  
Author(s):  
Zhongmin Zhu ◽  
Jinsong Shen ◽  
Chunhui Tao ◽  
Xianming Deng ◽  
Tao Wu ◽  
...  
Keyword(s):  
Hydrothermal Vents ◽  
Autonomous Underwater Vehicle ◽  
Electrode Array ◽  
Underwater Vehicle ◽  
Potential Method ◽  
Low Noise ◽  
Observation System ◽  
Seafloor Topography ◽  
Self Potential ◽  
Acquisition Method

Abstract. Marine self-potential (SP) investigation is an effective method to study deep-sea hydrothermal vents and seafloor sulfide deposits. At present, the commonly used marine self-potential instrument is a towed electrode array, large noise involves when the seafloor topography is complex, causing the greatly change of electrode distance and array attitude. In this paper, a new multi-component electric field observation system based on underwater autonomous underwater vehicle (AUV) was introduced for the measurement of seafloor self-potential. The system was tested in a lake and the multi-component self-potential data were collected. Observed data involve the navigational information of AUV, which could be corrected using a rotation transform. After navigational correction, measured data can recover the location of the artificial source well using self-potential tomography. The experimental results showed that the new SP system can be applied to marine SP observations, providing an efficient and low-noise SP acquisition method for marine resources and environmental investigations.

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