scholarly journals An Improved Localization Method for the Transition between Autonomous Underwater Vehicle Homing and Docking

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2468
Author(s):  
Ri Lin ◽  
Feng Zhang ◽  
Dejun Li ◽  
Mingwei Lin ◽  
Gengli Zhou ◽  
...  
Keyword(s):  
Data Exchange ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Optimization Method ◽  
Short Baseline ◽  
Localization Accuracy ◽  
Localization Method ◽  
Mapping Algorithm ◽  
Localization And Mapping ◽  
Update Rate

Docking technology for autonomous underwater vehicles (AUVs) involves energy supply, data exchange and navigation, and plays an important role to extend the endurance of the AUVs. The navigation method used in the transition between AUV homing and docking influences subsequent tasks. How to improve the accuracy of the navigation in this stage is important. However, when using ultra-short baseline (USBL), outliers and slow localization updating rates could possibly cause localization errors. Optical navigation methods using underwater lights and cameras are easily affected by the ambient light. All these may reduce the rate of successful docking. In this paper, research on an improved localization method based on multi-sensor information fusion is carried out. To improve the localization performance of AUVs under motion mutation and light variation conditions, an improved underwater simultaneous localization and mapping algorithm based on ORB features (IU-ORBSALM) is proposed. A nonlinear optimization method is proposed to optimize the scale of monocular visual odometry in IU-ORBSLAM and the AUV pose. Localization tests and five docking missions are executed in a swimming pool. The localization results indicate that the localization accuracy and update rate are both improved. The 100% successful docking rate achieved verifies the feasibility of the proposed localization method.

A Collaborative Multilateral Localization Algorithm for Wireless Sensor Networks

2013 ◽  
Vol 303-306 ◽  
pp. 201-205
Author(s):  
Shao Ping Zhang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Localization Algorithm ◽  
Localization Accuracy ◽  
Localization Method ◽  
Anchor Nodes ◽  
Simulation Results ◽  
Unknown Node

Localization technology is one of the key supporting technologies in wireless sensor networks. In this paper, a collaborative multilateral localization algorithm is proposed to localization issues for wireless sensor networks. The algorithm applies anchor nodes within two hops to localize unknown nodes, and uses Nelder-Mead simplex optimization method to compute coordinates of the unknown nodes. If an unknown node can not be localized through two-hop anchor nodes, it is localized by anchor nodes and localized nodes within two hops through auxiliary iterative localization method. Simulation results show that the localization accuracy of this algorithm is very good, even in larger range errors.

SIMULTANEOUS COOPERATIVE LOCALIZATION FOR AUVs USING RANGE-ONLY SENSORS

2011 ◽  
Vol 08 (02) ◽  
pp. 117-132 ◽  
Author(s):  
ALI JABAR RASHIDI ◽  
SAEED MOHAMMADLOO
Keyword(s):  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Measurement Unit ◽  
Cooperative Localization ◽  
Position Information ◽  
Localization Accuracy ◽  
Long Baseline ◽  
Localization And Mapping ◽  
Filter Process ◽  
Sonar Sensor

The absence of GPS underwater makes navigation for autonomous underwater vehicles (AUVs) a challenge. Moreover, the use of static beacons in the form of a long baseline (LBL) array limits the operation area to a few square kilometers and requires substantial deployment effort before operations. In this paper, an algorithm for cooperative localization of AUVs is proposed. We describe a form of cooperative Simultaneous Localization and Mapping (SLAM). Each of the robots in the group is equipped with an Inertial Measurement Unit (IMU) and some of them have a range-only sonar sensor that can determine the relative distance to the others. Two estimators, in the form of a Kalman filter, process the available position information from all the members of the team and produce a pose estimate for every one of them. Simulation results are presented for a typical localization example of three AUVs formation in a large environment and indirect trajectory. The results show that our proposed method offers good localization accuracy, although a small number of low-cost sensors are needed for each vehicle, which validates that it is an economical and practical localization approach.

scholarly journals A Review of Visual-Inertial Simultaneous Localization and Mapping from Filtering-Based and Optimization-Based Perspectives

Robotics ◽  
2018 ◽  
Vol 7 (3) ◽  
pp. 45 ◽  
Author(s):  
Chang Chen ◽  
Hua Zhu ◽  
Menggang Li ◽  
Shaoze You
Keyword(s):  
Mobile Robotics ◽  
Autonomous Underwater Vehicles ◽  
Simultaneous Localization And Mapping ◽  
Research Directions ◽  
Localization Accuracy ◽  
Core Theory ◽  
Localization And Mapping ◽  
Comprehensive Survey ◽  
Self Driving Cars ◽  
Future Work

Visual-inertial simultaneous localization and mapping (VI-SLAM) is popular research topic in robotics. Because of its advantages in terms of robustness, VI-SLAM enjoys wide applications in the field of localization and mapping, including in mobile robotics, self-driving cars, unmanned aerial vehicles, and autonomous underwater vehicles. This study provides a comprehensive survey on VI-SLAM. Following a short introduction, this study is the first to review VI-SLAM techniques from filtering-based and optimization-based perspectives. It summarizes state-of-the-art studies over the last 10 years based on the back-end approach, camera type, and sensor fusion type. Key VI-SLAM technologies are also introduced such as feature extraction and tracking, core theory, and loop closure. The performance of representative VI-SLAM methods and famous VI-SLAM datasets are also surveyed. Finally, this study contributes to the comparison of filtering-based and optimization-based methods through experiments. A comparative study of VI-SLAM methods helps understand the differences in their operating principles. Optimization-based methods achieve excellent localization accuracy and lower memory utilization, while filtering-based methods have advantages in terms of computing resources. Furthermore, this study proposes future development trends and research directions for VI-SLAM. It provides a detailed survey of VI-SLAM techniques and can serve as a brief guide to newcomers in the field of SLAM and experienced researchers looking for possible directions for future work.

Integrated Acoustic Communication and Positioning System Between an Autonomous Surface Vehicle and Autonomous Underwater Vehicles

2019 ◽  
Author(s):  
Yoshitaka Watanabe ◽  
Koji Meguro ◽  
Mitsuyasu Deguchi ◽  
Yukihiro Kida ◽  
Takuya Shimura
Keyword(s):  
Water Depth ◽  
Acoustic Communication ◽  
Multiple Access ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Small Body ◽  
Positioning System ◽  
Short Baseline ◽  
Autonomous Surface Vehicle ◽  
Multi Access

Abstract In underwater observation using an autonomous underwater vehicle (AUV), a support vessel typically monitors the AUV to support the observation. In order to make the AUV operation more efficient, an autonomous surface vehicle (ASV) and an acoustic multi-access communication and positioning system have developed. The developed acoustic system achieves multi-access with frequency division multiple access (FDMA) method, and the ASV can monitor up to three AUVs simultaneously. Positioning is performed with super short baseline (SSBL) method. The acoustic device has operation mode in which positioning and communication functions are integrated to achieve efficient uplink and accurate downlink simultaneously. Two observation operations were conducted successfully. In one of those, the ASV communicated with two types of AUVs during observation in 1250m water depth, then multiple access were achieved. Even nadir angle for one AUV became almost 40 degrees, the acoustic communication was performed. In another observation, two cruising AUVs were operated with a vessel and the ASV in 1500m water depth. The ASV monitored one AUV. Condition in case the device is equipped on small body of the ASV was evaluated. The communication was performed in this depth in severe condition. Furthermore integrated sequence of positioning and communication was successfully performed. Requirement in next phase, in which operation depth and number of multiple access are increased, is discussed.

scholarly journals Adaptive Navigation Algorithm with Deep Learning for Autonomous Underwater Vehicle

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6406
Author(s):  
Hui Ma ◽  
Xiaokai Mu ◽  
Bo He
Keyword(s):  
Deep Learning ◽  
Microelectromechanical Systems ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Low Frequency ◽  
Doppler Velocity ◽  
Position Information ◽  
Localization Accuracy ◽  
Navigation Algorithm ◽  
Frequency Position

Precise navigation is essential for autonomous underwater vehicles (AUVs). The measurement deviation of the navigation sensors, especially the microelectromechanical systems (MEMS) sensors, is a crucial factor that affects the localization accuracy. Deep learning is a novel method to solve this problem. However, the calculation cycle and robustness of the deep learning method may be insufficient in practical application. This paper proposes an adaptive navigation algorithm with deep learning to address these questions and realize accurate navigation. Firstly, this algorithm uses deep learning to generate low-frequency position information to correct the error accumulation of the navigation system. Secondly, the χ2 rule is selected to judge if the Doppler velocity log (DVL) measurement fails, which could avoid interference from DVL outliers. Thirdly, the adaptive filter, based on the variational Bayesian (VB) method, is employed to estimate the navigation information simultaneous with the measurement covariance, improving navigation accuracy even more. The experimental results, based on AUV field data, show that the proposed algorithm could realize robust navigation performance and significantly improve position accuracy.

Method of Optimization for Target Localization Model Parameters Based on LSSVR

2011 ◽  
Vol 268-270 ◽  
pp. 934-939
Author(s):  
Xue Wen He ◽  
Gui Xiong Liu ◽  
Hai Bing Zhu ◽  
Xiao Ping Zhang
Keyword(s):  
Particle Swarm Optimization ◽  
Fitness Function ◽  
Particle Swarm ◽  
Parameters Optimization ◽  
Target Localization ◽  
Likelihood Method ◽  
Support Vector ◽  
Swarm Optimization ◽  
Localization Accuracy ◽  
Localization Method

Aiming at improving localization accuracy in Wireless Sensor Networks (WSN) based on Least Square Support Vector Regression (LSSVR), making LSSVR localization method more practicable, the mechanism of effects of the kernel function for target localization based on LSSVR is discussed based on the mathematical solution process of LSSVR localization method. A novel method of modeling parameters optimization for LSSVR model using particle swarm optimization is proposed. Construction method of fitness function for modeling parameters optimization is researched. In addition, the characteristics of particle swarm parameters optimization are analyzed. The computational complexity of parameters optimization is taken into consideration comprehensively. Experiments of target localization based on CC2430 show that localization accuracy using LSSVR method with modeling parameters optimization increased by 23%~36% in compare with the maximum likelihood method(MLE) and the localization error is close to the minimum with different LSSVR modeling parameters. Experimental results show that adapting a reasonable fitness function for modeling parameters optimization using particle swarm optimization could enhance the anti-noise ability significantly and improve the LSSVR localization performance.

scholarly journals Optimal design of nose and tail of an autonomous underwater vehicle hull to reduce drag force using numerical simulation

2019 ◽  
Vol 234 (1) ◽  
pp. 76-88 ◽  
Author(s):  
Mohammad Saghafi ◽  
Roham Lavimi
Keyword(s):  
Energy Consumption ◽  
Drag Force ◽  
Autonomous Underwater Vehicle ◽  
Turbulence Modeling ◽  
Stokes Equations ◽  
Autonomous Underwater Vehicles ◽  
Three Dimensional ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Navier Stokes

In this research, the flow around the autonomous underwater vehicles with symmetrical bodies is numerically investigated. Increasing the drag force in autonomous underwater vehicles increases the energy consumption and decreases the duration of underwater exploration and operations. Therefore, the main objective of this research is to decrease drag force with the change in geometry to reduce energy consumption. In this study, the decreasing or increasing trends of the drag force of axisymmetric bare hulls have been studied by making alterations in the curve equations and creating the optimal geometric shapes in terms of hydrodynamics for the noses and tails of autonomous underwater vehicles. The incompressible, three-dimensional, and steady Navier–Stokes equations have been used to simulate the flow. Also, k-ε Realizable with enhanced wall treatment was used for turbulence modeling. Validation results were acceptable with respect to the 3.6% and 1.4% difference with numerical and experimental results. The results showed that all the autonomous underwater vehicle hulls designed in this study, at an attack angle of 0°, had a lower drag force than the autonomous underwater vehicle hull used for validation except geometry no. 1. In addition, nose no. 3 has been selected as the best nose according to the lowest value of stagnation pressure, and also tail no. 3 has been chosen as the best tail due to the production of the lowest vortex. Therefore, geometry no. 5 has been designed using nose and tail no. 3. The comparison made here showed that the maximum drag reduction in geometry no. 5 was equal to 26%, and therefore, it has been selected as the best bare hull in terms of hydrodynamics.

scholarly journals Report on Research with Biomimetic Autonomous Underwater Vehicle — Low Level Control

2018 ◽  
Vol 212 (1) ◽  
pp. 105-123
Author(s):  
Tomasz Praczyk ◽  
Piotr Szymak ◽  
Krzysztof Naus ◽  
Leszek Pietrukaniec ◽  
Stanisław Hożyń
Keyword(s):  
Research And Development ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Swimming Pool ◽  
Final Report ◽  
Level Control ◽  
Low Level

Abstract The paper presents the first part of the final report on all the experiments with biomimetic autono-mous underwater vehicle (BAUV) performed within the confines of the project entitled ‘Autonomous underwater vehicles with silent undulating propulsion for underwater ISR’, financed by Polish National Center of Research and Development. The report includes experiments in the swimming pool as well as in real conditions, that is, both in a lake and in the sea. The tests presented in this part of the final report were focused on low-level control.

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