scholarly journals Correction of Navigational Information Supplied to Biomimetic Autonomous Underwater Vehicle

2018 ◽  
Vol 25 (1) ◽  
pp. 13-23 ◽  
Author(s):  
Tomasz Praczyk
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Environmental Influence ◽  
Autonomous Underwater Vehicles ◽  
Dead Reckoning ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Doppler Velocity ◽  
Time Record ◽  
Navigational System ◽  
Vehicle Movement

Abstract In order to autonomously transfer from one point of the environment to the other, Autonomous Underwater Vehicles (AUV) need a navigational system. While navigating underwater the vehicles usually use a dead reckoning method which calculates vehicle movement on the basis of the information about velocity (sometimes also acceleration) and course (heading) provided by on-board devicesl ike Doppler Velocity Logs and Fibre Optical Gyroscopes. Due to inaccuracies of the devices and the influence of environmental forces, the position generated by the dead reckoning navigational system (DRNS) is not free from errors, moreover the errors grow exponentially in time. The problem becomes even more serious when we deal with small AUVs which do not have any speedometer on board and whose course measurement device is inaccurate. To improve indications of the DRNS the vehicle can emerge onto the surface from time to time, record its GPS position, and measure position error which can be further used to estimate environmental influence and inaccuracies caused by mechanisms of the vehicle. This paper reports simulation tests which were performed to determine the most effective method for correction of DRNS designed for a real Biomimetic AUV.

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.

scholarly journals Report on Research with Biomimetic Autonomous Underwater Vehicle — Navigation and Autonomous Operation

2018 ◽  
Vol 213 (2) ◽  
pp. 53-67 ◽  
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 ◽  
Vehicle Navigation ◽  
Final Report ◽  
Autonomous Operation

Abstract The paper presents the second part of the final report on all the experiments with biomimetic autonomous 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 on 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 navigation and autonomous operation.

scholarly journals Autonomous Underwater Vehicle in Internet of Underwater Things: A Survey

2021 ◽  
Vol 2129 (1) ◽  
pp. 012080
Author(s):  
Chinonso Okereke ◽  
Nur Haliza Abdul Wahab ◽  
Mohd Murtadha Mohamad ◽  
S H Zaleha
Keyword(s):  
Energy Storage ◽  
Crucial Role ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
The Internet ◽  
The Earth ◽  
Future Work

Abstract Water, mostly oceans, covers over two-third of the earth. About 95% of these oceans are yet to be explored which includes 99% of the sea-beds. The introduction of the Internet of Underwater Things (IoUT) underwater has become a powerful technology necessary to the quest to develop a SMART Ocean. Autonomous Underwater Vehicles (AUVs) play a crucial role in this technology because of their mobility and longer energy storage. In order for AUV technologies to be effective, the challenges of AUVs must be adequately solved. This paper provides an overview of the challenges of IoUT, the contributions of AUVs in IoUT as well as the current challenges and opening in AUV. A summary and suggestion for future work was discussed.

Safe Navigation Algorithm for Autonomous Underwater Vehicles

2021 ◽  
Vol 29 (1) ◽  
pp. 97-110
Author(s):  
V.S. Bykova ◽  
◽  
A.I. Mashoshin ◽  
I.V. Pashkevich ◽  
◽  
...  
Keyword(s):  
Control System ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Limited Size ◽  
Safe Navigation ◽  
Navigation Algorithm ◽  
Navigation Algorithms ◽  
Ice Edge

Two safe navigation algorithms for autonomous underwater vehicles are described: algorithm for avoidance of point obstacles including all the moving underwater and surface objects, and limited size bottom objects, and algorithm for bypassing extended obstacles such as bottom elevations, rough lower ice edge, garbage patches. These algorithms are developed for a control system of a heavyweight autonomous underwater vehicle.

Multi-autonomous underwater vehicles collaboratively search for intelligent targets in an unknown environment in the presence of interception

2020 ◽  
pp. 095440622094362
Author(s):  
Xi-wen Ma ◽  
Yan-li Chen ◽  
Gui-qiang Bai ◽  
Yong-bai Sha ◽  
Jun Liu
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Full Range ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Layer By Layer ◽  
Self Organizing Map ◽  
Unknown Environment ◽  
Underwater Environment ◽  
Wave Diffusion

We present a bionic neural wave network that uses multiple autonomous underwater vehicles to search and acquire intelligent targets in an unknown underwater environment. The neuron pheromone content is arranged according to neural wave diffusion and layer-by-layer energy attenuation, when underwater mesh space based on neural wave diffusion theory was established that the neuron nodes in the neural network structure correspond to obstacles, autonomous underwater vehicles, and targets in the environment. In order to solve the problems of over-allocation and under-allocation of the multi-autonomous underwater vehicles system during the cooperative capture of targets, a redistribution mechanism based on the improved self-organizing map algorithm is implemented and directed to rationalize task distribution. Two different taboo search methods are employed to update the autonomous underwater vehicle path in real time, and the polynomial coefficient solution method is used to fit partial path data. So that the autonomous underwater vehicle trajectory can be obtained and an interceptor position coordinate can be predicted. An auxiliary autonomous underwater vehicle is aimed to replace the intercepted autonomous underwater vehicle and the matching capture points are tracked to ensure the completion of the task so that the full range of hunting targets is identified. In order to simulate an unknown complex underwater environment, obstacles are randomly arranged around the target, the location information of the obstacle, and the target is unknown and unpredictable. Four simulation experiments were performed to verify the accuracy and efficiency of the algorithm under unknown environment. The results show that this algorithm can improve the path update average efficiency by 66% compared with other algorithms. Obviously, this algorithm is reasonable and effective.

scholarly journals A single acoustic beacon-based positioning method for underwater mobile recovery of an AUV

2018 ◽  
Vol 15 (5) ◽  
pp. 172988141880173 ◽  
Author(s):  
Ziye Zhou ◽  
Yanqing Jiang ◽  
Ye Li ◽  
Cao Jian ◽  
Yeyi Sun
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Dead Reckoning ◽  
Underwater Vehicle ◽  
Doppler Velocity ◽  
Fusion Algorithm ◽  
Time Step ◽  
Short Baseline ◽  
Positioning Method ◽  
One Step ◽  
The One

This article presents a navigation method for an autonomous underwater vehicle being recovered by a human-occupied vehicle. The autonomous underwater vehicle is considered to carry underwater navigation sensors such as ultra-short baseline, Doppler velocity log, and inertial navigation system. Using these sensors’ information, a navigation module combining the ultra-short baseline positioning and inertial positioning is established. In this study, there is assumed to be no communication between the autonomous underwater vehicle and human-occupied vehicle; thus, to obtain the autonomous underwater vehicle position in the inertial coordinate, a conjecture method to obtain the human-occupied vehicle coordinates is proposed. To reduce the error accumulation of autonomous underwater vehicle navigation, a method called one-step dead reckoning positioning is proposed, and the one-step dead reckoning positioning is treated as a correction to combine with ultra-short baseline positioning by a data fusion algorithm. One-step dead reckoning positioning is a positioning method based on the previous time-step coordinates of the autonomous underwater vehicle.

scholarly journals Updating Autonomous Underwater Vehicle Risk Based on the Effectiveness of Failure Prevention and Correction

2018 ◽  
Vol 35 (4) ◽  
pp. 797-808 ◽  
Author(s):  
Mario P. Brito ◽  
Gwyn Griffiths
Keyword(s):  
Autonomous Underwater Vehicle ◽  
Risk Mitigation ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Probability Of Failure ◽  
Risk Profile ◽  
Failure Prevention ◽  
Significant Difference

AbstractAutonomous underwater vehicles (AUVs) have proven to be feasible platforms for marine observations. Risk and reliability studies on the performance of these vehicles by different groups show a significant difference in reliability, with the observation that the outcomes depend on whether the vehicles are operated by developers or nondevelopers. This paper shows that this difference in reliability is due to the failure prevention and correction procedures—risk mitigation—put in place by developers. However, no formalization has been developed for updating the risk profile based on the expected effectiveness of the failure prevention and correction process. A generic Bayesian approach for updating the risk profile is presented, based on the probability of failure prevention and correction and the number of subsequent deployments on which the failure does not occur. The approach, which applies whether the risk profile is captured in a parametric or nonparametric survival model, is applied to a real case study of the International Submarine Engineering Ltd. (ISE) Explorer AUV.

scholarly journals An evaluation of path-planning methods for autonomous underwater vehicle based on terrain-aided navigation

2019 ◽  
Vol 16 (3) ◽  
pp. 172988141985318
Author(s):  
Zheng Cong ◽  
Ye Li ◽  
Yanqing Jiang ◽  
Teng Ma ◽  
Yusen Gong ◽  
...  
Keyword(s):  
Path Planning ◽  
Ant Colony Algorithm ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Positioning Accuracy ◽  
Planning Methods ◽  
Planning Algorithms ◽  
Motion Characteristics

This article presents a comparison of different path-planning algorithms for autonomous underwater vehicles using terrain-aided navigation. Four different path-planning methods are discussed: the genetic algorithm, the A* algorithm, the rapidly exploring random tree* algorithm, and the ant colony algorithm. The goal of this article is to compare the four methods to determine how to obtain better positioning accuracy when using terrain-aided navigation as a means of navigation. Each algorithm combines terrain complexity to comprehensively consider the motion characteristics of the autonomous underwater vehicles, giving reachable path between the start and end points. Terrain-aided navigation overcomes the challenges of underwater domain, such as visual distortion and radio frequency signal attenuation, which make landmark-based localization infeasible. The path-planning algorithms improve the terrain-aided navigation positioning accuracy by considering terrain complexity. To evaluate the four algorithms, we designed simulation experiments that use real-word seabed bathymetry data. The results of autonomous underwater vehicle navigation by terrain-aided navigation in these four cases are obtained and analyzed.

scholarly journals Design, Analysis and Development of Autonomous Underwater vehicle

2019 ◽  
Vol 9 (2) ◽  
pp. 3805-3810
Keyword(s):  
Object Recognition ◽  
Motion Control ◽  
Water Surface ◽  
Autonomous Underwater Vehicle ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicle ◽  
Underwater Vehicles ◽  
Heading Control ◽  
Underwater Object ◽  
Institute Of Technology

Autonomous Underwater Vehicles (AUV) are slowly operated unmanned robots which Capable of propelling on pre-defined mission tracks independently under the water surface and are frequently used for oceanographic exploration, bathymetric surveys and defense applications. This AUV can perform underwater object recognition and obstacle avoidance with the use of appropriate sensors and devices. Vidyut is a miniature AUV developed at Sri Sairam Institute of Technology. The vehicle is equipped with six thrusters which allow for motion control in 6 Dof and has a non-conventional single hull heavy bottom hydrodynamic design. This paper discusses different aspects of the vehicle's unique design. The output of the Arduino Uno controller has been discussed for continuous depth and heading control.

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