scholarly journals Autonomous Underwater Vehicles and Field of View in Underwater Operations

2021 ◽  
Vol 9 (3) ◽  
pp. 277
Author(s):  
Isaac Segovia Ramírez ◽  
Pedro José Bernalte Sánchez ◽  
Mayorkinos Papaelias ◽  
Fausto Pedro García Márquez
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Field Of View ◽  
Guidance System ◽  
Control Algorithms ◽  
Deep Waters ◽  
Underwater Cameras ◽  
Optimal Resolution ◽  
Acquisition Processes ◽  
And Control

Submarine inspections and surveys require underwater vehicles to operate in deep waters efficiently, safely and reliably. Autonomous Underwater Vehicles employing advanced navigation and control systems present several advantages. Robust control algorithms and novel improvements in positioning and navigation are needed to optimize underwater operations. This paper proposes a new general formulation of this problem together with a basic approach for the management of deep underwater operations. This approach considers the field of view and the operational requirements as a fundamental input in the development of the trajectory in the autonomous guidance system. The constraints and involved variables are also defined, providing more accurate modelling compared with traditional formulations of the positioning system. Different case studies are presented based on commercial underwater cameras/sonars, analysing the influence of the main variables in the measurement process to obtain optimal resolution results. The application of this approach in autonomous underwater operations ensures suitable data acquisition processes according to the payload installed onboard.

A Review of Guidance Laws Applicable to Unmanned Underwater Vehicles

2003 ◽  
Vol 56 (1) ◽  
pp. 15-29 ◽  
Author(s):  
W. Naeem ◽  
R. Sutton ◽  
S. M. Ahmad ◽  
R. S. Burns
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Guidance System ◽  
Unmanned Underwater Vehicles ◽  
Guidance And Control ◽  
Autonomous Operation ◽  
Guidance Law ◽  
Guidance Strategies ◽  
And Control ◽  
Guidance Laws

The main problem in bringing autonomy to any vehicle lies in the design of a suitable guidance law. For truly autonomous operation, the vehicle needs to have a reliable Navigation, Guidance and Control (NGC) system of which the guidance system is the key element that generates suitable trajectories to be followed. In this review paper, various guidance laws found in the literature and their relevance to autonomous underwater vehicles (AUVs) are discussed. Since existing guidance laws for underwater vehicles have emulated from tactical airborne missile systems, a number of approaches for the missile guidance systems are considered. Finally, potential guidance strategies for AUVs are proposed.

Concept and testing of an electromagnetic homing guidance system for autonomous underwater vehicles

2018 ◽  
Vol 73 ◽  
pp. 149-159 ◽  
Author(s):  
Bala Naga Jyothi Vandavasi ◽  
Umapathy Arunachalam ◽  
Vedachalam Narayanaswamy ◽  
Ramesh Raju ◽  
Doss Prakash Vittal ◽  
...  
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Guidance System

scholarly journals A Distributed Algorithm for Cooperative 3D Exploration under Communication Constraints

2013 ◽  
Vol 4 (4) ◽  
Author(s):  
Ravi Kulan Rathnam ◽  
Andreas Birk
Keyword(s):  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
High Fidelity ◽  
Optimization Strategy ◽  
Complete Control ◽  
Exploration Process ◽  
Communication Range ◽  
Navigation And Control ◽  
3D Exploration ◽  
And Control

AbstractAn algorithm for distributed exploration in 3D is presented which always keeps the robots within communication range of each other. The method is based on a greedy optimization strategy that uses a heuristic utility function. This makes it computationally very efficient but it can also lead to local minimums; but related deadlocks can be easily detected during the exploration process and there is an efficient strategy to recover from them. The exploration algorithm is integrated into a complete control infrastructure for Autonomous Underwater Vehicles (AUV) containing sensors, mapping, navigation, and control of actuators. The algorithm is tested in a high fidelity simulator which takes into account the dynamics of the robot, and simulates the required sensors. The effect of the communication range and the number of robots on the algorithm is investigated.

Development of Testbed AUV for Formation Control and its Fundamental Experiment in Actual Sea Model Basin

2021 ◽  
Vol 33 (1) ◽  
pp. 151-157
Author(s):  
Akihiro Okamoto ◽  
◽  
Motonobu Imasato ◽  
Shunka C. Hirao ◽  
Hidenori Sekiguchi ◽  
...  
Keyword(s):  
Formation Control ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Control Algorithms ◽  
Prototype System ◽  
Large Size ◽  
Constant Distance ◽  
Virtual Leader ◽  
Vital Factor ◽  
Fundamental Experiment

The formation control of multiple autonomous underwater vehicles (AUVs) is increasingly becoming a vital factor in enhancing the efficiency of ocean resources exploration. However, it is currently difficult to deploy such a package of AUVs for operation at sea because of their large size. The aim of our study is to create a demonstration system for formation control algorithms using actual hardware. To implement a prototype system, we developed a testbed AUV usable in a test basin and performed a simple formation control test in the Actual Sea Model Basin of the National Maritime Research Institute, Japan. Two AUVs, the simulated “virtual” leader and the developed “real” follower, communicate through an acoustic link and hence cruise to maintain a constant distance between them. Tests for more sophisticated formation control algorithms will be enabled using the system; consequently rapid implementation at sea will be realized.

scholarly journals A Low-Cost Electromagnetic Docking Guidance System for Micro Autonomous Underwater Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 682 ◽  
Author(s):  
Shilin Peng ◽  
Jingbiao Liu ◽  
Junhao Wu ◽  
Chong Li ◽  
Benkun Liu ◽  
...  
Keyword(s):  
Large Scale ◽  
Low Cost ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Guidance System ◽  
Electromagnetic Signal ◽  
Spatiotemporal Resolution ◽  
Search Coil ◽  
Wide Range ◽  
Processing Subsystem

As important observational platforms for the Smart Ocean concept, autonomous underwater vehicles (AUVs) that perform long-term observation in fleets are beneficial because they provide large-scale sampling data with a sufficient spatiotemporal resolution. Therefore, a large number of low-cost micro AUVs with docking capability for power recharge and data transmission are essential. This study designed a low-cost electromagnetic docking guidance (EMDG) system for micro AUVs. The EMDG system is composed of a transmitter coil located on the dock and a three-axial search coil magnetometer acting as a receiver. The search coil magnetometer was optimized for small sizes while maintaining sufficient sensitivity. The signal conditioning and processing subsystem was designed to calculate the deflection angle (β) for docking guidance. Underwater docking tests showed that the system can detect the electromagnetic signal and successfully guide AUV docking. The AUV can still perform docking in extreme positions, which cannot be realized through normal optical or acoustic guidance. This study is the first to focus on the EM guidance system for low-cost micro AUVs. The search coil sensor in the AUV is inexpensive and compact so that the system can be equipped on a wide range of AUVs.

scholarly journals Tracking Control of Autonomous Underwater Vehicles with Acoustic Localization and Extended Kalman Filter

2021 ◽  
Vol 11 (17) ◽  
pp. 8038
Author(s):  
Dongzhou Zhan ◽  
Huarong Zheng ◽  
Wen Xu
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Tracking Control ◽  
Autonomous Underwater Vehicles ◽  
Acoustic Signals ◽  
Underwater Vehicles ◽  
Ocean Currents ◽  
Acoustic Localization ◽  
And Control ◽  
Constraints Model

The absence of global positioning system (GPS) signals and the influence of ocean currents are two of the main challenges facing the autonomy of autonomous underwater vehicles (AUVs). This paper proposes an acoustic localization-based tracking control method for AUVs. Particularly, three buoys that emit acoustic signals periodically are deployed over the surface. Times of arrivals of these acoustic signals at the AUV are then obtained and used to calculate an estimated position of the AUV. Moreover, the uncertainties involved in the localization and ocean currents are handled together in the framework of the extended Kalman filter. To deal with system physical constraints, model predictive control relying on online repetitive optimizations is applied in the tracking controller design. Furthermore, due to the different sampling times between localization and control, the dead-reckoning technique is utilized considering detailed AUV dynamics. To avoid using the highly nonlinear and complicated AUV dynamics in the online optimizations, successive linearizations are employed to achieve a trade-off between computational complexity and control performance. Simulation results show that the proposed algorithms are effective and can achieve the AUV tracking control goals.

scholarly journals Modeling of Autonomous Underwater Vehicles with Multi-Propellers Based on Maximum Likelihood Method

2020 ◽  
Vol 8 (6) ◽  
pp. 407
Author(s):  
Feiyan Min ◽  
Guoliang Pan ◽  
Xuefeng Xu
Keyword(s):  
Maximum Likelihood ◽  
Controller Design ◽  
Autonomous Underwater Vehicles ◽  
Underwater Vehicles ◽  
Likelihood Method ◽  
Hydrodynamic Characteristics ◽  
Identification Algorithm ◽  
Modeling And Control ◽  
Good Convergence ◽  
And Control

The hydrodynamic characteristics of multi-propeller autonomous underwater vehicles (AUV) is usually complicated and it is difficult to obtain an accurate mathematical model. A modeling method based on CFD calculation and maximum likelihood identification algorithm is proposed for this problem. Firstly, rough hydrodynamic parameters of AUV hull are obtained by CFD calculation. Secondly, on the basis of rough parameters, a maximum likelihood identification algorithm is proposed to adjust the parameters and improve the model precision. Besides, the method to improve the convergence of identification algorithm is analyzed by considering the characteristics of AUV model structure. Finally, the identification algorithm and identification results were validated with experimental data. It was found that this method has good convergence and adaptability. In particular, the identification results of turning force and torque parameters are highly consistent in different identification experiments, which indicates that this method can well extract the maneuvering characteristics of AUVs, thus contributing to the controller design of AUVs. The research of this paper has potential application for the modeling and control of multi-propeller AUVs.

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