• Journal of Institute of Control, Robotics and Systems
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• v.14 no.12
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• pp.1197-1204
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• 2008

This paper presents an asymptotic formation control scheme for a group of underactuated autonomous underwater vehicles (AUVs) where only three control inputs - surge force, yaw moment and pitch moment are available for each vehicle's six degree of freedom (DOF) underwater motion. Usually, the dynamics agents applied in most of the formation algorithms presented so far have been modeled as particle systems, which is a simple double-integrator system. Therefore, these algorithms cannot be directly applicable to the practical systems, especially to the underwater vehicles whose dynamics are highly nonlinear. Moreover, the vehicles considered in this paper are underactuated. The formation control is derived using general potential function method, and the corresponding potential function consists of two parts: interactions between vehicles and virtual-leader following. Proposed formation scheme guarantees asymptotic local stability of closed-loop system. Numerical simulations are carried out to illustrate the effectiveness of proposed formation scheme.

• Journal of Ocean Engineering and Technology
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• v.36 no.1
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• pp.41-49
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• 2022

With the advancement of intelligent vehicles and unmanned systems, there is a growing interest in underwater surveys using autonomous marine vehicles (AMVs). This study presents an automated planning strategy for a long-term survey mission using a fleet of AMVs consisting of autonomous surface vehicles and autonomous underwater vehicles. Due to the complex nature of the mission, the actions of the vehicle must be of high-level abstraction, which means that the actions indicate not only motion of the vehicle but also symbols and semantics, such as those corresponding to deploy, charge, and survey. For automated planning, the planning domain definition language (PDDL) was employed to construct a mission planner for realizing a powerful and flexible planning system. Despite being able to handle abstract actions, such high-level planners have difficulty in efficiently optimizing numerical objectives such as obtaining the shortest route given multiple destinations. To alleviate this issue, a widely known technique in operations research was additionally employed, which limited the solution space so that the high-level planner could devise efficient plans. For a comprehensive evaluation of the proposed method, various PDDL-based planners with different parameter settings were implemented, and their performances were compared through simulation. The simulation result shows that the proposed method outperformed the baseline solutions by yielding plans that completed the missions more quickly, thereby demonstrating the efficacy of the proposed methodology.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.302-306
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• 2011

This paper presents Takagi-Sugeno (T-S) fuzzy-model-based controller for depth control of autonomous underwater vehicles(AUVs). Through sector nonlinearity methodology, The nonlinear AUV is represented by T-S fuzzy model. By using the Lyapunov function, the design condition of controller is derived to guarantee the performance of depth control in the format of linear matrix inequality (LMI). An example is provided to illustrate the effectiveness of the proposed methodology.

• Journal of Power System Engineering
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• v.20 no.1
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• pp.24-29
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• 2016

Remotely operated vehicles or autonomous underwater vehicles have been used for exploiting seabed natural resources. In this study, the autonomous underwater vehicle of hovering type(HAUV) is developed to observe underwater objects in close distance. A dynamic model with six degrees of freedom is established, capturing the motion characteristics of the HAUV. The equations of motion are generated for the dynamic control simulation of the HAUV. The added mass, drag and lift forces are included in the computer model. Computational fluid dynamics simulation is carried out using this computer model. The drag coefficients are produced from the CFD.

• International Journal of Naval Architecture and Ocean Engineering
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• v.8 no.3
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• pp.243-251
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• 2016

Autonomous Underwater Vehicles (AUVs) generally work in complex marine environments. Any fault in AUVs may cause significant losses. Thus, system reliability and automatic fault diagnosis are important. To address the actuator failure of AUVs, a fault diagnosis method based on the Gaussian particle filter is proposed in this study. Six free-space motion equation mathematical models are established in accordance with the actuator configuration of AUVs. The value of the control (moment) loss parameter is adopted on the basis of these models to represent underwater vehicle malfunction, and an actuator failure model is established. An improved Gaussian particle filtering algorithm is proposed and is used to estimate the AUV failure model and motion state. Bayes algorithm is employed to perform robot fault detection. The sliding window method is adopted for fault magnitude estimation. The feasibility and validity of the proposed method are verified through simulation experiments and experimental data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.513-517
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• 2006

Autonomous Underwater Vehicles plays specific role in underwater investigation. Generally, this kind of vehicles will move along a planned path for sea bottom or underwater installations inspections, search for mineral deposits along shelves, seeking lost items including bottom mines or for hydrographic measurements. A crucial barrier for it remains the possibility of precise determination of their underwater position. Commonly used radionavigation systems do not work in such circumstances or do not guarantee the required accuracies. In the paper some new solution is proposed on the assumption that it is possible to increase the precision by certain processing of a combination of measurements conducted by means of different techniques. Objective of the paper is the idea of navigation of AUV which consists of two phases: firstly a trip of AUV along pre-planned route and after that postprocessed transformation of collected data in post-processing mode. During the processing of collected data the modern adjustment methods have been applied, mainly estimation by means of least squares and M-estimation. Application of these methods should be associated with the measuring and geometric conditions of navigational tasks and thus suited for specific scientific and technical problems of underwater navigation. The first results of computer aided investigation will be presented and the basic scope of these application and possible development directions will be indicated also. The paper is prepared as an partial results of the works carried out within a framework of the research Project: 'Improvement of the Precise Underwater Vehicle Navigation Methods' financed by the Polish Ministry of Education and Science (No 0 T00A 012 25).

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.3
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• pp.441-450
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• 2022

The introduction of autonomous underwater gliders (AUGs) specifically addresses the reduction of operational costs that were previously prohibited with conventional autonomous underwater vehicles (AUVs) using a "scaling-down" design philosophy by utilizing the characteristics of autonomous drifters to far extend operation duration and coverage. Long-duration, wide-area missions raise the cost and complexity of in-water testing for novel approaches to autonomous mission planning. As a result, a simulator that supports the rapid design, development, and testing of autonomy solutions across a wide range using software-in-the-loop simulation at faster-than-real-time speeds becomes critical. This paper describes a faster-than-real-time AUG simulator that can support high-resolution bathymetry for a wide variety of ocean environments, including ocean currents, various sensors, and vehicle dynamics. On top of the de facto standard ROS-Gazebo framework and open-sourced underwater vehicle simulation packages, features specific to AUGs for ocean mapping are developed. For vehicle dynamics, the next-generation hybrid autonomous underwater gliders (Hybrid-AUGs) operate with both the buoyancy engine and the thrusters to improve navigation for bathymetry mappings, e.g., line trajectory, are is implemented since because it can also describe conventional AUGs without the thrusters. The simulation results are validated with experiments while operating at 120 times faster than the real-time.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.2
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• pp.91-99
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• 2013

An autonomous unmanned underwater vehicle is a type of marine self-propelled robot that executes some specific mission and returns to base on completion of the task. In order to successfully execute the requested operations, the vehicle must be guided by an effective navigation algorithm that enables it to avoid obstacles and follow the best path. Architectures and principles for intelligent dynamic systems are being developed, not only in the underwater arena but also in related areas where the work does not fully justify the name. The problem of increasing the capacity of systems management is highly relevant based on the development of new methods for dynamic analysis, pattern recognition, artificial intelligence, and adaptation. Among the large variety of navigation methods that presently exist, the dynamic window approach is worth noting. It was originally presented by Fox et al. and has been implemented in indoor office robots. In this paper, the dynamic window approach is applied to the marine world by developing and extending it to manipulate vehicles in 3D marine environments. This algorithm is provided to enable efficient avoidance of obstacles and attainment of targets. Experiments conducted using the algorithm in MATLAB indicate that it is an effective obstacle avoidance approach for marine vehicles.

• Journal of Ocean Engineering and Technology
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• v.26 no.4
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• pp.1-7
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• 2012

This paper deals with the global path planning problem for AUVs (autonomous underwater vehicles) in a tidal current field. The previous researches in the field were unsuccessful at simultaneously addressing the two issues of obstacle avoidance and tidal current-based optimization. The use of a genetic algorithm is proposed in this paper to move past this limitation and solve both issues at once. Simulation results showed that the genetic algorithm could be applied to generate an optimal path in the field of a tidal current with multiple obstacles.

• International Journal of Ocean System Engineering
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• v.2 no.3
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• pp.139-150
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• 2012

This paper presents an improved guidance algorithm for autonomous underwater vehicles (AUV) in 3D space for generating smoother vehicle turn during the course change at the way-points. The way-point guidance by the line-of-sight (LOS) method has been modified for correcting the reference angles to achieve minimal calculation and smoother transition at the way-points. The algorithm has two phases in which the first phase brings the vehicle to converge to a distance threshold point on the line segment connecting the first two way-points and the next phase generates an angular path with smoother transition at the way-points. Then the desired angles are calculated from the reference and correction angles. The path points are regularly parameterized in the spherical coordinates and mapped to the Cartesian coordinates. The proposed algorithm is found to be simple and can be used for real time implementation. The details of the algorithm and simulation results are presented.