• International Journal of Ocean System Engineering
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• 제2권3호
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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.

• International Journal of Ocean System Engineering
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• 제1권1호
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• pp.16-27
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• 2011

The depth and heading control of an autonomous underwater vehicle (AUV) are considered to follow the predetermined depth and heading angle. The proposed control algorithm was based on a sliding mode control, using estimated hydrodynamic coefficients. The hydrodynamic coefficients were estimated employing conventional nonlinear observer techniques, such as sliding mode observer and extended Kalman filter. Using the estimated coefficients, a sliding mode controller was constructed for a combined diving and steering maneuver. The simulated results of the proposed control system were compared with those of a control system that employed true coefficients. This paper demonstrated the proposed control system, and discusses the mechanisms that make the system stable and accurately follow the desired depth and heading angle in the presence of parameter uncertainty.

• 한국유체기계학회 논문집
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• 제16권1호
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• pp.24-31
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• 2013

The motion of living organisms such as birds, fishes, and insects, has been analyzed for the purpose of the design of MAV(Micro Air Vehicle) and NAV(Nano Air Vehicle). In this research, natural motion was considered to be applied to the determination of the geometry and motion of AUV(Autonomous Underwater Vehicle). The flapping motion of a number of hydrofoil shapes in AUV was studied, and at the same time, the optimization of the hydrofoil shape and flapping motion was executed that allow the highest thrust and efficiency. The harmonic motion of plunging and pitching of NACA 4 digit series models, was used for the numerical analysis. The meta model was made by using the kriging method in Optimization method and the experimental points of 49 were extracted for the OA(Orthogonal array) in DOE(Design of experiments). Parametric study using this experimental points was conducted and the results were applied to MGA(Micro Genetic Algorithm). The flow simulation model was validated to be an appropriate tool by comparing with experimental data and the optimized shape and motion of AUV was turned out to produce highest thrust and efficiency.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.347-350
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• 2006

Maritime and Ocean Engineering Research Institute (MOERI), a branch of KORDI, has designed and manufactured a model of an autonomous underwater vehicle (AUV) named ISiMI(Integrated Submergible for Intelligent Mission Implementation). ISiMI is an AUV platform to satisfy the various needs of experimental test required for development of challenging technologies newly investigated in the field of underwater robot; control and navigational algorithms and software architectures. The main design goal of ISiMI AUV is downsizing which will reduce substantially the operating cost compared to other vehicles previously developed in KORDI such as VORAM or DUSAUV. As a result of design and manufacturing process, ISiMI is implemented to be 1.2m in length, 0.17m in diameter and weigh 20 kg in air. A series of tank test is conducted to verify the basic functions of ISiMI in the Ocean Engineering Basin of MOERI, which includes manual control with R/F link, auto depth, auto heading control and a final approach control for underwater docking. This paper describes the implementation of ISiMI system and the experimental results to verify the function of ISiMi as a test-bed AUV platform.

• 한국해양공학회지
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• 제8권2호
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• pp.131-140
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• 1994

Dynamics of AUV has heavy nonlinearities and many unknown parameters due to its bluff shape and low cruising speed. Intelligent algorithms, therefore, are required to overcome these nonlinearities and unknown system dynamics. Several identification techniques have been suggested for the application of control of underwater vehicles during last decade. This paper applies the neural network to identification and motion control problem of AUVs. Nonlinear dynamic systems of an AUV are identified using feedforward neural network. Simulation results show that the learned neural network can generate the motion of AUV. This paper, also, suggest an adaptive control scheme up-dates the controller weights with reference model and feedforward neural network using error back propagation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1791-1796
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• 2004

Recently, great improvements have been made in developing autonomous underwater vehicles (AUVs) using stateof- the-art technologies for various kinds of sophisticated underwater missions. To meet increasing demands posed on AUVs, a powerful on-board computer system and an accurate sensor system with an well-organized control system architecture are needed. In this paper, a new control system architecture is proposed for AUV, ORCA (Oceanic Reinforced Cruising Agent) which is being currently developed by Korea Research Institute of Ships and Ocean Engineering (KRISO). The proposed architecture uses a hybrid architecture that combines a hierarchical architecture and a behavior based control architecture with an evaluator for coordinating between the architectures. This paper also proposed a sensor fusion structure based on the definition of 4 categories of sensors called grouping and 5-step data processing procedure. The development of the AUV, ORCA involving the system architecture, vehicle layout, and hardware configuration of on-board system are described.

• 한국정보통신학회논문지
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• 제10권11호
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• pp.1973-1977
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• 2006

본 논문에서는 IMU(Inertial Motion Unit), DVL(Doppler Velocity Log), USBL(Ultra Short Base Line) DGPS(Differential Global Positioning System) 등의 센서로부터 취득된 데이터를'융합하여 ROV(Remotely Operated Vehicle)와 AUV(Autonomous Underwater Vehicle)와 같은 수중체의 위치를 지구 전체영역에서 추정하기 위한 기본적인 알고리즘을 다루고 있다. 본 논문에 소개된 알고리즘은 6,000m급 과학 조사용 심해무인잠수정인 해미래[1]의 수중 위치추적에 사용될 예정이다.

• 한국지능시스템학회논문지
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• 제21권3호
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• pp.323-328
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• 2011

실제 시스템 적용에 있어서, 수중비행체(Underwater Flight Vehicle : UFV)의 자율제어(autonomous control)를 위한 3-D 장애물회피(obstacle avoidance) 시스템은 다음과 같은 문제점들을 가지고 있다. 즉, 소나(sonar)는 지역적 탐색영역 내에서 장애물의 거리(range)/방위(bearing) 정보를 제공하며, 자율수중운동체(Autonomous Underwater Vehicle : AUV) 관점에서 에너지 소비 및 음향학적 소음이 적은 시스템을 필요로 하며, 최대 피치 및 심도와 같은 UFV 운용 제약조건을 가진다. 나아가, 구조와 파라메터의 관점에 있어서 용이한 설계 절차를 요구한다. 이 문제를 해결하기 위해서 진화 전략(Evolution Strategy : ES) 및 퍼지논리 제어기(Fuzzy Logic Controller : FLC)를 이용하는 지능형 3-D 장애물회피 알고리즘이 제안되었다. 제안된 알고리즘의 성능을 검증하기 위해 UFV의 3-D 장애물회피가 수행되었다. 시뮬레이션 결과는 제안된 알고리즘이 실제 시스템에 존재하는 문제점들을 효과적으로 해결하고 있음을 보여준다.

• 제어로봇시스템학회논문지
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• 제19권9호
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• pp.768-773
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• 2013

In this paper, decoupled course, depth and roll controller design for an Autonomous Underwater Vehicle (AUV) and its performance test results are presented. Control system design is done using the PD control scheme based on a mathematical model of the AUV. Details of system implementation are given and the results of simulations and experiments using the prototype vehicle model are discussed. The designed controller was successfully applied to the nonlinear and coupled system under non-ideal actuator conditions.

• 로봇학회논문지
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• 제19권2호
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• pp.188-195
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• 2024

This paper proposes a photorealistic real-time dense 3D mapping system that utilizes a neural network-based image enhancement method and mesh-based map representation. Due to the characteristics of the underwater environment, where problems such as hazing and low contrast occur, it is hard to apply conventional simultaneous localization and mapping (SLAM) methods. At the same time, the behavior of Autonomous Underwater Vehicle (AUV) is computationally constrained. In this paper, we utilize a neural network-based image enhancement method to improve pose estimation and mapping quality and apply a sliding window-based mesh expansion method to enable lightweight, fast, and photorealistic mapping. To validate our results, we utilize real-world and indoor synthetic datasets. We performed qualitative validation with the real-world dataset and quantitative validation by modeling images from the indoor synthetic dataset as underwater scenes.