• 대한조선학회논문집
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• 제58권4호
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• pp.253-261
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• 2021

This paper describes the process of evaluating maneuverability in still water of an unmanned surface vehicle based on data measured by performing sea trials. First, we set up a test scenario that is easy to analyze the maneuverability of the unmanned surface vehicle and to identify and verify the dynamics model. Since the attitude of hull varies according to the speed of the unmanned surface vehicle which has a planing hull shape, the relationship between waterjet RPM, speed and attitude is analyzed by performing straight forward tests at various speeds. The turning tests of the unmanned surface vehicle in which the waterjet angle rotates while turning are performed by changing the waterjet rotation angle under the condition of two representative speeds to analyze turning ability. The turning ability of the unmanned surface vehicle includes speed reduction, yaw rate, heel, and turing diameter at steady turning phase according to the speed and RPM.

• 한국해양공학회지
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• 제34권6호
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• pp.475-480
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• 2020

Underwater operating platforms face difficulties regarding power supply and communications. To overcome these difficulties, this study proposes a hybrid surface and underwater vehicle (HSUV) and presents the development of the platform, control algorithms, and results of field tests. The HSUV is capable of supplying reliable power to the unmanned underwater vehicle (UUV) and obtaining data in real time by using a tether cable between the UUV and the unmanned surface vehicle (USV). The HSUV uses global positioning system (GPS) and ultra-short base line sensors to determine the relative location of the UUV. Way point (WP) and dynamic positioning (DP) algorithms were developed to enable the HSUV to perform unmanned exploration. After reaching the target point using the WP algorithm, the DP algorithm enables USV to maintain position while withstanding environmental disturbances. To ensure the navigation performance at sea, performance tests of GPS, attitude/heading reference system, and side scan sonar were conducted. Based on these results, manual operation, WP, and DP tests were conducted at sea. WP and DP test results and side scan sonar images during the sea trials are presented.

• 센서학회지
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• 제33권5호
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• pp.391-398
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• 2024

Accurate positioning is essential for unmanned underwater vehicle (UUV) operations, particularly for long-term survey missions. To reduce the inherent positioning errors from the inertial navigation systems of UUVs, or dead reckoning, underwater terrain observations from sonar sensors are typically exploited. Within the framework of pose-graph optimization, we can generate submaps of the seafloor and use them to add loop-closure constraints to the pose graph by determining the best match between the submaps. However, this approach results in error accumulation in long-term operations because the quality of local submaps depends on the dead reckoning. Hence, we can adopt external acoustic positioning systems, such as an ultrashort baseline (USBL), to add global constraints to the existing pose graph. We assume that the acoustic transponder is installed on a UUV and that the acoustic transceiver is equipped in an unmanned surface vehicle trailing the UUV to maintain an acoustic connection between the vehicles. We simulate the terrain and USBL measurements as well as evaluate the performance of the UUV's pose estimation via online pose-graph optimization.

• 제어로봇시스템학회논문지
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• 제21권12호
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• pp.1089-1099
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• 2015

This paper proposes vision-based collision risk estimation method for an unmanned surface vehicle. A robust image-processing algorithm is suggested to detect target obstacles from the vision sensor. Vision-based Target Motion Analysis (TMA) was performed to transform visual information to target motion information. In vision-based TMA, a camera model and optical flow are adopted. Collision risk was calculated by using a fuzzy estimator that uses target motion information and vision information as input variables. To validate the suggested collision risk estimation method, an unmanned surface vehicle experiment was performed.

• 한국해양공학회지
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• 제33권6호
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• pp.510-517
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• 2019

Efficient path planning is essential for unmanned surface vehicle (USV) navigation. The A^* algorithm is an effective algorithm for identifying a safe path with optimal distance cost. In this study, a modified version of the A^* algorithm is applied for planning the path of a USV in a static and dynamic obstacle environment. The current study adopts the A^* approach while maintaining a safe distance between the USV and obstacles. Two important parameters-path length and computational time-are considered at various start times. The results demonstrate that the modified approach is effective for obstacle avoidance by a USV that is compliant with the International Regulations for Preventing Collision at Sea (COLREGs).

• 한국군사과학기술학회지
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• 제24권1호
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• pp.61-69
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• 2021

Recently, autonomous navigation technology is actively being developed due to the increasing demand of an unmanned surface vehicle(USV). Local planning is essential for the USV to safely reach its destination along paths. the dynamic window approach(DWA) algorithm is a well-known navigation scheme as a local path planning. However, the existing DWA algorithm does not consider path line tracking, and the fixed weight coefficient of the evaluation function, which is a core part, cannot provide flexible path planning for all situations. Therefore, in this paper, we propose a new DWA algorithm that can follow path lines in all situations. Fixed weight coefficients were trained using reinforcement learning(RL) which has been actively studied recently. We implemented the simulation and compared the existing DWA algorithm with the DWA algorithm proposed in this paper. As a result, we confirmed the effectiveness of the proposed algorithm.

• 제어로봇시스템학회논문지
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• 제22권9호
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• pp.723-732
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• 2016

This paper proposes an approach to fused navigation of an unmanned surface vehicle(USV) and to detection of the outlier or interference of global positioning system(GPS). The method fuses available sensor measurements through extended Kalman filter(EKF) to find the location and attitude of the USV. The method uses error covariance of EKF for detection of GPS outlier or interference. When outlier or interference of the GPS is detected, the method excludes GPS data from navigation process. The measurements to be fused for the navigation are GPS, acceleration, angular rate, magnetic field, linear velocity, range and bearing to acoustic beacons. The method is tested through simulated data and measurement data produced through ground navigation. The results show that the method detects GPS outlier or interference as well as the GPS recovery, which frees navigation from the problem of GPS abnormality.

• Journal of Advanced Research in Ocean Engineering
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• 제2권4호
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• pp.192-201
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• 2016

This study examined a PD controller and its application to automatic berthing control of an unmanned surface vehicle (USV). First, a nonlinear mathematical model was established for the maneuvering of the USV in the presence of environmental forces. A PD control algorithm was then applied to control the rudder and propeller during an automatic berthing process. The algorithm consisted of two parts, namely the forward velocity control and heading angle control. The control algorithm was designed based on longitudinal and yaw dynamic models of the USV. The desired heading angle was obtained using the "line of sight" method. Finally, computer simulations of automatic USV berthing were performed to verify the proposed controller subjected to the influence of disturbance forces. The results of the simulation revealed a good performance of the developed berthing control system.

• 대한조선학회논문집
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• 제59권2호
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• pp.125-133
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• 2022

This paper proposes a fault detection method for a Unmanned Surface Vehicle (USV) with overactuated system. Current status information for fault detection is expressed as a scalogram image. The scalogram image is obtained by wavelet-transforming the USV's control input and sensor information. The fault detection scheme is based on Convolutional Neural Network (CNN) algorithm. The previously generated scalogram data was transferred learning to GoogLeNet algorithm. The data are generated as scalogram images in real time, and fault is detected through a learning model. The result of fault detection is very robust and highly accurate.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2004년도 학술대회지
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• pp.123-130
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• 2004

Ocean developments gradually move to deep-sea in the 21 century. A deep-sea unmanned underwater vehicle is one of important tools for ocean resource survey. A marine cable plays an important role for the safe operation of a deep-sea unmanned underwater vehicle. The first cable of a deep-sea unmanned underwater vehicle is excited by surface vessel motion and shows non-linear dynamic behaviors. A numerical method is necessary for analysing the dynamic behaviour of the first marine cable. In this study, a numerical program is estabilished based on a finite difference method. The program is appled to a 6000m long cable for a deep-sea unmanned underwater vehicle and shows good reasonable results.