• Journal of Ocean Engineering and Technology
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• v.11 no.3
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1868-1878
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• 2016

This paper proposes a novel velocity estimator for long-term underwater navigation of autonomous underwater vehicles(AUVs). Provided that an external position fix is not given, a viable goal in designing a underwater navigation algorithm is to reduce the divergence rate of position error only using the sporadic velocity information obtained from Doppler velocity log(DVL). For such case, the performance of underwater navigation eventually depends on accuracy and reliability of external velocity information. This motivates us to devise a velocity estimator which can drastically enhance the navigation performance even when the DVL measurement is unavailable. Incorporating the Gertler-Hagen hydrodynamics model of an AUV with the measurement models of velocity and depth sensors, the velocity estimator design problem is resolved using the extended Kalman filter. Different from the existing methods in which an AUV simulator is regarded as a virtual sensor, our approach is less sensitive to the model uncertainty often encountered in practice. This is because our velocity filter estimates the simulator errors with sensor aids and furthermore compensates these errors based on the indirect feedforward manner. Through the simulations for typical AUV navigation scenarios, the effectiveness of the proposed scheme is demonstrated.

• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• Journal of Korean Port Research
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• v.13 no.1
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• pp.87-100
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• 1999

This study was focused on analyzing the headway of various types of trailer in Pusan city with the high heavy vehicle rate. Then Passenger Car Equivalent(PCE) was calibrated in order to identify the impact of trailers in the traffic flow at the signalized intersections. To fulfill this goal types of trailer were classified into five categories such as full trailer semi-trailer unloaded semi-trailer semi-trailer loaded with 20ft container and semi-trailer loaded with 40ft container and Passenger Car Equivalents were identified. the Results are as follows: 1) The PCE’s were 2.64, 1.51, 2.09, 2.16 and 2.23 respectively. 2) The saturation flow rate on the signalized intersection was lower than that on the multi-lane highway in the big city of Korea. 3) The start-up delay on the thru lane was similar to the average value in our country but the start-up delay on the left-turn lane was longer than the average value in our country by the impact of container Vehicles.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.320-326
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• 2009

Providing visual field for a driver is one of the most important things for safe driving. Therefore, it will be a first step fur the safe driving that the driver recognizes front and back outside scenes within short time in the car. Specially, it is essential to take the visual field in frequently foggy area where the traffic accident can cause highest rank in the number of deaths. In this paper, our technique can provide the visual field by displaying the location of neighboring vehicles on the monitoring system, embedded board navigator in the car, using the location information of the vehicles from GPS(Global Positioning System) in real time. It is expected that this system can contribute to help safe driving and to lower collision accidents by guiding to cope with unexpected circumstances.

• The Journal of Korea Robotics Society
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• v.12 no.2
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• pp.173-183
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• 2017

This paper proposes an integrated positioning system to localize a moving object in the shadow-area that exists in the water tank. The new water tank for underwater robots is constructed to evaluate the navigation performance of underwater vehicles. Several sensors are integrated in the water tank to provide the position information of the underwater vehicles. However there are some areas where the vehicle localization becomes very poor since the very limited sensors such as sonar and depth sensors are effective in underwater environment. Also there are many disturbances at sonar data. To reduce these disturbances, an extended Kalman filter has been adopted in this research. To localize the underwater vehicles under the hostile situations, a SVR (Support Vector Regression) has been systematically applied for estimating the position stochastically. To demonstrate the performance of the proposed algorithm (an extended Kalman filter + SVR analysis), a new UI (User Interface) has been developed.

• Journal of Korea Multimedia Society
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• v.20 no.4
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• pp.649-659
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• 2017

Typically, a smart car is equipped with access to the Internet and a wireless local area network. Moreover, a smart car is equipped with a global positioning system (GPS) based navigation system that presents a map to a user for recommending the shortest path to a desired destination. This paper presents the design and implementation of a real-time shortest path search system for directed and dynamic roads. Herein, we attempt to simulate real-world road environments, while considering changes in the ratio of directed roads and in road conditions, such as traffic accidents and congestions. Further, we analyze the effect of the ratio of directed roads and road conditions on the communication cost between the server and vehicles and the arrival times of vehicles. In this study, we compare and analyze distance-based shortest path algorithms and driving time-based shortest path algorithms while varying the number of vehicles to search for the shortest path, road conditions, and ratio of directed roads.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.3
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• pp.395-405
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• 2024

This study provides a thorough examination of Unmanned Ground Vehicles(UGVs), focusing on crucial technologies and trends across major global markets. It includes an in-depth patent analysis revealing the dominant positions of the United States and the European Union in this field. Additionally, it underscores substantial advancements made by China, Japan, and Korea since 2010. Using Latent Dirichlet Allocation(LDA)-based patent text mining, the study identified key technology areas in UGV development, such as advanced control systems, navigation technologies, power supply mechanisms, and sensing and communication tools. Through linear regression analysis, the study predicted the future paths of these technology areas, offering important insights into the evolving world of UGV technology. The findings can provide strategic guidance for stakeholders in the defense, commercial, and academic sectors, pointing out the future directions in UGV advancements.

• Journal of Advanced Navigation Technology
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• v.28 no.3
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• pp.254-261
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• 2024

Accurate guidance during landing and take-off is important, and instrument landing system (ILS) has been used for stability and verification. Regular inspections are conducted for stable operation, and there is research to perform inspection using drones in addition to ground vehicles and measurement aircraft. Using SDR and single board computer, which can receive wide frequency range, we designed a small system that receives and processes localizer signals through GNU Radio. To check signal processing characteristics through GNU Radio, we simulated with MATLAB Simulink and confirmed the theoretical values. Difference in depth of modulation (DDM) and approach angle can be calculated when the aircraft enters the runway. And GNU Radio implemented real-time signal processing wirelessly using transmission control protocol (TCP). This gives the results within the error of 0.5% when the aircraft entered the runway center line and 0.27% for the angle of 1° degree. Compared to the inspecting and maintaining ILS signals using aircraft or ground vehicles, it is possible to implement a receiving system using small SDR that can be mounted for drone.

• Journal of Korean Port Research
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• v.14 no.3
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• pp.303-312
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are lane angle, distance error and real position of other vehicles, we should calculate the reference steering angle.