• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.130-138
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• 2024

High-precision 3D Object Detection is a crucial component within autonomous driving systems, with far-reaching implications for subsequent tasks like multi-object tracking and path planning. In this paper, we propose a novel approach designed to enhance the performance of 3D Object Detection, especially in heading angle estimation by employing a moving object segmentation technique. Our method starts with extracting point-wise moving labels via a process of moving object segmentation. Subsequently, these labels are integrated into the LiDAR Pointcloud data and integrated data is used as inputs for 3D Object Detection. We conducted an extensive evaluation of our approach using the KITTI-road dataset and achieved notably superior performance, particularly in terms of AOS, a pivotal metric for assessing the precision of 3D Object Detection. Our findings not only underscore the positive impact of our proposed method on the advancement of detection performance in lidar-based 3D Object Detection methods, but also suggest substantial potential in augmenting the overall perception task capabilities of autonomous driving systems.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.31 no.1
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• pp.91-96
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• 1986

This study was carried out to clarify the barley grain development process under the double cropping paddy. The maximum length, width, and thickness of Baekdong were reached at 33,42, and 45 days after heading. They were not significantly reduced by 11, 7, and 5 days earlier harvesting than their above maximum develop-ing periods, respectively. Physiological maturity times were observed at about 40-46 days after heading, and the moisture contents were ranged 28-31 %. Practical maturity times were about 7 -8 days earlier than physiological ones. The beginning times of the sharp development phase of grain were delayed for two to ten days by delay of seeding times. However, the periods of the stationary and the lag development phases were about nine to ten days each and they were little changed by seeding times.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.170-170
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• 2022

Grain filling traits of rice were traced to determine the critical temperature that ceased grain filling process, from the late transplanted temperate rice varieties in the field conditions of2020 and 2021. The tested three varieties were transplanted six times with four target heading dates of 20 Aug. (control), 10 Sep., 20 Sep. and 30 Sep. Nine times of sampling were made from a week after heading with three replicates for each treatment. Development of grain filling percentage, grain dry weight and milled rice weight demonstrated sigmoid curves in the first and second transplants of 2020, and in the first to third transplants of 2021. The three grain filling traits in the 2020 third transplants and in the 2021 fourth transplants initially increased with the progress of grain development, and reached the peaks at certain time points, then decreased thereafter. Non-linear regression analyses, performed for the traits in the transplants that showed sigmoid curves except control, indicated that 95% of the final data (95% FD) was attained when the seven-day moving temperature (Sd-MovT) was 8.4-9.6℃, which excluded the cases when the temperature before the dates of 95% FD was lower than that on the dates of 95% FD. Sd-MovT on the date of peak data was 8.5-9.8℃ in the 2020 third transplants and 6.9-8.3℃ in the 2021 fourth transplants. Grain development was observed when seven-day mean temperature (Sd-MT) from 35 to 41 days after heading date was 9.4-10.8℃ in the 2020 third transplants and 10.1-11.9℃ in the 2021 fourth transplants. But Sd-MT of 8.7-9.1℃ in 2020 and 6.9-7.6℃ in 2021, at 42-48 days after heading, resulted in no progress of grain development. Overall, Sd-MovT at the point of stagnated grain development appeared in the range of 6.9-9.8℃. The lowest Sd-MT that showed the progress of grain development was 9.4-9.5℃ and the highest Sd-MT that showed no grain development was 9.1℃, both of which appeared in Odae and Haiami of the 2020 third transplants Therefore it is concluded that critical temperature for the grain development of temperate rice in natural conditions exists between 9.1℃ and 9.5℃.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.43 no.3
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• pp.212-221
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• 2007

This paper describes on the evaluation and management of work process in suction hopper dredger and grab bucket dredger as an application of a PC-based ECDIS system. The dynamic tracking of dredging bucket and the data logging of grab dredging information were performed by using the grab dredging vessel "Kunwoong G-18". The position and route tracking of the dredger moving toward the ocean dumping site of dredged material was performed by using the hopper dredging vessel "Samyang-7". The evaluation of wok process in the dredging field, for grab dredger, was continuously carried out on January to May, 2006, in Incheon Hang and for hopper dredger, on July to December, 2003, in Busan Hang, Korea. The dredging information, such as dredger's position, heading, dredging depth and route track which was individually time stamped during the dredging operation, was automatically processed in real-time on the ECDIS and displayed simultaneously on the S-57 ENC chart. From these results, we conclude that the ECDIS system can be applied as a tool in order to manage the work process during the dredging operation, and also in order to generate the factual record of the dredging activities that is sufficient for dredging inspector to accurately evaluate the contract performance even in the absence of a full-time onboard inspector.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.182-188
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• 2000

High-frequency electric resistance welding (HERW) technique is one of the most productive manufacturing method currently available for pipe and tube production because of its high welding speed. In this process, a heat input is controlled by skilled operators observing color and shape of bead but such a manual control can not provide reliability and stability required for manufacturing pipes of high grade quality because of a variety of bead shapes and noisy environment. In this paper, in an effort to provide reliable quality inspection, we propose a neural network-based method for classification of bead shape. The proposed method utilizes the structure of Kohonen network and is designed to learn the skill of the expert operators and to provide a good solution to classify bead shapes according to their welding conditions. This proposed method is implemented on the real pipe manufacturing process, and a series of experiments are performed to show its effectiveness.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.222-227
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• 2005

Resolving the integer ambiguity of GPS carrier phase measurements is the most important routine in precise positioning. In this paper, success rate is analyzed when using baseline information in the process of determining attitude. The result is verified through the simulation. Determining the initial position for the ambiguity resolution is estimated by using code measurement and baseline constraint. Success rate is estimated using covariance of the formed initial position. UKF has been used to overcome the nonlinear baseline condition during the process so that the higher success rate has been obtained compared with the general attitude determination.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.752-758
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• 2006

A GPS receiver provides much information such as calculated position, speed, heading, status of satellites, current time errors, etc. It is well-known that GPS signals from GPS receiver mounted on moving vehicle are often distorted, contaminated by various noises, and blocked by tunnel or tall buildings. The phenomenon often obstructs correct navigation especially when a vehicle keeps stopping or is moving in low speed. Therefore it is needed to pre-process the signals to adapt it to various applications. In this paper, an algorithm to pre-process the signals is proposed. For this, GPS data obtaining from uNAV GPS receiver are analyzed and classified based on dynamic characteristic. Then, the proposed algorithm is applied to the data and some test results are shown to verify the usefulness of the algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.115-120
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• 2006

This article propose a new idea of developing a hybrid scheme to achieve faster INS alignment with higher accuracy using a novel procedure to estimate the initial attitude angles that combines a Kalman filter and Adaptive Neuro-Fuzzy Inference System architecture. A tactical grade inertial measurement unit was applied to verify the performance of proposed scheme in this study. The preliminary results indicated the outstanding improvements in both time consumption for fine alignment process and accuracy of estimated attitude angles, especially in heading angles. In general, the improvement in terms of time consumption and the accuracy of estimated attitude estimated accuracy reached 80% and 70% respectively during alignment process after compensating the attitude angles estimated by an extended Kalman filter with 15 states using proposed approach. It is worth mentioned that the proposed approach can be implemented in general real time navigation applications.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.720-723
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• 2005

Ship motion is a complex controlled process with several hydrodynamic parameters that vary in wide ranges with respect to ship load condition, speed and surrounding conditions (such as wind, current, tide, etc.). Therefore, to effectively control ships in a designed track is always an important task for ship masters. This paper presents an effective adaptive autopilot ships that ensure the optimal accuracy, economy and stability characteristics. The PID control methodology is modified and parameters of a PID controller is designed to satisfy conditions for an optimal objective function that comprised by heading error, resistance and drift during changing course, and loss of surge velocity or fuel consumption. Designing of the controller for course changing process is based on the Model Reference Adaptive System (MRAS) control theory, while as designing of the automatic course keeping process is based on the Self Tuning Regulator (STR) control theory. Simulation (using MATLAB software) in various disturbance conditions shows that in comparison with conventional PID autopilots, the designed autopilot has several notable advantages: higher course turning speed, lower swing of ship bow even in strong waves and winds, high accuracy of course keeping, shorter time of rudder actions smaller times of changing rudder direction.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1098-1102
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• 2014

Localization of aerial vehicles and map building of flight environments are key technologies for the autonomous flight of small UAVs. In outdoor environments, an unmanned aircraft can easily use a GPS (Global Positioning System) for its localization with acceptable accuracy. However, as the GPS is not available for use in indoor environments, the development of a SLAM (Simultaneous Localization and Mapping) system that is suitable for small UAVs is therefore needed. In this paper, we suggest a vision-based SLAM system that uses vision sensors and an AHRS (Attitude Heading Reference System) sensor. Feature points in images captured from the vision sensor are obtained by using GPU (Graphics Process Unit) based SIFT (Scale-invariant Feature Transform) algorithm. Those feature points are then combined with attitude information obtained from the AHRS to estimate the position of the small UAV. Based on the location information and color distribution, a Gaussian process model is generated, which could be a map. The experimental results show that the position of a small unmanned aircraft is estimated properly and the map of the environment is constructed by using the proposed method. Finally, the reliability of the proposed method is verified by comparing the difference between the estimated values and the actual values.