• 로봇학회논문지
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• 제17권2호
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• pp.142-151
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• 2022

With the advent of the 4th industrial revolution, autonomous driving technology is being commercialized in various industries. However, research on autonomous driving so far has focused on platforms with wheel-type platform. Research on a tracked platform is at a relatively inadequate step. Since the tracked platform has a different driving and steering method from the wheel-type platform, the existing research cannot be applied as it is. Therefore, a path-tracking algorithm suitable for a tracked platform is required. In this paper, we studied a path-tracking algorithm for a tracked platform based on a GPS sensor. The existing Pure Pursuit algorithm was applied in consideration of the characteristics of the tracked platform. And to compensate for "Cutting Corner", which is a disadvantage of the existing Pure Pursuit algorithm, an algorithm that changes the LAD according to the curvature of the path was developed. In the existing pure pursuit algorithm that used a tracked platform to drive a path including a right-angle turn, the RMS path error in the straight section was 0.1034 m and the RMS error in the turning section was measured to be 0.2787 m. On the other hand, in the variable LAD algorithm, the RMS path error in the straight section was 0.0987 m, and the RMS path error in the turning section was measured to be 0.1396 m. In the turning section, the RMS path error was reduced by 48.8971%. The validity of the algorithm was verified by measuring the path error by tracking the path using a tracked robot platform.

• 드라이브 ㆍ 컨트롤
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• 제18권4호
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• pp.77-83
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• 2021

With the progress in virtual reality technology, various virtual objects can be displayed using head-mounted displays (HMD). However, force feedback sensations such as pushing against a virtual object are not possible with an HMD only. Focusing on force feedback, desktop-type devices are generally used, but the user cannot move in a virtual space because such devices are fixed on a desk. With a wearable force feedback device, users can move around while experiencing force feedback. Therefore, the authors have developed a wearable force feedback device using a magnetorheological fluid clutch and pneumatic rubber artificial muscle, aiming at presenting the elasticity, friction, and viscosity of an object. To date, we have developed a wearable four-degree-of-freedom (4-DOF) force feedback device and have quantitatively evaluated that it can present commanded elastic, frictional, and viscous forces to the end effector. However, sensory evaluation with a human has not been performed. In this paper, therefore, we conduct a sensory evaluation of the proposed method. In the experiment, frictional and viscous forces are rendered in a virtual space using a 4-DOF force feedback device. Subjects are asked to answer questions on a 1- to 7-point scale, from 1 (not at all) to 4 (neither) to 7 (strongly). The Wilcoxon signed rank test was used for all data, and answer 4 (neither) was used as compared standard data. The experimental results confirmed that the user could feel the presence or absence of viscous and frictional forces. However, the magnitude of those forces was not sensed correctly.

• 드라이브 ㆍ 컨트롤
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• 제18권4호
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• pp.1-8
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• 2021

An electro proportional pressure control valve is mainly used to control the clutch of an agricultural tractor's automatic transmission. During transmission, the operating, hydraulic oil is mix with many kinds of contaminants. The contaminants can be trapped between the valve body and spool of the proportional pressure control valve leading to abnormal operating conditions and finally critical damage to the transmission hydraulic system. The present study aimed to verify the valve control algorithm as a basic study of developing control logic that removes contaminants between the spool and the body of the proportional pressure control valve. To develop the algorithm, MATLAB/SIMULINK was used. PWM method was used to control the applied solenoid coil current. The effectiveness of the algorithm was verified by comparing the actual pressure of the normal valve with the actual pressure of the abnormal valve. Based on the present study findings, when the algorithm was applied, the response of the valve pressure according to the current became stable and oil contaminated particles were removed. In the future study, the control algorithm will be optimized for the stability of the proportional pressure reducing valve, and it will be verified in consideration with the driving of the clutch.

• 산업융합연구
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• 제20권8호
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• pp.69-75
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• 2022

초등학교 주변에는 교통약자인 어린이 교통사고를 예방하기 위하여 어린이 보호구역내 스쿨존(school zone)을 지정하여 이 구역내에서는 차량 운행속도를 30km/h 미만으로 운행함에 따라 주·정차가 금지되어 있다. 하지만 우리나라는 OECD 국가 중 어린이 교통사고 사망률이 1위라는 불명예를 안고 있다. 이와 같은 배경하에 본 연구는 어린이 보호구역에서의 다양한 도로여건에 따라 불법 주·정차 차량으로 인한 운전자 시야확보 및 주행차량에 대한 인지의 어려움 등이 상존하고 있어, 이에 어린이 보호구역 내에 불법 주·정차방지 시스템을 구축함으로써 교통약자인 어린이들에 대해 교통사고방지와 운전자 안전운전에 대한 경각심 증진에 기여하기 위함에 연구의 목적을 두었다. 연구 방법으로는 주요선행연구와 문헌조사 및 분석을 바탕으로 주·정차방지시스템에 대한 구축방안을 제시하였다. 구축방안을 통해 교통사고 방지, 스마트한 운전자의 안전운행 유도, 보행자 안전의식 강화, 운전자의 안전의식 경각심 유도 등 효과를 기대할 수 있다.

• 한국재난정보학회 논문집
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• 제18권4호
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• pp.699-705
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• 2022

연구목적: 시퀀스제어는 제조, 유통, 건설, 의료 산업분야의 자동화 등에 응용되어 널리 사용하고 있다. 4차산업의 발전으로 제어분야에 인공지능 융합 기술이 산업에 중요한 요소가 되어가고 있다. 특히 기존 시스템에 마이크로프로세서와 인공지능이 융합된 설비의 안전성과 혁신성을 평가하고 신뢰성 높은 장비개발이 요구되고 있어 교육목적의 장비를 개발하여 해당분야의 발전을 견인하고자 한다. 연구방법: 자체 개발한 일체형 인공지능 컨트롤러 모듈은 기존의 시퀀스 및 PLC제어 회로에 인공지능 능력을 융합한 장비이다. 본 장비의 성능평가항목으로 동작, 음성, 문자, 색상 등의 인식 능력과 회로의 안정성, 신뢰성을 평가하였다. 결론: 시퀀스 및 PLC 회로를 설계 후 융합된 일체형 인공지능 컨트롤러 모듈의 성능평가항목이 모두 만족하였고 회로의 안전성과 신뢰성에 문제가 없는 것으로 나타났다.

• 드라이브 ㆍ 컨트롤
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• 제20권2호
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• pp.15-23
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• 2023

In this study, two-dimensional location of crops for auto weeding was detected using deep learning. To construct a dataset for soybean detection, an image-capturing system was developed using a mono camera and single-board computer and the system was mounted on a weeding robot to collect soybean images. A dataset was constructed by extracting RoI (region of interest) from the raw image and each sample was labeled with soybean and the background for classification learning. The deep learning model consisted of four convolutional layers and was trained with a weakly supervised learning method that can provide object localization only using image-level labeling. Localization of the soybean area can be visualized via CAM and the two-dimensional position of the soybean was estimated by clustering the pixels associated with the soybean area and transforming the pixel coordinates to world coordinates. The actual position, which is determined manually as pixel coordinates in the image was evaluated and performances were 6.6(X-axis), 5.1(Y-axis) and 1.2(X-axis), 2.2(Y-axis) for MSE and RMSE about world coordinates, respectively. From the results, we confirmed that the center position of the soybean area derived through deep learning was sufficient for use in automatic weeding systems.

• 반도체디스플레이기술학회지
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• 제21권4호
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• pp.65-70
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• 2022

In manufacturing and semiconductor industries, transfer robots increase productivity through accurate and continuous work. Due to the nature of the semiconductor process, there are environments where humans cannot intervene to maintain internal temperature and humidity in a clean room. So, transport robots take responsibility over humans. In such an environment where the manpower of the process is cutting down, the lack of maintenance and management technology of the machine may adversely affect the production, and that's why it is necessary to develop a technology for the machine failure diagnosis system. Therefore, this paper tries to identify various causes of failure of transport robots that are widely used in semiconductor automation, and the Prognostics and Health Management (PHM) method is considered for determining and predicting the process of failures. The robot mainly fails in the driving unit due to long-term repetitive motion, and the core components of the driving unit are motors and gear reducer. A simulation drive unit was manufactured and tested around this component and then applied to 6-axis vertical multi-joint robots used in actual industrial sites. Vibration data was collected for each cause of failure of the robot, and then the collected data was processed through signal processing and frequency analysis. The processed data can determine the fault of the robot by utilizing machine learning algorithms such as SVM (Support Vector Machine) and KNN (K-Nearest Neighbor). As a result, the PHM environment was built based on machine learning algorithms using SVM and KNN, confirming that failure prediction was partially possible.

• 한국군사과학기술학회지
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• 제26권3호
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• pp.227-233
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• 2023

In this paper, to substitute the existing TWTA(Travailing Wave Tube Amplifier) component in small radar system, we developed the Ku band SSPA(Solid-State Power Amplifier) based on the fabrication of power MMIC (Monolithic Microwave Integrated Circuit) chips. For the development of the 500 W SSPA, the 40 W-grade power MMIC was designed by ADS(Advanced Design System) at Keysight company with UMS GH015 library, and was processed by UMS foundry service. And 70 W main power modules were achieved the 2-way T-junction combiner method by using the 40 W-grade power MMICs. Finally, the 500 W SSPA was fabricated by the wave guide type power divider between the drive power amplifier and power modules, and power combiner with same type between power modules and output port. The electrical properties of this SSPA had 504 W output power, -58.11 dBc spurious, 1.74 °/us phase variation, and -143 dBm/Hz noise level.

• 드라이브 ㆍ 컨트롤
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• 제20권4호
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• pp.27-34
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• 2023

Weeding in orchards is closely associated with productivity and quality. The customary weeding process is both labor-intensive and time-consuming. To solve the problems, there is need for automation of agricultural robots and machines in the agricultural field. On the other hand, orchards have complicated working areas due to narrow spaces between trees and amorphous terrain. Therefore, it is necessary to develop customized robot technology for unmanned weeding work within the department. This study developed a path generation and path control method for unmanned weeding according to the orchard environment. For this, the width of the weeding span, the number of operations, and the width of the weeding robot were used as input parameters for the orchard environment parameters. To generate a weeding path, a weeding robot was operated remotely to obtain GNSS-based location data along the superheated center line, and a driving performance test was performed based on the generated path. From the results of orchard field tests, the RMSE in weeding period sections was measured at 0.029 m, with a maximum error of 0.15 m. In the steering period within row and steering to the next row sections, the RMSE was 0.124 m, and 0.047 m, respectively.

• 한국음향학회지
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• 제28권5호
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• pp.441-446
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• 2009

본 논문에서는 오디오 정보 분석을 이용하여 골프 통영상을 자동 색인하는 알고리즘을 제안한다. 제안하는 알고리즘에서는 입력되는 골프 동영상을 비디오 신호와 오디오 신호로 분리한 후에, 연속적인 오디오 스트림을 Adaboost Cascade 분류방식을 통하여 스튜디오 환경에서의 아나운서의 음성구간, 선수이름이 TV 화면에 소개 될 때 수반되는 음악구간, 선수들의 플레이에 따라 반응하는 관중들의 박수 및 환호성 소리구간, 필드에서의 레포터의 음성구간, 바다나 바람 등의 필드환경 잡음 사운드구간 등의 5가지 구간으로 분류한다. 그리고 드라이브 샷, 아이런 샷과 퍼팅 샷 시에 발생하는 스윙 사운드는 onset 검출과 변조스펙트럼 검증 방법을 통해 검출되며, 관객의 박수 소리 구간과 결합하여 액션 및 하이라이트를 효율적으로 색인할 수 있게 한다. 제안된 알고리즘은 오디오 신호의 간단한 연산을 통해 의미를 지니고 있는 기본구조들을 검출하기 때문에 골프 동영상에서 사용자가 원하는 부분을 빠르게 브라우징하는 임베이디드 시스템에 적용가능하다.