• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.1034-1037
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• 2019

본 논문은 진공을 이용한 흡착방식과 바퀴형 이동방식을 사용하는 벽면 이동로봇의 구성과 로봇 내부에서의 균열검출 및 처리 프로세스에 관한 연구이다. 임베디드 시스템에서 기계학습을 이용한 균열검출을 구현하기 위해 YOLO v3를 수정하여 구동하였으며, 검출된 균열의 영상을 저장하고 위치 정보를 추정하였다. 또한, 균열 정보를 수집하기 위해 고정 IP를 갖는 서버를 구축하고 각 기기 간의 효율적인 통신 네트워크를 구성하였다. 본 기술은 균열검출 작업뿐만 아니라 보수작업에도 활용될 수 있어, 대형 구조물과 건축물 등의 안전진단뿐만 아니라 안전성 향상에 이바지할 수 있을 것으로 예상한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.1071-1074
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• 2015

본 논문은 진공을 이용한 흡착방식과 바퀴형 이동방식을 이용하고 환경 탐지용 센서를 부착한 벽면 이동형 로봇의 물리적 해석을 통한 이동 성능 개선에 관한 연구로서, 대형 구조물의 안전 검사 및 위험한 시설물의 보수 작업등을 보조하기 위한 목적이 있다. 로봇의 무게에 따른 중력을 견딜 수 있는 강력한 진공흡착방식과 고성능 모터 제어에 의한 바퀴 이동방식을 혼합하고 효율적으로 평형을 유지 또는 제어하기 위하여 로봇에 미치는 다양한 힘과 모멘트를 분석하고 수식화 하였으며 기존의 수직이동 속도를 개선하기 위한 로봇의 물리적 변수를 추출하여 변수와 이동력간의 관계를 고찰하였다.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.288-295
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• 2022

This study shows a system identification method of a balancing loading device for a stair climbing delivery robot. The balancing loading device is designed as a 2-axes gimbal structure and is interpreted as two independent pendulum structures for simplifying. The loading device's properties such as mass, moment of inertia, and position of the center of gravity are changeable for luggage. The system identification process of the loading device is required, and the controller should be optimized for the system in real-time. In this study, the system identification method is based on least squares method to estimate the unknown parameters of the loading device's dynamic equation. It estimates the unknown parameters by calculating them that minimize the error function between the real system's motion and the estimated system's motion. This study improves the accuracy of parameter estimation using a null space solution. The null space solution can produce the correct parameters by adjusting the parameter's relative sizes. The proposed system identification method is verified by the simulation to determine how close the estimated unknown parameters are to the real parameters.

• Journal of Bio-Environment Control
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• v.23 no.2
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• pp.123-130
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• 2014

Oriental melon (Cucumis melo var. makuwa) should be cultivated on the soil and be harvested. It is difficult to find because it is covered with leaves, and furthermore, it is very hard to grip it due to its climbing stems. This study developed and tested oriental melon harvesting robots such as an end-effector, manipulator and identification device. The end effector is divided into a gripper for harvest and a cutter for stems. In addition, it was designed to control the gripping and cutting forces so that the gripper could move four fingers at the same time and the cutter could move back and forth. The manipulator was designed to realize a 4-axis manipulator structure to combine orthogonal coordinate-type and shuttle-type manipulators with L-R type model to rotate based on the central axis. With regard to the identification device, oriental melon was identified using the primary identification global view camera device and secondary identification local view camera device and selected in the prediction of the sugar content or maturity. As a result of the performance test using this device, the average harvest time was 18.2 sec/ea, average pick-up rate was 91.4%, average damage rate was 8.2% and average sorting rate was 72.6%.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.25 no.4
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• pp.287-292
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• 2012

In this study, Multi-Channel Magnetic Flux Leakage(MFL) sensor - based inspection system was applied to monitor the condition of cables. This inspection system measures magnetic flux to detect the local faults(LF) of steel cable. To verify the feasibility of the proposed damage detection technique, an 8-channel MFL sensor head prototype was designed and fabricated. A steel cable bunch specimen with several types of damage was fabricated and scanned by the MFL sensor head to measure the magnetic flux density of the specimen. To interpret the condition of the steel cable, magnetic flux signals were used to determine the locations of the flaws and the level of damage. Measured signals from the damaged specimen were compared with thresholds set for objective decision making. In addition, the magnetic flux density values measured from every channel were summed to focus on the detection of axial location. And, sum of flux density were displayed with threshold. Finally, the results were compared with information on actual inflicted damages to confirm the accuracy and effectiveness of the proposed cable monitoring method.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.115-123
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• 2021

Pine nuts are Korea's representative nut forest products and profitable crops. However, pine nuts are harvested by climbing the trees themselves, thus the risk is high. In order to solve this problem, it is necessary to harvest pine nuts using a robot or an unmanned aerial vehicle(UAV). In this paper, we propose a deep learning based detection method for harvesting pine nut in UAV aerial images. For this, a video was recorded in a real pine forest using UAV, and a data augmentation technique was used to supplement a small number of data. As the data for 3D detection, Unity3D was used to model the virtual pine nut and the virtual environment, and the labeling was acquired using the 3D transformation method of the coordinate system. Deep learning algorithms for detection of pine nuts distribution area and 2D and 3D detection of pine nuts objects were used DeepLabV3+, YOLOv4, and CenterNet, respectively. As a result of the experiment, the detection rate of pine nuts distribution area was 82.15%, the 2D detection rate was 86.93%, and the 3D detection rate was 59.45%.