• 제목/요약/키워드: agricultural robot

검색결과 136건 처리시간 0.028초

Estimation of tomato maturity as a continuous index using deep neural networks

  • Taehyeong Kim;Dae-Hyun Lee;Seung-Woo Kang;Soo-Hyun Cho;Kyoung-Chul Kim
    • 농업과학연구
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    • 제49권4호
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    • pp.785-793
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    • 2022

  • In this study, tomato maturity was estimated based on deep learning for a harvesting robot. Tomato images were obtained using a RGB camera installed on a monitoring robot, which was developed previously, and the samples were cropped to 128 × 128 size images to generate a dataset for training the classification model. The classification model was constructed based on convolutional neural networks, and the mean-variance loss was used to learn implicitly the distribution of the data features by class. In the test stage, the tomato maturity was estimated as a continuous index, which has a range of 0 to 1, by calculating the expected class value. The results show that the F1-score of the classification was approximately 0.94, and the performance was similar to that of a deep learning-based classification task in the agriculture field. In addition, it was possible to estimate the distribution in each maturity stage. From the results, it was found that our approach can not only classify the discrete maturation stages of the tomatoes but also can estimate the continuous maturity.

  • https://doi.org/10.7744/kjoas.20220072 인용 PDF KSCI

콜로니 픽킹 로봇 시스템의 개발 (II) 로봇 시스템의 성능실험 - (Development of Robot System for Colony Picking (II) - The Performance test of developed robot system -)

  • 이현동;김기대;김찬수;나건영;이영규;임용표
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 2003년도 하계 학술대회 논문집
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    • pp.427-433
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    • 2003

  • 숙주세포가 분열될 때, 재조합 DNA 분자의 복제물이 자손에게 전달되며 거기서 벡터 복제가 일어난다. 수많은 세포 분열이 일어난 후, 동일한 숙주세포의 콜로니(colony), 혹은 클론(clone)이 생성된다. 이때 숙주세포의 분열은 배양액을 담은 용기에서 이루어진다. 박테리아 속의 배양된 콜로니에 재조합 DNA가 포함되어 있지 않으면 푸른색을 띠고, 재조합 DNA가 포함되어 있으면 흰색을 띠게된다. 이 흰색의 콜로니만을 추출해 내는 것이 바로 콜로니 픽킹(picking)이라 한다. (중략)

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GPS를 이용한 필드로봇의 PC기반 자율항법 제어 시스템 (PC controlled Autonomous Navigation System for GPS Guided Field Robot)

  • 한재원;박재호;홍성경;류영선
    • Journal of Biosystems Engineering
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    • 제34권4호
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    • pp.278-285
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    • 2009

  • Navigation system is applied in variety of fields including the simple location positioning, autopilot navigation of unmanned robot tractor, autonomous guidance systems for agricultural vehicles, construction of large field works that require high precision and map making process. Particularly utilization of GPS (Global Positioning System) is very common in the present navigation system. This study introduces a navigation system for autonomous field robot that travels to the pre-input path using GPS information. Performance of the GPS- based navigation is highly depended on its receiving rate because GPS receivers do not acquire any navigation information in the period between the refresh intervals. So this study presents an algorithm that improves an accuracy of the navigation by estimation the positional information during the blind period of a low rate GPS receiver. In fact the algorithm calculated the robot's heading in a 50 Hz rate, so the blind period of an 1 Hz GPS receiver is extensively covered. Consequently implementation of the algorithm to the GPS based navigation showed an improvement in guidance accuracy. The conventional field robot directly carried an expensive control computer and sensors onboard, therefore the miniaturization and weight reduction of the robot was limited. In this paper, the field robot carried only communication equipments such as GPS module, normal RC receiver, and bluetooth modem. This enabled the field robot to be built in an economic cost and miniature size.

  • https://doi.org/10.5307/JBE.2009.34.4.278 인용 PDF KSCI

로보트 비전을 이용한 대상물체의 위치 결정에 관한 연구 (Determination of Object Position Using Robot Vision)

  • Park, K.T.
    • 한국정밀공학회지
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    • 제13권9호
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    • pp.104-113
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    • 1996

  • In robot system, the robot manipulation needs the information of task and objects to be handled in possessing a variaty of positions and orientations. In the current industrial robot system, determining position and orientation of objects under industrial environments is one of major problems. In order to pick up an object, the roblt needs the information about the position and orientation of object, and between objects and gripper. When sensing is accomplished by pinhole model camera, the mathematical relationship between object points and their images is expressed in terms of perspective, i.e., central projection. In this paper, a new approach to determine the information of the supporting points related to position and orientation of the object using the robot vision system is developed and testified in experimental setup. The result will be useful for the industrial, agricultural, and autonomous robot.

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