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A Novel End-effector for Tomato Harvesting Robot: Mechanism and Evaluation
Jongpyo Jun,Jaehwi Seol,Hyoung Il Son 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
The application of robots to the agricultural sector has significantly improved productivity in the field. Studies investigating various forms of end-effectors are being carried out constantly, especially in relation to the harvests of fruits that require a lot of labor. However, the majority of studies focus on stably cutting the pedicel after accurately recognizing the target, while there is relatively little interest in the method and process of transferring agricultural produce after the harvest. The development of a dedicated end-effector is essential to reduce the duration of the entire procedure, which is a significant goal in harvest-related research. This entails comprehensive consideration of the transfer process. To address this issue, in this paper, we propose an integrated end-effector, which enables almost simultaneous execution of harvesting and transfer of tomatoes. Further, a modular mechanism is introduced to improve the performance of harvesting robots, and future directions of research are outlined.
ULEV-Ⅱ 규제대응용 배가스 후처리 시스템 구성을 위한 촉매 활성 연구
유종표(Jongpyo Yoo),신병선(Byeongseon Shin),홍석진(Seokjin Hong),권정민(Jungmin Kwon),김상수(Sangsoo Kim),정명근(Myounggeun Jung) 한국자동차공학회 2004 한국자동차공학회 춘 추계 학술대회 논문집 Vol.- No.-
To meet the ULEV-Ⅱ legislation, the catalytic of new technology catalyst has been discussed for exhaust gas aftertreatment system. For evaluating the performance of the new technology catalyst, engine dynamometer test and vehicle test were conducted. In the engine dynamometer test, it was proved that LOT & OSC performance of new technology catalyst had better than that of tri-metal catalyst. In addition, de-NOx activity was improved under cold start in FTP-75 mode. From the result of the test, the new technology catalyst is proposed for a optimized exhaust gas aftertreatment system for ULEV-Ⅱ.
디지털 트윈을 적용한 식물공장 내 식물 성장 예측모델 연구
이종표(JongPyo Lee),신원섭(WonSeop Shin),강정아(Jeonga Kang),권유정(YuJeong Kwon),정길연(GilYeon Jung),최정열(JungYul Choi) 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2
본 논문은 식물공장의 생산성 향상을 위해서 디지털 트윈을 적용한 식물 공장 내 식물 성장 예측모델을 연구하였다. 이를 위해서 현실 및 디지털 트윈 식물공장 테스트베드를 제작하였으며 4가지의 환경에서 식물 성장 데이터를 수집하였다. 수집한 데이터를 이용하여 식물 성장 데이터를 예측하는 머신러닝 모델을 구축하였으며, 구축한 모델을 사용하여 측정값과 예측값을 비교하여 정확성을 확인하였다.