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- 저자 : Nakyong Ko (검색결과 3 건)
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IPC를 통해 조정되는 다중 로봇의 동작 시뮬레이터 개발
서동진(DongJin Seo),고낙용(NakYong Ko),김성준(SungJun Kim) 대한기계학회 2005 대한기계학회 춘추학술대회 Vol.2005 No.11
This paper focuses on building multiple robot simulation program controlling the robots via wireless internet and inter-process communication. We tested the proposed simulation program in real heterogeneous multiple robot systems. One of them is TRESTLE project which is a research project in The Robotics Institute of Carnegie Mellon University. The robots in the simulation system are as the followings: a mobile manipulators, crane robot, roving eyes. Also it is tested for motion planning of the Nomad Super Scout II. Using the simulation program reduces a lot of time and cost in algorithm development and also reduces the dangerous job of real hardware test. The simulator is useful to make efficient motion plan of multiple robots as well as verification of the safe motion, So it saves time and cost and reduces possible safety problem.
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Multi-Functional Brain Computer Interface Using Convolutional Neural Networks
Woosung Choi,Honggi Yeom,Nakyong Ko 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
Brain-computer interface (BCI) is a promising technology that controls computers or machines using brain signals. With this technology, people with various disabilities, such as neural paralysis, and spinal cord injury can control electric devices or express their intention by thinking. However, previous BCI studies have a limitation that they can predict only one type of intention. To use the BCI system in daily life, the BCI user should be able to achieve various tasks such as moving, text typing, and arm movements. In this paper, we propose a multi-functional BCI method that can predict various intentions simultaneously. To classify multiple intentions, we proposed two prediction models using Neural Networks (NN) and Convolutional Neural Networks (CNN) models. To evaluate the proposed BCI system, the classification accuracy of the model was measured and compared using steady state visually evoked potential (SSVEP), sensory motor rhythm (SMR), and both of them (Multiple Intention). The average prediction accuracies were 22.46% in NN, 55.86% in CNN. These results indicate that the proposed multi-functional BCI can predict multiple intentions. It also means that users of the proposed BCI system can control various electric devices simultaneously.
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Koungsuk Kim,Kisoo Kang,Hyunchul Jung,Nakyong Ko 대한기계학회 2004 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.18 No.9
This paper describes the speckle shearing interferometry, a non-destructive optical method, for quantitative estimation of void defect and monitoring separation defect inside of a pneumatic tire. Previous shearing interferometry has not supplied quantitative result of inside defect, due to effective factors. In the study, factors related to the details of an inside defect are classified and optimized with pipeline simulator. The size and the shape of defect can be estimated accurately to find a critical point and also is closely related with shearing direction. The technique is applied for quantitative estimation of defects inside of a pneumatic tire. The actual traveling tire is monitored to reveal the cause of separation and the starting points. And also unknown void defects on tread are inspected and the size and shape of defects are estimated which has good agreement with the result of visual inspection.
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