• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.836-839
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• 2004

Qualitative elevation of products is very important Part. A business racking us brains to find for qualitative elevation of products. Recently, measurement accuracy of a non-contact 3D scanner has been rapidly improving. As a result, the number application cases of non-contact 3D scanners are increasing. A non-contact 3D scanner is capable of measuring a curved surface rapidly and has high resolution. It is more affordable and potable than the CMMs, It is therefore expected to be applied more frequently in more diverse industries. Automating the measuring process using a non-contact 3D scanner and developing a technology, which allows a user to measure easily, will eventually improve the quality of products. As their inspection and analysis processes improve.

• Journal of Mechanical Science and Technology
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• 제16권6호
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• pp.762-769
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• 2002

This paper presents how effective it is to use many features for improving the speed and accuracy of visual servo systems. Some rank conditions which relate the image Jacobian to the control performance are derived. The focus is to describe that the accuracy of the camera position control in the world coordinate system is increased by utilizing redundant features in this paper. It is also proven that the accuracy is improved by increasing the number of features involved. Effectiveness of the redundant features is evaluated by the smallest singular value of the image Jacobian which is closely related to the accuracy with respect to the world coordinate system. Usefulness of the redundant features is verified by the real time experiments on a Dual-Arm robot manipulator made by Samsung Electronic Co. Ltd..

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.255-260
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• 2001

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C31 is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Performance of the neural controller is illustrated by simulation and experimental results for a SCARA robot.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 추계학술대회 논문
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• Design & Manufacturing
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• 제16권4호
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• pp.60-66
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• 2022

Recently, with the development of industry and the improvement of living standards, various wastes are generated along with the production of various products. Most of these wastes are used as containers for products, and plastic or aluminum is used. Various attempts are being made to automate the classification of these wastes due to the high labor cost, but most of them are solved by manpower due to the geometrical shape change due to the nature of the waste. In this study, in order to automate the waste sorting task, Deep Learning technology is applied to a robot system for waste sorting and a vision system for waste sorting to effectively perform sorting tasks according to the shape of waste. As a result of the experiment, a Deep Learning parameter suitable for waste sorting was selected. In addition, through various experiments, it was confirmed that 99% of wastes could be selected in individual & group image learning. It is expected that this will enable automation of the waste sorting operation.

• 산업진흥연구
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• 제7권4호
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• pp.9-15
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• 2022

본 연구는 기피공정중 하나인 롤밴딩 공정의 자동화시스템을 평가하였다. 그 결과 기존 1시간에 20개의 장약통을 생산하는 효율성을 1시간에 50개를 생산하는 공정으로 변화시켰다. 생산량의 평균값은 1시간당 57.6개의 생산, 반복정밀도의 오차는 0.03mm, 평균 롤 직경 오차값은 0.49mm, 평균 정렬 오차값은 0.09mm, 평균 공정리드타임은 43.21초로 나타났다. 생산성, 반복정밀도, 불량률, 얼라인 불량률, 공정 리드타임 등 구체적인 평가 방식을 제시하였다. 이를 통하여 자동화된 시스템을 검증하였다. 추후 본 연구에 수행된 내용들이 다른 자동화 시스템의 검증에 도움이 될 것으로 사료된다.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.405-413
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• 2006

A novel approach based on genetic algorithms (GA) is developed to find a global minimum-jerk trajectory of a space robotic manipulator in joint space. The jerk, the third derivative of position of desired joint trajectory, adversely affects the efficiency of the control algorithms and stabilization of whole space robot system and therefore should be minimized. On the other hand, the importance of minimizing the jerk is to reduce the vibrations of manipulator. In this formulation, a global genetic-approach determines the trajectory by minimizing the maximum jerk in joint space. The planning procedure is performed with respect to all constraints, such as joint angle constraints, joint velocity constraints, joint angular acceleration and torque constraints, and so on. We use an genetic algorithm to search the optimal joint inter-knot parameters in order to realize the minimum jerk. These joint inter-knot parameters mainly include joint angle and joint angular velocities. The simulation result shows that GA-based minimum-jerk trajectory planning method has satisfactory performance and real significance in engineering.

• Journal of Information Processing Systems
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• 제19권6호
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• pp.730-744
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• 2023

The topic of this paper is the recognition of human activities using egocentric vision, particularly captured by body-worn cameras, which could be helpful for video surveillance, automatic search and video indexing. This being the case, it could also be helpful in assistance to elderly and frail persons for revolutionizing and improving their lives. The process throws up the task of human activities recognition remaining problematic, because of the important variations, where it is realized through the use of an external device, similar to a robot, as a personal assistant. The inferred information is used both online to assist the person, and offline to support the personal assistant. With our proposed method being robust against the various factors of variability problem in action executions, the major purpose of this paper is to perform an efficient and simple recognition method from egocentric camera data only using convolutional neural network and deep learning. In terms of accuracy improvement, simulation results outperform the current state of the art by a significant margin of 61% when using egocentric camera data only, more than 44% when using egocentric camera and several stationary cameras data and more than 12% when using both inertial measurement unit (IMU) and egocentric camera data.

• 한국정보통신학회논문지
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• 제18권3호
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• pp.503-509
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• 2014

본 논문에서는 이동 로봇의 군집 제어를 위해 실시간 적응 신경 회로망 보상기를 갖는 PID 제어기를 제안한다. 전체 제어 시스템은 선도-추종 로봇 접근법에 의한 기구학 제어기와 이동 로봇의 동역학을 고려한 동적 제어기로 구성되어 있다. 동적 제어기는 PID 제어기에 동특성 변화를 보상하고 성능을 개선시키기 위해 실시간 학습 기능을 가진 신경 회로망 보상기로 구성하였다. 모의실험을 통해 원형 궤적과 직선 궤적에 대해 PID 제어기와 신경 회로망 보상기의 성능을 비교하였다. 이를 통해 실시간 학습 기능을 가진 신경 회로망 보상기가 PID 제어기의 성능을 향상시킴으로써 군집 제어에서 추종 로봇의 추종 성능을 향상시키는 것을 확인하였다.

• 비파괴검사학회지
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• 제22권3호
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• pp.254-260
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• 2002

화력발전소 보일러 튜브 및 대형 유체수송관의 자동 진단을 위해 비파괴검사 방법을 사용하는 두 가지 형태의 이동로봇을 개발하였다. 개발된 이동로봇은 보일러 튜브 또는 유체수송관의 외면을 주행하면서 전자기 초음파 탐촉자를 이용하여 파이프 벽면에 발생하는 미세한 구멍, 균열 또는 부식 및 침식에 의한 감육 등과 같은 결함을 검출한다. 이와 같은 이동로봇을 이용한 결합 검출의 자동화는 열악한 환경에서 작업자의 위험 없이 대형 구조물의 중대한 결함을 방지하는 유용한 수단으로 활용될 수 있다.