• Title/Summary/Keyword: 협동 로봇

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Design and Implementation of OPC UA-based Collaborative Robot Guard System Using Sensor and Camera Vision (센서 및 카메라 비전을 활용한 OPC UA 기반 협동로봇 가드 시스템의 설계 및 구현)

  • Kim, Jeehyeong;Jeong, Jongpil
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.6
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    • pp.47-55
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    • 2019
  • The robot is the creation of new markets and various cooperation according to the manufacturing paradigm shift. Cooperative management easy for existing industrial robots, robots work on productivity, manpower to replace the robot in every industry cooperation for the purpose of and demand increases.to exist But the industrial robot at the scene of the cooperation working due to accidents are frequent, threatening the safety of the operator. Of industrial site is configured with a robot in an environment ensuring the safety of the operator to and confidence to communicate that can do the possibility of action.Robot guard system of the need for development cooperation. The robot's cooperation through the sensors and computer vision task within a radius of the double to prevent accidents and accidents should reduce the risk. International protocol for a variety of industrial production equipment and communications opc ua system based on ultrasonic sensors and cnn to (Convolution Neural Network) for video analytics. We suggest the cooperation with the robot guard system. Robots in a proposed system is unsafe situation of workers evaluating the possibility of control.

Vision-based Joint Defect Tracking by Motion Fault Diagnosis of Collaborative Robots (협동로봇 동작 오류 진단을 통한 비전 기반 조인트 결함 추적 기법)

  • Hui-Chan Yang;Jinse Kim;Dong-Yeon Yoo;Jung-Won Lee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.595-596
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    • 2023
  • 스마트팩토리의 핵심 설비 기기인 협동로봇의 유지보수를 위해 다양한 센서 데이터를 활용한 딥러닝 기반 결함 진단 연구가 확대되고 있다. 하지만 협동로봇은 기계적 특성과 수행하는 작업의 다양성으로 인해 내부 센서 데이터의 복잡도가 매우 높아 고정적인 결함 진단 기법을 적용하기 어렵다. 따라서 본 논문은 협동로봇의 동작 패턴을 직관적이고 신속하게 인지할 수 있는 비전 기술을 활용하여, 동작 오류 진단을 기반으로 원인이 되는 조인트 결함 위치를 추적하는 딥러닝 기법을 제안한다.

Improvement for the Safety on the Automobile-Parts Assembly Process using Collaborative Robot through Risk Assessment : Disk snap ring assembly process mainly (위험성 평가를 통한 협동로봇 활용 자동차부품 조립공정의 안전성 향상 방안 : 디스크 스냅링 조립공정 위주로)

  • Cho, Guy-Sun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.21 no.8
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    • pp.342-347
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    • 2020
  • Recently, as the collaborative robot has been introduced into the domestic industrial robot market, it is installed mainly in the manufacturing industry. Collaborative robots are subject to the safety regulations of industrial robots by Article 93 of the Safety Inspection of the Industrial Safety and Health Act. The sites where collaborative robots are to be installed must perform risk assessments for robots-humans, work environments, and work methods and reduce the risks according to ISO 10218-2 and ISO 12100. On the other hand, because it is early in the introduction of collaborative robots, new risks for collaborative robots have not been issued, and risk assessments are unfamiliar and difficult to apply in the workplace. The risk assessment of collaborative robots aims to identify and reduce the risk of a high probability of occurrence by focusing on the abnormal behavior of humans, human errors, equipment defects, and interlock functions. In this study, a risk assessment was applied to a domestic automobile parts production plant, and improvement measures were drawn. This risk assessment is expected to be useful for improving the safety of small businesses by continuously discovering risk assessment examples of collaborative robots.

A Study of Solving Maze Escape Problem through Robots' Cooperation (로봇협동을 통한 미로탈출 문제해결 방안)

  • Hong, Ki-Cheon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.11
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    • pp.4167-4173
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    • 2010
  • ICT education guidelines revised in 2005 reinforce computer science elements such as algorithm, data structure, and programming covering all schools. It means that goal of computer education is improving problem-solving abilities not using of commercial software. So this paper suggests problem-solving method of maze escape through robots' cooperation in an effort of learning these elements. Problems robots should solve are first-search and role-exchange. First-search problem is that first robot searches maze and send informations about maze to the second robot in real time. Role-exchange problem is that first robot searches maze, but loses its function at any point. At this time second robot takes a role of first robot and performs first robot's missions to the end. To solve these two problems, it goes through four steps; problem analysis, algorithm description, flowchart and programming. Additional effects of our suggestion are chance of cooperation among students and use of queue in data structure. Further researches are use of more generalized mazes, application to real field and a talented curriculum.

Design of Engineering Education Using Robot Applications (로봇을 응용한 청소년 공학 설계)

  • Won, Sub;Lee, Dong-Hyuck;Lee, Jun-Ha
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2009.10a
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    • pp.436-437
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    • 2009
  • 본 논문에서는 로봇을 제작하고 응용함으로써 창의력을 키우고 실험과 제작을 통하여 협동심을 기르도록 하는 공학 과정을 설계하였다. 마이크로프로세서 및 무선 전송 장치 등의 차세대 유비쿼터스 개념을 통하여 이해하고 응용 및 활용하는 과정과, 반도체에 응용 제품인 컴퓨터에 대한 이론을 배우고 실습하는 과정으로 이루어져 있다. 청소년들에게 로봇을 통한 대화 공간 마련과 로봇 프로그램을 통해 과학 및 로봇분야의 인재 발굴에 기여하고 로봇에 대한 공감대 확산 및 과학 프로그램의 모델을 제시 하였다.

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Gear Fault Diagnosis Based on Residual Patterns of Current and Vibration Data by Collaborative Robot's Motions Using LSTM (LSTM을 이용한 협동 로봇 동작별 전류 및 진동 데이터 잔차 패턴 기반 기어 결함진단)

  • Baek Ji Hoon;Yoo Dong Yeon;Lee Jung Won
    • KIPS Transactions on Software and Data Engineering
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    • v.12 no.10
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    • pp.445-454
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    • 2023
  • Recently, various fault diagnosis studies are being conducted utilizing data from collaborative robots. Existing studies performing fault diagnosis on collaborative robots use static data collected based on the assumed operation of predefined devices. Therefore, the fault diagnosis model has a limitation of increasing dependency on the learned data patterns. Additionally, there is a limitation in that a diagnosis reflecting the characteristics of collaborative robots operating with multiple joints could not be conducted due to experiments using a single motor. This paper proposes an LSTM diagnostic model that can overcome these two limitations. The proposed method selects representative normal patterns using the correlation analysis of vibration and current data in single-axis and multi-axis work environments, and generates residual patterns through differences from the normal representative patterns. An LSTM model that can perform gear wear diagnosis for each axis is created using the generated residual patterns as inputs. This fault diagnosis model can not only reduce the dependence on the model's learning data patterns through representative patterns for each operation, but also diagnose faults occurring during multi-axis operation. Finally, reflecting both internal and external data characteristics, the fault diagnosis performance was improved, showing a high diagnostic performance of 98.57%.

A Case Study on Instruction Using Robot in Elementary Regular Classes (초등학교 정규교과에서 로봇활용수업 적용 사례 연구)

  • Park, Jung-Ho;Cho, Hye-Kyung
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.8
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    • pp.67-76
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    • 2011
  • This study is to analyze the effects on using robots in elementary regular classes. The robots and PC-linked applications were developed considering the school subjects' academic goals and the learners' responses were carefully examined while applying the robots in the class. The image profile after the robot application shows positive feedbacks in most of the contents and some significant differences were found in contents such as 'theoretical-practical', 'uncooperative-cooperative'(p<.05). Moreover, the analysis on the learners' image drawings shows that more robot images are formed related to the concrete learning environment. The learners have answered in an interview to evaluate their understanding of Robot based instruction that both direct and indirect robot experience induce positive participations and provide authentic learning experience. During the robot based instruction, the learners cooperate with their group members and recognize the cooperation as a positive activity. It proves that the robot based instruction can lead to a possibility of new education paradigm.

The Study of Barista Robots Utilizing Collaborative Robotics and AI Technology (협동로봇과 AI 기술을 활용한 바리스타 로봇 연구)

  • Do Hyeong Kwon;Tae Myeong Ha;Jae Seong Lee;Yun Sang Jeong;Yeong Geon Kim;Hyeon Gak Kim;Seung Jun Song;Dae Gil O;Geonu Lee;Jae Won Jeong;Seungwoon Park;Chul-Hee Lee
    • Journal of Drive and Control
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    • v.21 no.3
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    • pp.36-45
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    • 2024
  • Collaborative robots, designed for direct interaction with humans have limited adaptability to environmental changes. This study addresses this limitation by implementing a barista robot system using AI technology. To overcome limitations of traditional collaborative robots, a model that applies a real-time object detection algorithm to a 6-degree-of-freedom robot arm to recognize and control the position of random cups is proposed. A coffee ordering application is developed, allowing users to place orders through the app, which the robot arm then automatically prepares. The system is connected to ROS via TCP/IP socket communication, performing various tasks through state transitions and gripper control. Experimental results confirmed that the barista robot could autonomously handle processes of ordering, preparing, and serving coffee.

Evaluation of Materials Related to Gender-Preferences for the Application of Cooperative Robot Skin (협동 로봇 스킨에 적용하기 위한 재료의 성별 선호도와 관련된 자료 조사)

  • Son, Minhee;Shin, Dongwon;Lee, Caroline Sunyong
    • Journal of Appropriate Technology
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    • v.7 no.1
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    • pp.2-25
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    • 2021
  • This study evaluated gender preferences regarding the mechanical properties of polymers that are typically used as cooperative robot skin. Gender-based preferences of workers aged 20~30 and polydimethylsiloxane were examined according to the body parts which is most frequently in contact with the robot during operation. The factors influencing preference, i.e., stiffness and stickiness, as measured by strain rate and contact angle, respectively, were analyzed to compare gender-based differences. Female preferred stiffer materials with small strain rates while male preferred softer materials with large strain rates. As a result of evaluating mechanical properties of the materials to relate to gender-based preference, we found that female tended to prefer Dragon-skin with the lowest stickiness, and a low strain rate, during compressive creep tests. In contrast, male tended to prefer Ecoflex with high strain rate regardless of stickiness. Therefore, these results provide basis for material selection when considering cooperative robot skin.