• 제목/요약/키워드: Collaborative Robot

검색결과 49건 처리시간 0.027초

협동로봇 활용을 위한 작업안전 시나리오 설계 방법론 연구 (A Design Methodology of Task Safety Scenario for the Application of Collaborative Robots)

  • 김율희;김진오
    • 로봇학회논문지
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    • 제15권3호
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    • pp.256-268
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    • 2020
  • This study is about a design method for deriving task safety scenarios for the application of collaborative robots. A five-step process for deriving task safety scenarios for collaborative robots has been proposed, which focuses on the type of collaboration between human and collaborative robot. The three types of collaboration were classified according to the collaboration workspace and the worktime of human and collaborative robot. Based on these three types of collaboration, task safety scenarios include scenarios that predict risk from unintended use during work. Collaboration with collaborative robot is a human-centered process because human actions can create dangerous situations. Besides, we improved the understanding of this design methodology by presenting examples of the application of task safety scenarios according to the process for each type of collaboration.

Development of a Dual-arm Collaborative Robot System for Chemical Drum Assembly

  • Gi-Seong Kim;Sung-Hun Jeong;Shi-Baek Park;Han-Sung Kim
    • 한국산업융합학회 논문집
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    • 제26권4_1호
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    • pp.545-551
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    • 2023
  • In this paper, a robot automation methodology for chemical drum assembly in semiconductor industries are presented. Robot automation is essential to resolve safety issues in which operators are directly or indirectly exposed to chemicals or fumes in assembling dispense heads on chemical drums. However, the chemical drum assembling process involves complex and difficult tasks, such as mating male/female keycodes and fastening screws with large-diameter, which may be very difficult to be performed by a single-arm robot with a commercial rigid F/T sensor. In order to solve the problems, a method for assembling a chemical drum using dual-arm collaborative robot system, compliance F/T sensor, robot vision and gripper is presented.

센서리스 협동로봇의 직관적인 교시를 위한 직교공간 직접교시 (Cartesian Space Direct Teaching for Intuitive Teaching of a Sensorless Collaborative Robot)

  • 안국현;송재복
    • 로봇학회논문지
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    • 제14권4호
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    • pp.311-317
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    • 2019
  • Direct teaching is an essential function for collaborative robots for easy use by non-experts. For most robots, direct teaching is implemented only in joint space because the realization of Cartesian space direct teaching, in which the orientation of the end-effector is fixed while teaching, requires a measurement of the end-effector force. Thus, it is limited to the robots that are equipped with an expensive force/torque sensor. This study presents a Cartesian space direct teaching method for torque-controlled collaborative robots without either a force/torque sensor or joint torque sensors. The force exerted to the end-effector is obtained from the external torque which is estimated by the disturbance observer-based approach with the friction model. The friction model and the estimated end-effector force were experimentally verified using the robot equipped with joint torque sensors in order to compare the proposed sensorless approach with the method using torque sensors.

센서네트워크 기반의 수중, 수상 및 공중 로봇의 협력제어 기법 (Collaborative Control Method of Underwater, Surface and Aerial Robots Based on Sensor Network)

  • 만동우;기현승;김현식
    • 전기학회논문지
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    • 제65권1호
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    • pp.135-141
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    • 2016
  • Recently, the needs for the development and application of marine robots are increasing as marine accidents occur frequently. However, it is very difficult to acquire the information by utilizing marine robots in the marine environment. Therefore, the needs for the researches of sensor networks which are composed of underwater, surface and aerial robots are increasing in order to acquire the information effectively as the information from heterogeneous robots has less limitation in terms of coverage and connectivity. Although various researches of the sensor network which is based on marine robots have been executed, all of the underwater, surface and aerial robots have not yet been considered in the sensor network. To solve this problem, a collaborative control method based on the acoustic information and image by the sonars of the underwater robot, the acoustic information by the sonar of the surface robot and the optical image by the camera of the static-floating aerial robot is proposed. To verify the performance of the proposed method, the collaborative control of a MUR(Micro Underwater Robot) with an OAS(Obstacle Avoidance Sonar) and a SSS(Side Scan Sonar), a MSR(Micro Surface Robot) with an OAS and a BMAR(Balloon-based Micro Aerial Robot) with a camera are executed. The test results show the possibility of real applications and the need for additional studies.

Offset Wrist를 갖는 6자유도 협동로봇의 역기구학 해석 (Inverse Kinematic Analysis of a 6-DOF Collaborative Robot with Offset Wrist)

  • 김기성;김한성
    • 한국산업융합학회 논문집
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    • 제24권6_2호
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    • pp.953-959
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    • 2021
  • In this paper, the numerical inverse kinematics analysis is presented for a collaborative robot with an offset wrist. Robot manipulators with offset wrist are widely used in industrial applications, due to many advantages over those with wrist center and those with three parallel axes such as simple mechanical design, light weight, and so on. There may not exist a closed-form solution for a robot manipulator with offset wrist. A simple numerical method is applied to solve the inverse kinematics with offset wrist. Singularity is analyzed using Jacobian matrix and the numerical inverse kinematics algorithm is implemented on the real-time controller.

협동로봇의 건전성 관리를 위한 머신러닝 알고리즘의 비교 분석 (Comparative Analysis of Machine Learning Algorithms for Healthy Management of Collaborative Robots)

  • 김재은;장길상;임국화
    • 대한안전경영과학회지
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    • 제23권4호
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    • pp.93-104
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    • 2021
  • In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

기계식 중력보상 기반의 중량물 취급용 5자유도 로봇 머니퓰레이터의 개발 (Development of a 5 DOF Manipulator for Weight Handling based on Counterbalance Mechanism)

  • 송승우;송재복
    • 로봇학회논문지
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    • 제11권4호
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    • pp.242-247
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    • 2016
  • A robot manipulator handling a heavy weight requires high-capacity motors and speed reducers, which increases the cost of a robot and the risk of injury when a human worker is in collaboration with a robot. To cope with this problem, we propose a collaborative manipulator equipped with a counterbalance mechanism which compensates mechanically for a gravitational torque due to the robot mass. The prototype of the manipulator was designed on the basis of a four-bar linkage structure which contains active and passive pitch joints. Experimental performance evaluation shows that the proposed robot works effectively as a collaborative robot.

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

  • 조규선
    • 한국산학기술학회논문지
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    • 제21권8호
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    • pp.342-347
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    • 2020
  • 최근 국내에도 협동로봇이 산업용로봇 시장에 진입하면서 제조업을 중심으로 설치되고 있으나 산업안전보건법 제93조 안전검사에 따른 산업용로봇의 안전규제를 그대로 적용받고 있어 안전보호 대책인 펜스와 매트를 설치하여야 하는 상황이었다. 협동로봇을 설치할 사업장은 ISO 10218-2과 ISO 12100에 따라 로봇-인간, 작업환경, 작업방식에 대한 위험성평가를 실시하고 위험도를 낮추어야 한다. 그러나, 국내 산업현장에 협동로봇의 도입 초기인 관계로 협동로봇에 대한 새로운 위험성도 알려지지 않고 있으며 위험성평가도 활성화되지 않아 사업장에서는 위험성평가가 낯설고 어렵게 받아들여지고 있다. 협동로봇의 위험성평가는 로봇과 인간이 공존하는 개념에서 출발해서 작업자의 이상행동, 인적 오류, 설비결함, 인터록 기능에 초점을 맞춰 실제 일어날 가능성이 높은 위험을 발굴하고 개선하는데 그 목적이 있으며 본 연구는 국내 자동차부품 제조업에 적용된 사례를 통해 입증하고자 하였다. 향후에도 협동로봇의 위험성평가를 다양한 공정 및 작업에 대해 사례 발굴함으로써 중소기업의 안전성 향상에 유용할 것으로 기대한다.