• Title/Summary/Keyword: SCARA robot

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Optimal Motion Control of 3-axis SCARA Robot Using a Finite Jerk and Gain Tuning Based on $LabVIEW^{(R)}$ ($LabVIEW^{(R)}$ 기반 3축 스카라 로봇의 유한 저크 및 게인 동조를 이용한 최적 모션 제어)

  • Kim, J.H.;Chung, W.J.;Kim, H.G.;Lee, G.S.
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.17 no.3
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    • pp.40-46
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    • 2008
  • This paper presents the optimal motion control for 3-axis SCARA robot by using $LabVIEW^{(R)}$. Specifically, for optimal motion control of 3-axis SCARA robot, we study velocity profile based on finite jerk(the first derivative of acceleration) and optimal gain tunig based on frequency response method by using $LabVIEW^{(R)}$. The velocity optimization with finite jerk aims at generating the smooth velocity profile of robot. Velocity profile based on finite jerk is acquired and applied to 3-axis SCARA robot by using $LabVIEW^{(R)}$. DSA(Dynamic Signal Analyzer) for frequency response method is programed by using $LabVIEW^{(R)}$. We obtain the bode plot of transfer function about 3-axis SCARA robot by using DSA, and perform the gain tuning considering dynamic characteristic based on the bode plot. These experiments have shown that the proposed motion control can reduce vibration displacement and response error rate each 33.7% and 51.7% of 3-axis SCARA robot.

The design and development of high performance SCARA ROBOT (고성능 SCARA ROBOT 개발)

  • 이영우;안태영;권구빈;손신국;민정동
    • 제어로봇시스템학회:학술대회논문집
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    • 1986.10a
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    • pp.1-4
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    • 1986
  • This paepr handles the illustrations about various characteristics of SCARA type ROBOT developed by Samsung Precision Ind. and includes system structure, controller, robot language and future developing plan. This robot has high-precision, high-speed and flexible movement performances. So it is very useful for small parts assembly systems.

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Integrated robot control system for off-line teaching (오프라인 교시작업을 위한 통합 로봇제어시스템의 구현)

  • 안철기;이민철;이장명;김성권
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.503-506
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    • 1996
  • An integrated Robot control system for SCARA robot is developed. The system consists of an off-line programming(OLP), software and a robot controller using four digital signal processor(TMS32OC50). The OLP has functions of teaching task, dynamic simulator, three dimensional animation, and trajectory planning. To develop robust dynamic control algorithm, a new sliding mode control algorithm for the robot is proposed. The trajectory tracking performance of these algorithm is evaluated by implementing to SCARA robot(SM5 type) using DSP controller which has conventional PI-FF control algorithm. To make SCARA robot operate according to off-line teaching, an interface between OLP and robot controller in the integrated system is designed. To demonstrate performance of the integrated system, the proposed control algorithm is applied to the system.

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Development of a 3D graphic simulation tool for SCARA robot (스카라 로봇의 3차원 그래픽 시뮬레이션 툴 개발)

  • 이대영;최재원;이민철
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.724-727
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    • 1997
  • In this paper, we developed a Windows 95 version Off-Line Programming System which can simulate a Robot model in 3D Graphic space. 4 axes SCARA Robot (especially FARA SM5)was adopted as an objective model. Forward kinematics, inverse kinematics and robot dynamics modeling were included in the developed program. The interface between users and the OLP system in the Windows 95's GUI environment was also studied. The developing language is Microsoft Visual C++. Graphic libraries, OpenGL, by Silicon Graphics, Inc. were utilized for 3D Graphics.

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SCARA robot calibration on off-line programming (오프라인 프로그래밍에서 스카라 로봇의 보정)

  • Jung, Sung-Woo;Son, Kwon;Lee, Min-Chul;Choi, Jae-Won
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1832-1835
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    • 1997
  • Off-line programming systems are widely spread in assembly lines of minute electronic products to huge offshore structures. Any OLP system has to be calibrated before the on-line robot tasks are performed because there are inherent differences between the CAD model on OLP and the real robot workspace. This paper uses simple geometric expressions to propose a calibration method applicable to an OLP for SCARA robots. A positioning task on the two-dimensional horizontal surface was used in the error analysis of a SCARA robot and the anaysis shows that the inaccuracy results from the two error sources non-zero offset angles of two rotational joints at the zero return and differences in link lengths. Pen marks on a sheet of plotting paper are used to determine the accurate data on the joint centers and link dimensions. The calculated offset angles and link lengths are fed back to the OLP for the calibration of the CAD model of the robot and task environments.

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A Compensation Control Method Using Neural Network for Mechanical Deflection Error in SCARA Robot with Random Payload

  • Lee, Jong Shin
    • Journal of the Korean Society of Mechanical Technology
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    • v.13 no.3
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    • pp.7-16
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    • 2011
  • This study proposes the compensation method for the mechanical deflection error of a SCARA robot. While most studies on the related subject have dealt with the development of a control algorithm for improvement of robot accuracy, this study presents the control method reflecting the mechanical deflection error which is predicted in advance. The deflection at the end of the gripper of SCARA robot is caused by the self-weights and payloads of Arm 1, Arm 2 and quill. If the deflection is constant even though robot's posture and payload vary, there may not be a big problem on robot accuracy because repetitive accuracy, that is relative accuracy, is more important than absolute accuracy in robot. The deflection in the end of the gripper varies as robot's posture and payload change. That's why the moments $M_x$, $M_y$ and $M_z$ working on every joint of a robot vary with robot's posture and payload size. This study suggests the compensation method which predicts the deflection in advance with the variations in robot's posture and payload using neural network. To do this, I chose the posture of robot and the payloads at random, found the deflections by the FEM analysis, and then on the basis of this data, made compensation possible by predicting deflections in advance successively with the variations in robot's posture and payload through neural network learning.

Recursive Torque Control of Robot Manipulators (로봇 매니퓰레이터의 반복 토크 제어)

  • 신대왕;김종식;박전수
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.05a
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    • pp.570-573
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    • 2000
  • A control law for a SCARA robot manipulator is designed using recursive torque methods. This scheme uses previous torques and error dynamics to generate torque controls at the present time and adopts relatively simple numerical and control algorithms that can be easily realizable. In order to evaluate the performance and robustness of the suggested control system, the 2-link SCARA robot manipulator is practically implemented using a dSPACE interface. It is found that the recursive controller has a good tracking performance in spite of the presence of payload disturbances.

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A Study On The Trajectory Control of A SCARA Robot Using Sliding Mode (슬라이딩모드를 이용한 SCARA 로보트의 궤적제어에 관한 연구)

  • 이민철;진상영;이만형
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.19 no.1
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    • pp.99-110
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    • 1995
  • An industrial robot needs a simple and robust control algorithm obtaining high precision control performance in spite of disturbance and parameter's change. In this paper, for solving this problem, a new sliding mode control algorithm is proposed and applied to the trajectory control of a SCARA type robot. The proposed algorithm has diminished the chattering occurring in sliding mode by setting a dead band along the switching line on the phase plane. It shows that we can easily obtain a simple switching control input satisfying sliding mode in spite of regarding nonlinear terms of a manipulator and servo system as disturbance. A guideline for selection of dead-band width is determined by optimal value of cost function presenting magnitudes of chattering and error. By this algorithm, we can expect the high performance of the trajectory tracking of an industrial robot which needs a robust and simple algorithm.