• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.230-233
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• 1993

This paper described a relationship between motion speed and working accuracy of industrial articulated robot arms. Working accuracy of the robot arm deteriorates at high speed operation caused by a nonlinear transformation of the kinematics and the time delay of the robot arm dynamic. The deterioration of the following trajectory was expressed as a linear function of the squares of the robot arm motion speed, depending upon a posture of the robot arm and division interval of the objective trajectory.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.4
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• pp.111-116
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• 2007

This study is aimed to analyze the accuracy of depth information of reservoir using the robot-ship equipped with GPS and echosounder. The accuracy of depth measurements by sounding data was analyzed according to change of robot-ship's speed in the water. The field experiment results showed that as robot-ship's speeds were slow, accuracy of sounding data were increased. Until Robot-ship's speed was up to 5 km/hr, the accuracy of sounding data were included reliable section of normal distribution.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.3
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• pp.1-7
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• 2010

The aim of this research is to evaluate movement and path characteristics of developed heavy duty handling robot using laser tracker(API T3) according to the ISO 9283 robot performance evaluation criteria. As carry out 3D modeling and simulation using CATIA, a test cube was set up to select moving and measuring range of robot. Performance test for pose and distance accuracy, path and path velocity accuracy under payload zero and 440kgf was accomplished. The resulted output data show the reliability of the developed robot.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.4
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• pp.406-410
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• 2008

This paper presents a new robot calibration algorithm with joint stiffness parameters for the enhanced positioning accuracy of industrial robot manipulators. This work is towards on-going development of an industrial robot calibration software which is able to identify both the kinematic and non-kinematic robot parameters. In this paper, the conventional kinematic calibration and its important considerations are briefly described first. Then, a new robot calibration algorithm which simultaneously identifies both the kinematic and joint stiffness parameters is presented and explained through a computer simulation with a 2 DOF manipulator. Finally, the developed algorithm is implemented to Hyundai HX165 robot and its resulting improvement of the positioning accuracy is addressed.

• Journal of Information Processing Systems
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• v.19 no.3
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• pp.370-376
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• 2023

Aiming at the problems of low image enhancement accuracy, long enhancement time and poor image quality in the traditional robot sequence motion image enhancement methods, an adaptive enhancement method for robot sequence motion image is proposed. The feature representation of the image was obtained by Karhunen-Loeve (K-L) transformation, and the nonlinear relationship between the robot joint angle and the image feature was established. The trajectory planning was carried out in the robot joint space to generate the robot sequence motion image, and an adaptive homomorphic filter was constructed to process the noise of the robot sequence motion image. According to the noise processing results, the brightness of robot sequence motion image was enhanced by using the multi-scale Retinex algorithm. The simulation results showed that the proposed method had higher accuracy and consumed shorter time for enhancement of robot sequence motion images. The simulation results showed that the image enhancement accuracy of the proposed method could reach 100%. The proposed method has important research significance and economic value in intelligent monitoring, automatic driving, and military fields.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.21-26
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• 1988

The application of robot to industry is increasing and as a result the study on robot is widely being carried out. In this study, to improve the accuracy of robot motion the method which calibrates initially assumed link parameters is considered. This method calibrates 4N link parameters for N D.O.F. robot with rigid links.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.7
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• pp.728-733
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• 2009

This paper presents the compensation of mechanical deflection error in SCARA robot. End of robot gripper is deflected by weight of arm and pay-load. If end of robot gripper is deflected constantly regardless of robot configuration, it is not necessary to consider above mechanical deflection error. However, deflection in end of gripper varies because that moment of each axis varies when robot moves, it affects the relative accuracy. I propose the compensation method of deflection error using neural network. FEM analysis to obtain the deflection of gripper end was carried out on various joint angle, the results is used in neural network teaming. The result by simulation showed that maximum relative accuracy reduced maximum 9.48% on a given working area.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.1
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• pp.41-46
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• 2011

In this paper, we experimentally investigate factors that decrease in noise of a industrial take-out robot at driving state. For this, we analyse change in the noise of the take-out robot with gear machining accuracy and clearance. In order to calculate the noise related to gear machining accuracy that is based upon the Japanese Industrial Standard(JIS), we equally increase motor speed from 0 rpm to 1250 rpm. In addition, to investigate influence of clearance on noise, we evenly change clearance from 0.5 mm to 1.2 mm. These experiments show that clearance is more effective factor than gear machining accuracy to reduce the noise of the take-out robot.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1267-1271
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• 2014

There have been many autonomous robot calibration methods which form closed loop structures through the various attached sensors and mechanical fixtures. Single point calibration among them has been used for on-site calibration due to its convenience of implementation. The robot can reach a single point with infinitely many configurations so that single point calibration algorithm can be set up and easily implemented relative to the other methods. However, it is not still easy to drive the robots' sharp edge to its corresponding edge of the fixture. This is error-prone process. In this paper, we propose a 3 dimensional small displacement measuring sensor and a robot calibration algorithm based on this sensor. This method relieves the difficulty of matching two edges in the single point calibration and improves the resulting robot accuracy. Simulated study is carried out on a Hyundai HA06 robot to show the effectiveness of the proposed method over the single point calibration. And also, the resulting robot accuracy is compared with that from 3D laser tracker based calibration to show the dependency of robot accuracy on range of the workspace where the measurement data are collected.