• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.10a
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• pp.355-360
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• 2002

To calibrate a non-redundantly actuated parallel mechanism, one can find actual kinematic parameters by means of geometrical constraint of the mechanism's kinematic structure and measurement values. However, the calibration algorithm for a non-redundant case does not apply fur a redundantly actuated parallel mechanism, because the angle error of the actuating joint varies with position and the geometrical constraint fails to be consistent. Such change of joint angle error comes from constraint torque variation with each kinematic pose (meaning position and orientation). To calibrate a redundant parallel mechanism, one therefore has to consider constraint torque equilibrium and the relationship of constraint torque to torsional deflection, in addition to geometric constraint. In this paper, we develop the calibration algorithm fir a redundantly actuated parallel mechanism using these three relationships, and formulate cost functions for an optimization algorithm. As a case study, we executed the calibration of a 2-DOF parallel mechanism using the developed algorithm. Coordinate values of tool plate were measured using a laser ball bar and the actual kinematic parameters were identified with a new cost function of the optimization algorithm. Experimental results showed that the accuracy of the tool plate improved by 82% after kinematic calibration in a redundant actuation case.

• Journal of Biosystems Engineering
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• v.27 no.6
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• pp.547-556
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• 2002

Upright positioning of garlic cloves in mechanical planting has been considered as an essential process because pose of garlic affects not only initial budding and rooting of garlics but quality and yield. Due to the geometrical uniqueness and irregularity of garlic cloves in shape, manual planting operation has been conducted. The overall objective of this research was to determine design factors for designing a garlic clove planter The results are summarized as follows : 1. A vibrating-type clove-metering device was designed and tested. Effects of tilted angle of metering plate and magnitude of vibration on metering performance were investigated. The successful planting rates of the metering device were 96.7% for Hanji varieties. 2. Clove upright-positioning device, posture inducer was designed and tested. When the clearance between the hoppers was set at 4mm, the rates of upright positioning of the device were 92.2% for with Hanji varieties. 3. Optimum metering performance was observed at the plate tilted angle of 80。 with the posture type positioning device.

• Geomechanics and Engineering
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• v.18 no.1
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• pp.21-27
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• 2019

Rockburst disasters pose serious threat to mining safety and underground excavation, especially in China, resulting in massive life-wealth loss and even compulsive closed-down of some coal mines. To investigate the mechanism of rockbursts that occur under a state of static forces, a stress model with sidewall as prototype was developed and verified by a group of laboratory experiments and numerical simulations. In this model, roadway sidewall was simplified as a square plate with axial compression and end (horizontal) restraints. The stress field was solved via the Airy stress function. To track the "closeness degree" of the stress state approaching the yield limit, an unbalanced force F was defined based on the Mohr-Coulomb yield criterion. The distribution of the unbalanced force in the plane model indicated that only the friction angle above a critical value could cause the first failure on the coal in the deeper of the sidewall, inducing the occurrence of rockbursts. The laboratory tests reproduced the rockburst process, which was similar to the prediction from the theoretical model, numerical simulation and some disaster scenes.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.762-766
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• 2003

In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.508-518
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• 2016

In this paper, we propose a method combining an accelerometer with a cross structured light system to estimate the golf green slope. The cross-line laser provides two laser planes whose functions are computed with respect to the camera coordinate frame using a least square optimization. By capturing the projections of the cross-line laser on the golf slope in a static pose using a camera, two 3D curves’ functions are approximated as high order polynomials corresponding to the camera coordinate frame. Curves’ functions are then expressed in the world coordinate frame utilizing a rotation matrix that is estimated based on the accelerometer’s output. The curves provide some important information of the green such as the height and the slope’s angle. The curves estimation accuracy is verified via some experiments which use OptiTrack camera system as a ground-truth reference.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.611-615
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• 2010

In this paper, we propose a method that exaggerate a character motion using quadratic deformation. While the previous methods tend to exaggerate a rotational motion of an individual joint angle, our method attempt to model the poses of a whole body at each frame and exaggerate those, so that the whole-pose action of the character can be exaggerated. Our method can be computed in real-time, and prevents a joint motion that rotates unexpected direction.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.265-272
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• 2009

IVarious driving mechanisms to adapt to uneven environment have been developed for many urban search and rescue (USAR) missions. A tracked mechanism has been widely used to maintain the stability of robot's pose and to produce large traction force on uneven terrain in this research area. However, it has a drawback of low energy efficiency due to friction force when rotating. Moreover, single tracked mechanism can be in trouble when the body gets caught with high projections, so the track doesn't contact on the ground. A transformable tracked mechanism is proposed to solve these problems. The mechanism is designed with several articulations surrounded by tracks, used to generate an attack angle when the robot comes near obstacles. The stair climbing ability of proposed robot was analyzed since stairs are one of the most difficult obstacles in USAR mission. Stair climbing process is divided into four separate static analysis phases. Design parameters are optimized according to geometric limitations from the static analysis. The proposed mechanism was produced from optimized design parameters, and demonstrated in artificially constructed uneven environment and the actual stairway.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.8
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• pp.678-687
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• 2005

This paper describes a relative localization algorithm using odometry data and consecutive local maps. The purpose of this paper is the odometry error correction using the area matching of two consecutive local maps. The local map is built up using a sensor module with dual laser beams and USB camera. The range data form the sensor module is measured using the structured lighting technique (active stereo method). The advantage in using the sensor module is to be able to get a local map at once within the camera view angle. With this advantage, we propose the AVS (Aligned View Sector) matching algorithm for. correction of the pose error (translational and rotational error). In order to evaluate the proposed algorithm, experiments are performed in real environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.225-229
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• 2020

Recently, convolutional neural network (CNN) have been showed outstanding performance in the field of image recognition, image processing and computer vision, etc. In this paper, we propose a CNN-based image rotation correction algorithm as a solution to image rotation problem, which is one of the factors that reduce the recognition rate in image recognition system using CNN. In this paper, we trained our deep learning model with Leeds Sports Pose dataset to extract the information of the rotated angle, which is randomly set in specific range. The trained model is evaluated with mean absolute error (MAE) value over 100 test data images, and it is obtained 4.5951.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.9
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• pp.901-908
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• 2013

The introduction of industrial intelligent robot using vision sensor has been interested in automated factory. 2D and 3D vision sensors have used to recognize object and to estimate object pose, which is for packaging parts onto a complete whole. But it is not trivial task due to illumination and various types of objects. Object image has distorted due to illumination that has caused low reliability in recognition. In this paper, recognition method of complex shape object has been proposed. An accurate object region has detected from combined binary image, which has achieved using DoG filter and local adaptive binarization. The object has recognized using neural network, which is trained with sub-divided object class according to object type and rotation angle. Predefined shape model of object and maximal slope have used to estimate the pose of object. The performance has evaluated on ETRI database and recognition rate of 96% has obtained.