• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.45-46
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• 2012

• Journal of the Korean Society for Precision Engineering
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• v.26 no.5
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• pp.14-22
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.479-480
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.243-244
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.671-672
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• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.185-186
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• 2010

• Agricultural and Biosystems Engineering
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• v.5 no.1
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• pp.1-4
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• 2004

Community-based precision farming is a new concept of agricultural systems, which leads to organize groups of wise farmers and technology platforms in Japan. The wisdom farmers create a rational farming system to manage hierarchical variability: variability in farmers' community as well as variability of within-field and between-field. The technology platform develops and provides three key-technologies: mapping technology, variable-rate technology, and decision support systems available for rural constraints. Advancement of bio-production robots leads precision farming to the next level, where two technological innovations: how to produce and manage information-oriented fields and information-added products, can be attained.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.166-171
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• 1996

Generally, when we control the robot, we should calculate exactly Inverse Kinematics. However, Inverse Kinematics calculation is complex and it takes much time for the manipulator to control in real-time. Therefore, the calculation of Inverse Kinematics can result in significant control delay in real time. In this paper, we will present that Inverse Kinematics can be calculated through Fuzzy Logic Mapping, Based on an exact solution through fuzzy reasoning instead of Inverse Kinematics calculation Also, the result provides sufficient precision and transient tracking error can be controlled based on a fuzzy adaptive scheme proposed in this paper. Based on the Denavit-Hartenberg parameters specification, after the Jacobian matrix of arbitrary manipulator is calculated, we will construct Fuzzy Inverse Kinematics Mapping(FIKM) using fuzzy logic and represent a good control efficiency through simulation of 2-DOF manipulator.

• International Journal of Advanced Culture Technology
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• v.9 no.4
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• pp.302-306
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• 2021

Indoor localization is one of the basic elements of Location-Based Service, such as indoor navigation, location-based precision marketing, spatial recognition of robotics, augmented reality, and mixed reality. We propose a Voxel Labeling-based visual positioning system using object simultaneous localization and mapping (SLAM). Our method is a method of determining a location through single image 3D cuboid object detection and object SLAM for indoor navigation, then mapping to create an indoor map, addressing it with voxels, and matching with a defined space. First, high-quality cuboids are created from sampling 2D bounding boxes and vanishing points for single image object detection. And after jointly optimizing the poses of cameras, objects, and points, it is a Visual Positioning System (VPS) through matching with the pose information of the object in the voxel database. Our method provided the spatial information needed to the user with improved location accuracy and direction estimation.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.252-256
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• 1998

Accurate mapping of satellite images is one of the most important Parts in many remote sensing applications. Since the position and the attitude of a satellite during image acquisition cannot be determined accurately enough, it is normal to have several hundred meters' ground-mapping errors in the systematically corrected images. The users which require a pixel-level or a sub-pixel level mapping accuracy for high-resolution satellite images must use a number of Ground Control Points (GCPs). In this paper, the performance of two geometric correction algorithms is tested and compared. One is the polynomial warping algorithm which is simple and popular enough to be implemented in most of the commercial satellite image processing software. The other is full camera modelling algorithm using Physical orbit-sensor-Earth geometry which is used in satellite image data receiving, pre-processing and distribution stations. Several criteria were considered for the performance analysis : ultimate correction accuracy, GCP representatibility, number of GCPs required, convergence speed, sensitiveness to inaccurate GCPs, usefulness of the correction results. This paper focuses on the usefulness of the precision correction algorithm for regular image pre-processing operations. This means that not only final correction accuracy but also the number of GCPs and their spatial distribution required for an image correction are important factors. Both correction algorithms were implemented and will be used for the precision correction of KITSAT-3 images.