• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.3
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• pp.51-51
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• 1998

It is very important to test linear cycle positioning accuracy of Machining centers as it affect all other machines machined by them in industries. For example, if the linear positioning accuracy of each axes directions is bad, the size of works will be wrong and the change-ability will be bad in the assembly of machine parts. In this paper, measuring systems are organized to measure linear displacements of table or spindle of machine center using laser interferometer, magnescale and tick pulses comming out from computer in order to get data at constant time intervals from the sensors. And each set of data gotten from test is expressed to a plots by computer treatment and the results of linear positioning error motion is estimated to numerics by statistical treatments.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.21 no.3
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• pp.465-472
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• 2012

This paper describes a new robust control algorithm which can be used to enhance the positioning performance of an ultra-precision positioning system. The working table is supported by flexure hinges and moved by a piezoelectric actuator, whose position is measured by an ultra-precise linear encoder. The system dynamics is very complicated because the movement of the table is governed by both the mechanical characteristics and those of the PZT actuator. So that, the dynamics of the stage was modeled roughly in this paper, and the overall system was formularized to solve the small gain problem. A series of experiments was conducted in order to verify the usefulness of the proposed algorithm. From the experimental results, the positioning performance such as the accuracy, the rise time and the hysteresis nonlinearity were greatly improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.641-642
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• 2018

Currently, the performance of positioning technology based on radio wave fingerprint is greatly influenced by the selection of data comparison algorithm. In this case, the accuracy of the indoor positioning can be greatly improved by the data expansion technique necessary for the learning structure. In this paper, we discuss the importance of learning structure that can be applied to actual positioning through classification and extension of learning data to construct learning structure based on Wi-Fi radio fingerprint.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.247-250
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• 2006

Based on the possibility theory and the fuzzy set, the Maximum Possibility Estimation method and its applications in kinematic GPS positioning are presented in this paper. Firstly, the principle and the optimal criterion of the Maximum Possibility Estimation method are explained. Secondly, the kinematic GPS positioning model of single epoch single frequency with baseline length constraint is developed. Then, the authors introduce the artificial immune algorithm and use this algorithm to search the global optimum of the Maximum Possibility Estimation model. The results of some examples show that the method is efficient for kinematic GPS positioning.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.129-132
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• 1996

There is a tendency nowadays to produce increasingly miniaturized electronic equipment which incorporate parts that have to be precisely positioned, like lenses, heads and CCD's in scanners, printers, copiers, VCR's, optical fiber modules, etc. In contrast to the production process of precision parts, which is currently being carried out automatically, the assemblage process is still being performed by specially skilled technicians. The assemblage process comprises normally the following steps: firstly, the parts are roughly positioned and partially fixed, secondly, the parts are manually nudged towards the target position and finally glued, screwed or welded. This paper presents a system that uses six piezo Impact Drive Mechanisms for accurate micro positioning within three degrees of freedom (lateral and longitudinal translation and rotation). The system is designed to positioning a printed circuit board with an accuracy better than 3 .mu.m (for translations), 5 mrad (for rotation).

• ETRI Journal
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• v.38 no.3
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• pp.560-567
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• 2016

To solve the problem of parameter optimization in image sensor-based visible light positioning systems, theoretical limits for both the location and the azimuth angle of the image sensor receiver (ISR) are calculated. In the case of a typical indoor scenario, maximum likelihood estimations for both the location and the azimuth angle of the ISR are first deduced. The Cramer-Rao Lower Bound (CRLB) is then derived, under the condition that the observation values of the image points are affected by white Gaussian noise. For typical parameters of LEDs and image sensors, simulation results show that accurate estimates for both the location and azimuth angle can be achieved, with positioning errors usually on the order of centimeters and azimuth angle errors being less than $1^{\circ}$. The estimation accuracy depends on the focal length of the lens and on the pixel size and frame rate of the ISR, as well as on the number of transmitters used.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.5
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• pp.451-458
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• 2016

Urban railway can be divided into ground and underground sections. In particular, the center of the metropolitan has been built mostly underground stations and tunnels. Underground section is difficult to measure the position because GPS signal is unavailable, so it is necessary to apply the indoor positioning technology. For this purpose, we analyzed the positioning technologies which are based on Wi-Fi and mobile base stations. The positing technology for smart phone which uses mobile base station' information is developed in the underground area of urban railway where the core technique is to implement base station ID into the positing technology by considering hand-off point.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1200-1215
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• 2023

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.12
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• pp.20-25
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• 2000