• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.2062-2064
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• 2015

In this paper, we propose indoor positioning algorithm performed at the image sensor equipped in mobile station, which receives the light signal from LED panels. To evaluate the performance of positioning algorithm, we consider the ambient noise existing indoor environment, and it is found that the proposed algorithm estimates the position of mobile station with high accuracy regardless of existence of ambient noise.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.13 no.6
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• pp.15-22
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• 2014

With a conventional positioning apparatus, it is very difficult simultaneously to achieve desired driving ranges and precision levels at the sub-micrometer level. Generally, a lead screw and friction drive have been used as servo control systems. These have large driving ranges, and high-speed positioning is feasible. In this study, we present a global servo system controlled by a laser interferometer acting as a displacement measurement sensor for achieving positioning accuracy at the sub-micrometer level.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.251-256
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• 2006

In the work package 'Integrated Positioning' of the research project NAVIO (Pedestrian Navigation Systems in Combined Indoor/Outdoor Environements) we are dealing with the navigation and guidance of visitors of our University. Thereby start points are public transport stops in the surroundings of the Vienna University of Technology and the user of the system should be guided to certain office rooms or persons. For the position determination of the user different location sensors are employed, i.e., for outdoor positioning GPS and dead reckoning sensors such as a digital compass and gyro for heading determination and accelerometers for the determination of the travelled distance as well as a barometric pressure sensor for altitude determination and for indoor areas location determination using WiFi fingerprinting. All sensors and positioning methods are combined and integrated using a Kalman filter approach. Then an optimal estimate of the current location of the user is obtained using the filter. To perform an adequate weighting of the sensors in the stochastic filter model, the sensor characteristics and their performance was investigated in several tests. The tests were performed in different environments either with free satellite visibility or in urban canyons as well as inside of buildings. The tests have shown that it is possible to determine the user's location continuously with the required precision and that the selected sensors provide a good performance and high reliability. Selected tests results and our approach will be presented in the paper.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.7
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• pp.107-116
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• 2014

This paper presents camera-based road surface marking detection methods suited to sensor fusion-based positioning system that consists of low-cost GPS (Global Positioning System), INS (Inertial Navigation System), EDM (Extended Digital Map), and vision system. The proposed vision system consists of two parts: lane marking detection and RSM (Road Surface Marking) detection. The lane marking detection provides ROIs (Region of Interest) that are highly likely to contain RSM. The RSM detection generates candidates in the regions and classifies their types. The proposed system focuses on detecting RSM without false detections and performing real time operation. In order to ensure real time operation, the gating varies for lane marking detection and changes detection methods according to the FSM (Finite State Machine) about the driving situation. Also, a single template matching is used to extract features for both lane marking detection and RSM detection, and it is efficiently implemented by horizontal integral image. Further, multiple step verification is performed to minimize false detections.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2099-2106
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• 2006

In this paper, we addressed the node positioning method for minimizing the sensing energy consumption in wireless sensor networks with adjustable sensing ranges. It is necessary for minimizing the sensing energy consumption to minimize the overlapped sensing area by neighboring nodes. To find a optimal node position, we derived a optimal equations by using the overlapped areas, each node's radiuses and expended angles of opposite neighboring nodes. Based on it, we devised a new node positioning method, called as ASRC(Adjustable Sensing Ranges Control). Unlike existing condition based model, our proposed method was derived from mathematical formula, and we confirmed its validity of sensing energy consumption through simulations.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.289-295
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• 2021

Recently, owing to the development of autonomous vehicles, research on precisely determining the position of a moving object has been actively conducted. Previous research mainly used the fusion of GNSS/IMU (Global Positioning System / Inertial Navigation System) and sensors attached to the vehicle through a Kalman filter. However, in recent years, new technologies have been used to determine the location of a moving object owing to the improvement in computing power and the advent of deep learning. Various techniques using RNN (Recurrent Neural Network), LSTM (Long Short-Term Memory), and NARX (Nonlinear Auto-Regressive eXogenous model) exist for such learning-based positioning methods. The purpose of this study is to compare the precision of existing filter-based sensor fusion technology and the NARX-based method in case of GNSS signal blockages using simulation data. When the filter-based sensor integration technology was used, an average horizontal position error of 112.8 m occurred during 60 seconds of GNSS signal outages. The same experiment was performed 100 times using the NARX. Among them, an improvement in precision was confirmed in approximately 20% of the experimental results. The horizontal position accuracy was 22.65 m, which was confirmed to be better than that of the filter-based fusion technique.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.2
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• pp.28-35
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• 2009

Positioning technology which a part technology of Mobile Robot is an essential technology to locate the position of Robot and navigate to wanted position. The Robot that based on wheel drive uses Odometry position. technology. But when using Odometry positioning technology, it's hard to find out constant error value because a slip phenomenon occurs as the Robot runs. In this paper, we present the way to minimize positioning error by using Odometry and Inertial sensor. Also, the way to reduce error with Inertial sensor on SLAM using image will be shown, too.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.1
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• pp.9-15
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• 2005

Most of location systems use RF signal. Because multipath is too severe at indoor environment, RF signal are usually used in outdoor positioning such as GPS. To overcome the difficulty at indoor positioning, m positioning is recently developed and is being vigorously studied. Some standardizations on UWB are in progress at IEEE 802.15 committee. In developing UWB positioning system, we should consider the synchronization of sensor network, positioning algorithm, sensor allocation, and so on. This paper presents a comparison of TDOA positioning algorithms that are widely used in location systems. Two algorithms are compared; one is derived by linearization, and the other is by analytic solution(CH algorithm). Simulation results show that the CH algorithm is superior to the linearized least square at indoor environment in that CH algorithm shows consistent positioning performance regardless of the visibility and geometry of basestations.

• Journal of Magnetics
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• v.22 no.1
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• pp.150-154
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• 2017

A novel high precision spatial positioning method utilizing the electromagnetic momentum, i.e., Electromagnetic Momentum Positioning (EMP), is proposed in this paper. By measuring the momentum of the electromagnetic field around the small current loop, the relative position between the sensor and the current loop is calculated. This method is particularly suitable for the application of close-range and high-precision positioning, e.g., data gloves and medical devices in personal healthcare, etc. The simulation results show that EMP method can give a high accuracy with the positioning error less than 1 mm, which is better than the traditional magnetic positioning devices with the error greater than 1 cm. This method lays the foundation for the application of data gloves to meet the accurate positioning requirement, such as the high precision interaction in Virtual Reality (VR), Augmented Reality (AR) and personal wearable devices network.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.2 s.233
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• pp.311-317
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• 2005

NC controller parameters are fixed when the controller is combined with a machine. However, the characteristics of controller could be changed as it has being used by the machine or other environmental conditions. Ultimately, it results in tool positioning accuracy changing. The loading torque in servo motor also influences on the positioning accuracy. This study focus on a measuring and analysing method for verifying the angular positioning accuracy of NC servo motor. We used a high resolution A/D converter for acquiring analogue signal of rotary encoder in servo motor. Generating tool path by the combination of axial movements (X,Y,Z) is compared with the encoder signals with the servo motor torque. The current variation signal is also read from the servo motor power using a hall sensor and converted to the motor torque. The method of analysing proposed in this study will be used for determining the gains (tuning) of parameter in NC controller, when the controller is set up at a machine initially or the controller condition is changed during the work.