• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.647-654
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• 2016

Indoor localization based on visible-light communication using the received signal strength intensity (RSSI) has been widely studied because of its high accuracy compared with other wireless localization methods. However, because the RSSI can vary according to the inclination and azimuth of the receiver, a large error can occur, even at the same position. In this paper, we propose a visible-light communication-based 3-D indoor positioning algorithm using the Gauss-Newton technique in order to reduce the errors caused by the change in the inclination of the receiver. The proposed system reduces the amount of computations by selecting the initial position of the receiver through the linear least-squares method (LSM), which is applied to the RSSIs, and improves the position accuracy by applying the Gauss-Newton technique to the 3-D nonlinear model that contains the RSSIs acquired by the changes in the azimuth and inclination of the receiver. In order to verify the validity of the proposed algorithm in an indoor space with dimensions of $6{\times}6{\times}3m$ where 16 LED lights are installed, we compare and analyze the errors of the conventional linear LSM-based trilateration technique and the proposed algorithm according to the changes in the inclination and azimuth of the receiver. The experimental results show that the location accuracy of the proposed algorithm is improved by 82.5% compared to the conventional LSM-based trilateration technique.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.9
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• pp.866-871
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• 2010

Gait analysis is essential for leg diagnosis and rehabilitation for the patients, the handicapped and the elderly. The use of 3D motion capture device for gait analysis is very common for gait analysis. However, this device has several shortcomings including limited workspace, visibility and high price. Instead, we developed gait estimation system using gyroscopes. This system provides gait information including the number of gaits, stride and walking distance. With four gyroscope (one for each leg's thigh and calf) outputs, the proposed gait modeling estimates the movements of the hip, the knees and the feet. Complete pedestrian localization is implemented with gait information and the heading angle estimated from the rate gyro and the magnetic compass measurements. The developed system is very useful for diagnosis and the rehabilitation of the pedestrian at the hospital. It is also useful for indoor localization of the pedestrians.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.1080-1084
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• 2007

Many different methods for sound source localization have been developed. Most of them mainly depend on time delay of arrival (TDOA) or on empirical or analytic head related transfer functions (HRTFs). In real implementation, since the direct path between a source and a sensor is interrupted by obstacles as like a head or body of robot, it has to be considered the number of sensors as well as their positions. Therefore, in this paper, we present the methods, which are included sensor position problem, to localize the sound source with 4 microphones to cover the 3D space. Those are modified two-step TDOA methods. Our conclusion is that the different method has to be applied in case to be different microphone position on real robot platform.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.11
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• pp.952-959
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• 2016

This paper proposes a novel indoor positioning system (IPS) that uses a calibrated camera sensor network and dense 3D map information. The proposed IPS information is obtained by generating a bird's-eye image from multiple camera images; thus, our proposed IPS can provide accurate position information when objects (e.g., the mobile robot or pedestrians) are detected from multiple camera views. We evaluate the proposed IPS in a real environment with moving objects in a wireless camera sensor network. The results demonstrate that the proposed IPS can provide accurate position information for moving objects. This can improve the localization performance for mobile robot operation.

• Journal of Ocean Engineering and Technology
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• v.38 no.3
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• pp.115-123
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• 2024

USBL systems are essential for providing accurate positions of autonomous underwater vehicles (AUVs). On the other hand, the accuracy can be degraded by outliers because of the environmental conditions. A failure to address these outliers can significantly impact the reliability of underwater localization and navigation systems. This paper proposes a novel outlier rejection algorithm for AUV localization using Voronoi diagrams and query point calculation. The Voronoi diagram divides data space into Voronoi cells that center on ultra-short baseline (USBL) data, and the calculated query point determines if the corresponding USBL data is an inlier. This study conducted experiments acquiring GPS and USBL data simultaneously and optimized the algorithm empirically based on the acquired data. In addition, the proposed method was applied to a sensor fusion algorithm to verify its effectiveness, resulting in improved pose estimations. The proposed method can be applied to various sensor fusion algorithms as a preprocess and could be used for outlier rejection for other 2D-based location sensors.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.113-116
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• 2006

In this paper, we first implement an audio playback system for virtual reality by providing 3D audio effects to listeners. In general, such a 3D audio playback system utilizes a sound localization technique using head related transfer function (HRTF) to generate 3D audio effect. However, the 3D audio effect is degraded due to the crosstalk in the stereo loudspeaker environment. To enhance the 3D sound effect, we implement the crosstalk cancellation technique proposed by Atal and Schroeder and apply it to the 3D audio system.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.51.3-51
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• 2002

3D sound user often finds the results that the sound image appear to originate either inside, or close to, the head when he uses headphone-based binaural system. This phenomenon is called in-head localization(IHL). The main factors were chosen to evaluate externalization performance : individualized HRTFs, near-field HRTF characteristics and reverberation. Direct comparison was conducted among them, especially two factors\ulcorner reverberation and near-field HRTFs.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.481-492
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• 2005

To guide the guiding robot for the visually impaired carefully, the digital map to be used to search a path must be detailed and has some information about dangerous spots. It also has to search not only safe but also short path through the position data by GPS and INS sensors. In this paper, as the difference of the ability that the visually unpaired can recognize, we have developed the localization tracking system so that it can make a movement path and verify position information, and the global navigation system for the visually impaired using the GPS and INS. This system can be used when the visually impaired move short path relatively. We had also verified that the system was able to correct the position as the assistant navigation system of the GPS on the outside.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1697-1703
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• 2014

In this paper, we propose an indoor RSSI (received signal strength indication)-based localization method that uses virtually overlapped visible light with an indoor LED lighting system. In our system, a photodiode (PD) measures the RSSI from LED lamps that blink in one row or column units. Subsequently, the RSSI is used to obtain the horizontal distances between the LED lamps and the receiver with the predetermined characteristics curve, R-D curve, that represents the relation between the RSSI and the horizontal distances. When the controlled LED lamps blink in one row or column units, the R-D curve at the border of the LED lamps is different because of the weak lighting, which results in the position sensing error of the receiver. The deviation of the optical power of each LED also causes the error. To solve these problems, we propose a method that overlaps the visible light through the numerical operation at the receiver side without any modification of the light source side. Our proposed method has been simulated in a room measuring $1.2{\times}1.2{\times}1.8m^3$ considering the effect of the error on the optical power of the LED. The simulation result shows that the proposed method eliminates the error condition with the R-D curve and achieves an average positioning error of 13.4 mm under the error rate 3% of the optical power.

• Journal of Advanced Navigation Technology
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• v.23 no.6
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• pp.526-534
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• 2019

Localization methods using radio signals should obtain range measurements from three or more anchors. However, a typical building consists of narrow, long hallways and corners, making it difficult to secure more than three light of sight anchors. The result is a multi-modal solution that makes it difficult to estimate the user's location. In order to overcome this problem, this paper proposes a method for estimating the location using artificial neural networks. Using the artificial neural network, even if a multi-modal solution occurs, the position can be estimated by acquiring user movement pattern information based on accumulated range measurements. The method does not require any additional equipment or sensors, and only anchor-based range measurements can estimate the user's location. In order to verify the proposed method, location estimation tests were performed in situations where the multi-modal solution occurred by installing an insufficient number of anchors in a building. As a result, it was confirmed that the location can be estimated even when the number of anchors is insufficient.