• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• Journal of Sensor Science and Technology
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• v.19 no.3
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• pp.202-208
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• 2010

This study examined the dependency of crystalline orientation and electric properties of sol-gel PZT film on hydrolysis, a $PbTiO_3$ seed layer and a concentration of sol-gel solution. The PZT thin films were prepared by using 2-Methoxyethanol-based sol-gel method and spin-coating on Pt/Ti/$SiO_2$/Si substrates. The 1-${\mu}m$-thick PZT films were coated and then fired in a furnace by direct insert method. The highly (111) oriented PZT film of pure perovskite structure could be obtained. We could control the degree of orientation by various parameters such as hydrolysis, a $PbTiO_3$ seed layer and a concentration of sol-gel solution. The highest measured remanent polarization, dielectric constant and piezoelectric coefficient are $24.16\;{\mu}C/cm^2$, 2808, and 159 pC/N, respectively.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.366-367
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• 2006

Different orientated SBN thin films were deposited by Ion Beam Sputtering, and electric properties were measured on each orientation. Ferroelectric $Sr_xBa_{1-x}Nb_2O_6$(SBN) has excellent electro-optic, photo-refractive, piezoelectric, pyroelectric properties. SBN thin film has been deposited by various method, of sol-gel, PLD, CVD, sputtering, etc.. To avoid lead pollution of Pb-system perovskite ferroelectric materials. SBN thin films were fabricated for pyroelectric IR sensor. Using the ceramic target of the same composition and Pt(100)/$TiO_2/SiO-2$/Si(100) substrate, crystallization and orientation behavior as well as electric properties of the films were examined. Seed layer and thin films thickness was controlled to observe the effect on preferred orientation. We measured I-V, C-V, P-E hysteresis to characterize electric-properties on each orientations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.11a
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• pp.59-60
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• 2007

• Spatial Information Research
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• v.10 no.3
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• pp.407-419
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• 2002

In this study, the design of 4S-Van system is discussed fur the implementation of laser mapping system. Laser device is fast and accurate sensor that acquires 3D road and surface data. The orientation laser sensor is determined by loosely coupled (D)GPS/INS Integration. Considering current system architecture, (D)GPS/INS integration is performed far performance analysis of direct georeferencing and self-calibration is performed for interior and exterior orientation and displacement. We utilized 3 laser sensors for compensation and performance improvement. 3D surface data from laser scanner and texture image from CCD camera can be used to implement 3D visualization.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.87-98
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• 1999

This study is concentrated on the development of real-time estimation model and vision control method as well as the experimental test. The proposed method permits a kind of adaptability not otherwise available in that the relationship between the camera-space location of manipulable visual cues and the vector of manipulator joint coordinates is estimate in real time. This is done based on a estimation model ta\hat generalizes known manipulator kinematics to accommodate unknown relative camera position and orientation as well as uncertainty of manipulator. This vision control method is roboust and reliable, which overcomes the difficulties of the conventional research such as precise calibration of the vision sensor, exact kinematic modeling of the manipulator, and correct knowledge of position and orientation of CCD camera with respect to the manipulator base. Finally, evidence of the ability of real-time vision control method for manipulator's position control is provided by performing the thin-rod placement in space with 2 cues test model which is completed without a prior knowledge of camera or manipulator positions. This feature opens the door to a range of applications of manipulation, including a mobile manipulator with stationary cameras tracking and providing information for control of the manipulator event.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2289-2301
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• 2015

Mobile devices are becoming powerful enough to realize augmented reality (AR) application. This paper introduces two AR methods to estimate an environmental illumination distribution of a scene. In the first method, we extract the lighting direction and intensity from input images captured with a front-side camera of a mobile device, using its orientation sensor. The second method extracts shadow regions cast by three dimensional (3D) AR marker of known shape and size. Because previous methods examine per pixel shadow intensity, their performances are much affected by the number of sampling points, positions, and threshold values. By using a simple binary operation between the previously clustered shadow regions and the threshold real shadow regions, we can compute efficiently their relative area proportions according to threshold values. This area-based method can overcome point sampling problem and threshold value selection. Experiment results demonstrate that the proposed methods generate natural image with multiple smooth shadows in real-time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2948-2963
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• 2015

In the field of computer vision, visual surveillance systems have recently become an important research topic. Growth in this area is being driven by both the increase in the availability of inexpensive computing devices and image sensors as well as the general inefficiency of manual surveillance and monitoring. In particular, the ultimate goal for many visual surveillance systems is to provide automatic activity recognition for events at a given site. A higher level of understanding of these activities requires certain lower-level computer vision tasks to be performed. So in this paper, we propose an intelligent activity recognition model that uses a structure learning method and a classification method. The structure learning method is provided as a K2-learning algorithm that generates Bayesian networks of causal relationships between sensors for a given activity. The statistical characteristics of the sensor values and the topological characteristics of the generated graphs are learned for each activity, and then a neural network is designed to classify the current activity according to the features extracted from the multiple sensor values that have been collected. Finally, the proposed method is implemented and tested by using PETS2013 benchmark data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2064-2071
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• 2012

The generalization trend of smart phones have brought many smartphone games into daily lives. These games are mainly dependent on the interactions on the display of the phone using finger touches. On the other hand, functions for detecting the positions and actions of the phones such as gyro-sensors have been rapidly developed over the former orientation sensors and acceleration sensors. Though it has become technologically possible to detect the users' motion via the smartphone devices and to use the phone device directly as the game device, it is hard to find the actualized cases. This paper proposes a new paradigm including basic frameworks and algorithm for the games combining the motion recognitions and mutual communications on the smartphones and finally presents the details of its implementation and results.

• Journal of Magnetics
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• v.14 no.1
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• pp.42-46
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• 2009

The measurement of external magnetic field orientation using Giant Magneto Impedance (GMI) sensors has been performed. A soft magnetic alloy of $Co_{30}Fe_{34}Ni_{36}$ was electroplated on a Si wafer with a CoFeNi seed layer. V-shaped microwire patterns were formed using a conventional photolithography process. An external magnetic field was generated by a rectangular AlNiCo permanent magnet. The reference direction was defined as the external magnetic field direction oriented in the middle of 2 GMI devices. As the orientation of the magnetic field deviated from the reference direction, variation in the field component along each device introduced voltage changes. It was found that, by taking the voltage difference between the left and right arms of the Vshaped device, the nonlinearity of each device could be significantly reduced. The fabricated angle sensor had a linear range of approximately $70^{\circ}$ and an overall sensitivity of approximately 10 mV.