• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.1016-1021
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• 2005

A piezoresistive pressure sensor using a silicone rubber membrane has been fabricated on the selectively diffused (100)-oriented n/n+/n silicon substrates by a unique silicon micromachining technique using porous silicon ething. The width, length and thickness of the beam were 120${\mu}m$, 600${\mu}m$ and 7${\mu}m$, respectively and the thickness of the silicone rubber membrane was 40${\mu}m$. By the fusion of silicon beam and silicone rubber membrane, the mechanical strength of the pressure sensor could be highly improved due to smaller shear stress. The effectiveness of the sensor was confirmed through an experiment and FEM simulation in which the pressure sensor was characterized.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.6
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• pp.33-42
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• 2010

This research propose a practical guidance system considering ocean currents in real sea operation. Optimality of generated path is not an issue in this paper. Way-points from start point to possible goal positions are selected by experienced human supervisors considering major ocean current axis. This paper also describes the implementation of a precise underwater navigation solution using multi-sensor fusion technique based on USBL, GPS, DVL and AHRS measurements in detail. To implement the precise, accurate and frequent underwater navigation solution, three strategies are chosen. The first one is the heading alignment angle identification to enhance the performance of standalone dead-reckoning algorithm. The second one is that absolute position is fused timely to prevent accumulation of integration error, where the absolute position can be selected between USBL and GPS considering sensor status. The third one is introduction of effective outlier rejection algorithm. The performance of the developed algorithm is verified with experimental data of mine disposal vehicle and deep-sea ROV.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.54-59
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• 2010

This paper present to study the guidance system as localization technique using sensor fusion and line tracking technique using virtual line for AGV(autonomous guided vehicle). An existing AGV could drive on decided line only. And representative guidance systems of such guidance system are magnet-gyro guidance and wired guidance. However, those have had the high cost of installation and maintenance, and the difficulty of system change according to variation of working environment. To solve such problems, we make the localization system which is fused with a laser navigation and gyro, encoder. The system is robust against noise, and flexible according to working environment through sensor fusion. For line tracking of laser navigation without wire guidance, we set the virtual line in program, and design the driving controller based on difference of angle and distance between AGV's position and decided virtual line. To experiment, we use the AGV which is made by ourselves, and experiment the line tracking repeatedly on same experimental environment. In result, maximum distance error between decided virtual line and AGV's position was less than 49.93mm, and we verified that the proposed system is efficient for line tracking of actual AGV.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.5
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• pp.434-443
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• 2007

Presently, the exploration of an unknown environment is an important task for thee new generation of mobile service robots and mobile robots are navigated by means of a number of methods, using navigating systems such as the sonar-sensing system or the visual-sensing system. To fully utilize the strengths of both the sonar and visual sensing systems. This paper presents a technique for localization of a mobile robot using fusion data of multi-ultrasonic sensors and vision system. The mobile robot is designed for operating in a well-structured environment that can be represented by planes, edges, comers and cylinders in the view of structural features. In the case of ultrasonic sensors, these features have the range information in the form of the arc of a circle that is generally named as RCD(Region of Constant Depth). Localization is the continual provision of a knowledge of position which is deduced from it's a priori position estimation. The environment of a robot is modeled into a two dimensional grid map. we defines a vision-based environment recognition, phisically-based sonar sensor model and employs an extended Kalman filter to estimate position of the robot. The performance and simplicity of the approach is demonstrated with the results produced by sets of experiments using a mobile robot.

• Journal of Ocean Engineering and Technology
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• v.11 no.3
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• Korean Journal of Remote Sensing
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• v.19 no.4
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• pp.329-339
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• 2003

In this study, an approach of image fusion in decision level has been proposed for unsupervised image classification using the images acquired from multiple sensors with different characteristics. The proposed method applies separately for each sensor the unsupervised image classification scheme based on spatial region growing segmentation, which makes use of hierarchical clustering, and computes iteratively the maximum likelihood estimates of fuzzy class vectors for the segmented regions by EM(expected maximization) algorithm. The fuzzy class vector is considered as an indicator vector whose elements represent the probabilities that the region belongs to the classes existed. Then, it combines the classification results of each sensor using the fuzzy class vectors. This approach does not require such a high precision in spatial coregistration between the images of different sensors as the image fusion scheme of pixel level does. In this study, the proposed method has been applied to multispectral SPOT and AIRSAR data observed over north-eastern area of Jeollabuk-do, and the experimental results show that it provides more correct information for the classification than the scheme using an augmented vector technique, which is the most conventional approach of image fusion in pixel level.

• Journal of Power System Engineering
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• v.5 no.4
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• pp.11-17
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• 2001

Micronization of sensor is a trend of the silicon sensor development with regard to a piezoresistive silicon pressure sensor, the size of the pressure sensor diaphragm have become smaller year by year, and a microaccelerometer with a size less than $200{\sim}300{\mu}m$ has been realized, In this paper, we study some of the bonding processes of SCS(single crystal silicon) insulator wafer for the microaccelerometer. and their subsequent processes which might affect thermal loads. The finite element method(FEM) has been a standard numerical modeling technique extensively utilized in micro structural engineering discipline for design of SCS insulator wafers. Successful temperature distribution analysis and design of the SCS insulator wafers based on the tunneling current concept using microaccelerometer depend on the knowledge about normal mechanical properties of the SCS and $SiO_2$ layer and their control through manufacturing processes.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.249-254
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• 2007

A mobile robot with various types of sensors and wireless camera is introduced. We show this mobile robot can detect objects well by combining the results of active sensors and image processing algorithm. First, to detect objects, active sensors such as infrared rays sensors and supersonic waves sensors are employed together and calculates the distance in real time between the object and the robot using sensor's output. The difference between the measured value and calculated value is less than 5%. We focus on how to detect a object region well using image processing algorithm because it gives robots the ability of working for human. This paper suggests effective visual detecting system for moving objects with specified color and motion information. The proposed method includes the object extraction and definition process which uses color transformation and AWUPC computation to decide the existence of moving object. Shape information and signature algorithm are used to segment the objects from background regardless of shape changes. We add weighing values to each results from sensors and the camera. Final results are combined to only one value which represents the probability of an object in the limited distance. Sensor fusion technique improves the detection rate at least 7% higher than the technique using individual sensor.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.289-297
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• 2009

This paper presents the development and control of a two wheeled car-like mobile robot using balancing mechanism whose heading control is done by turning the handle. The mobile inverted pendulum is a combined system of a mobile robot and an inverted pendulum system. A sensor fusion technique of low cost sensors such as a gyro sensor and a tilt sensor to measure the balancing angle of the inverted pendulum robot system accurately is implemented. Experimental studies of the trajectory following control task has been conducted by command of steering wheel while balancing.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.75-83
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• 2018

Predictive IoT Sensor Algorithm is a technique of data science that helps computers learn from existing data to predict future behaviors, outcomes, and trends. This algorithm is a cloud predictive analytics service that makes it possible to quickly create and deploy predictive models as analytics solutions. Sensors and computers collect and analyze data. Using the time series prediction algorithm helps to predict future temperature. The application of this IoT in industrial environments like power plants and factories will allow organizations to process much larger data sets much faster and precisely. This rich source of sensor data can be networked, gathered and analyzed by super smart software which will help to detect problems, work more productively. Using predictive IoT technology - sensors and real-time monitoring - can help organizations exactly where and when equipment needs to be adjusted, replaced or how to act in a given situation.