• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.562-569
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• 2016

This paper proposes a navigation system with a robust localization method for an underwater unmanned vehicle. For robust localization with IMU (Inertial Measurement Unit), a DVL (Doppler Velocity Log), and depth sensors, the EKF (Extended Kalman Filter) has been utilized to fuse multiple nonlinear data. Note that the GPS (Global Positioning System), which can obtain the absolute coordinates of the vehicle, cannot be used in the water. Additionally, the DVL has been used for measuring the relative velocity of the underwater vehicle. The DVL sensor measures the velocity of an object by using Doppler effects, which cause sound frequency changes from the relative velocity between a sound source and an observer. When the vehicle is moving, the motion trajectory to a target position can be recorded by the sensors attached to the vehicle. The performance of the proposed navigation system has been verified through real experiments in which an underwater unmanned vehicle reached a target position by using an IMU as a primary sensor and a DVL as the secondary sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.5
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• pp.450-456
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• 2006

Monte Carlo localization is known to be one of the most reliable methods for pose estimation of a mobile robot. Although MCL is capable of estimating the robot pose even for a completely unknown initial pose in the known environment, it takes considerable time to give an initial pose estimate because the number of random samples is usually very large especially for a large-scale environment. For practical implementation of MCL, therefore, a reduction in sample size is desirable. This paper presents a novel approach to reducing the number of samples used in the particle filter for efficient implementation of MCL. To this end, the topological information generated through the thinning technique, which is commonly used in image processing, is employed. The global topological map is first created from the given grid map for the environment. The robot then scans the local environment using a laser rangefinder and generates a local topological map. The robot then navigates only on this local topological edge, which is likely to be similar to the one obtained off-line from the given grid map. Random samples are drawn near the topological edge instead of being taken with uniform distribution all over the environment, since the robot traverses along the edge. Experimental results using the proposed method show that the number of samples can be reduced considerably, and the time required for robot pose estimation can also be substantially decreased without adverse effects on the performance of MCL.

• Korea Trade Review
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• v.46 no.3
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• pp.99-117
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• 2021

Korea's FTA e-commerce regulations are evolving into a standardized norm. However, "location of computing facilities", which was not covered by Korea's existing FTA, was newly established in Korea's first Mega FTA, RCEP. China, a member of RCEP, restricts data movement and requires data localization through its Cybersecurity law. These facts have led to start this study with interest in data-related regulations. It examined country-specific and regulatory characteristics in the process of forming digital trade norms, using the TAPED established by Burri et al. (2020). It also analyzed the current status of introducing norms related to 'data flow', 'data localization' and 'data protection' of the EU, USA and China, which are leading the formation of e-commerce trade norms. Finally, the legal review was conducted to compare the exact meaning of the wording expressed in each agreement for the six recently enacted Mega FTAs and Digital Economic Agreements. These findings are meaningful in that they provided implications for the effectiveness of RCEP and the direction of negotiations on Korea's digital trade norms.

• Korean Business Review
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• v.11
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• pp.343-364
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• 1998

The results of the study show that managers of Korean manufacturing firms pursue international business strategy(IBS) to achieve four different objectives: global integration, national responsiveness, market expansion, or development and exploitation of firm-specific knowledge. IBS is closely related to the international business environment of the firms. When managers think they can exploit economies of scale by integrating worldwide operations, they prefer the global standardization strategy. Managers of firms which implement the localization strategy actively recognize the importance of the strategy more than those of other firms. IBS helps to improve the overall international competitiveness of the firms. Especially. implementing global standardization and localization simultaneously seems to be useful to strengthen the competitiveness of the firms.

• International Commerce and Information Review
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• v.15 no.1
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• pp.135-159
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• 2013

The globalization of business is making it more important than ever to understand how international human resource can be utilized more competitively. This study explores how the international human resource strategies between global integration and local responsiveness affects the company's competitive advantage. The findings for global integration strategy suggest that when a subsidiary is highly dependent on the parent company's resources and the findings for local responsiveness suggest that when a subsidiary is highly dependant on the host country's resources and institution. This study proposes competitive advantage by the global integration strategy and local responsiveness strategy. The effects of IHRM to create value for company's core competence was analyzed. Two IHRM strategic choices will affect the different competences such as integration and localization abilities. This paper also suggests the two kinds of core competences of IHRM strategies how impact on company's performance.

• Asia Marketing Journal
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• v.14 no.3
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• pp.137-151
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• 2012

Established in May 2005, INNOCEAN Worldwide started as an affiliate marketing and communications company of the Hyundai Motor Group and grew into a top agency ranked no. 2 in the South Korean market within seven years. Currently, INNOCEAN Worldwide has become a global company, operating in sixteen countries through four regional headquarters, fifteen overseas subsidiaries, and seven branch offices with more than 1,100 employees. The company holds top clients from finance, electronics, telecommunications, food, retail, education and other various industries. The accomplishment of INNOCEAN Worldwide can be summarized by the following five key factors. The first factor is INNOCEAN Worldwide's strong and enduring passion and commitment to enter the global market and to build and strengthen its global network. The second factor is achieving successful localization through recruiting talented employees for its overseas branches directly from the local workforce, which enables the company to overcome language barriers, cultural differences, and creative gaps among different regional markets. Third is the company's effective implementation of the 'Global Resource Remix' strategy, which incorporates the distinctive competencies of each overseas operation as a global company standard. Fourth is the creation of the 'Discover System,' a global knowledge management system enabling overseas offices worldwide to share each other's accumulated knowledge and experiences. The fifth factor is the successful establishment of INNOCEAN Worldwide's unique Total Marketing Solution Service. Through this service, the company has offered integrated consulting services for strategic brand management to solve various marketing problems. In summary, the passion and commitment of INNOCEAN Worldwide's top management for the company's globalization and the supporting system that enables such commitment have made it possible for the company to take a global leap and become not merely a company with global operations but a truly global company.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1400-1420
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• 2012

Object detection and tracking using visual sensors is a critical component of surveillance systems, which presents many challenges. This paper addresses the enhancement of object detection and tracking via the combination of multiple visual sensors. The enhancement method we introduce compensates for missed object detection based on the partial detection of objects by multiple visual sensors. When one detects an object or more visual sensors, the detected object's local positions transformed into a global object position. Local and global information exchange allows a missed local object's position to recover. However, the exchange of the information may degrade the detection and tracking performance by incorrectly recovering the local object position, which propagated by false object detection. Furthermore, local object positions corresponding to an identical object can transformed into nonequivalent global object positions because of detection uncertainty such as shadows or other artifacts. We improved the performance by preventing the propagation of false object detection. In addition, we present an evaluation method for the final global object position. The proposed method analyzed and evaluated using case studies.

• Journal of Korea Multimedia Society
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• v.17 no.9
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• pp.1092-1097
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• 2014

It is difficult to perform automatic formation flight of UAV (Unmanned Aerial vehicle) when GPS (Global Positionig System) is out of order or has a system error, since the relative position estimation in the flight group is impossible in that case. In this paper, we design a relative localization system for the automatic formation flight of UAV. For this purpose, we adopt digital beam forming (DBF) to estimate the angle with the central controller of the flight group and Particle Filtering scheme to compensate the estimation error of ToA (time of arrival) method. Computer simulation results present a proper distance between the central controller and a following unit to maintain the automatic formation flight.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.544-547
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• 1997

In this paper, we propose a dynamic localization method using a rotating sonar and a map. The proposed method is implemented by using extended Kalman filter. The state equation is based on the encoder propagation model and the encoder error model, and the measurement equation is a map-based measurement equation using a rotating sonar sensor. By utilizing sonar beam characteristics, map-based measurements are updated while AMR is moving continuously. By modeling and estimating systematic errors of a differential encoder, the position is successfully estimated even the interval of the map-based measurement. Monte-Carlo simulation shows that the proposed global position estimator has the performance of a few millimeter order in position error and of a few tenth degrees in heading error and of compensating systematic errors of the differential encoder well.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.102-107
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• 2011

In this paper we present cooperation of heterogeneous robot team, composed of a wheeled robot and a helicopter for localization and map building. This heterogeneous robot team can successfully fulfill task by combining the abilities of both robots than single robot because wheeled robot and helicopter have complementing ability. The scenario describes a tightly cooperative task, where the wheeled robot move carrying the helicopter and detect obstacles, if there are obstacles, helicopter take off for map building and land, then robot team move destination avoiding obstacles. We present PID controller for position control of helicopter and transformation algorithm to global coordinate from image pixel coordinate. Experimental result show that the proposed method is valid.