• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3037-3040
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• 2000

Real-Time object tracking has emerged as an important component in several application areas including machine vision. surveillance. Human-Computer Interaction. image-based control. and so on. And there has been developed various algorithms for a long time. But in many cases. they have showed limited results under uncontrolled situation such as illumination changes or cluttered background. In this paper. we present a novel. computationally efficient algorithm for tracking human face robustly under illumination changes and cluttered backgrounds. Previous algorithms usually defines color model as a 2D membership function in a color space without consideration for illumination changes. Our new algorithm developed here. however. constructs a 3D color model by analysing plenty of images acquired under various illumination conditions. The algorithm described is applied to a mobile head-eye robot and experimented under various uncontrolled environments. It can track an human face more than 100 frames per second excluding image acquisition time.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.701-706
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• 2007

Recently, a number of researches about linear magnetorheological(MR) damper using valve-mode characteristics of MR fluid have sufficiently undertaken, but researches about rotary MR damper using shear-mode characteristics of MR fluid are not enough. In this paper, we performed vibration control of shear-mode MR damper for unlimited rotating actuator of mobile robot. Also fuzzy logic based vibration control for shear-mode MR damper is suggested. The parameters, like scaling factor of input/output and center of the triangular membership functions associated with the different linguistic variables, are tuned by genetic algorithm. Simulation results demonstrate the effectiveness of the fuzzy-skyhook controller for vibration control of shear-mode MR damper under impact force.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.291-296
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• 2008

This paper presents the dodecagon-based Q-leaning and SVM algorithm for object search with multiple robots. We organized an experimental environment with several mobile robots, obstacles, and an object. Then we sent the robots to a hallway, where some obstacles were tying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making(DBAM) and Area-based action making(ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and SVM to enhance the fusion model with Distance-based action making(DBAM) and Area-based action making(ABAM) process.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.898-902
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• 2015

Alternative radio-navigation technologies aim at providing continuous navigation solution even if one cannot use GNSS (Global Navigation Satellite System). In shadowing region such as indoor environment, GNSS signal is no longer available and the alternative navigation system should be used together with GNSS to provide seamless positioning. For soldiers in battlefield where GNSS signal is jammed or in street battle, the alternative navigation system should work without positioning infrastructure. Moreover, the radio-navigation system should have scalability as well as high accuracy performance. This paper presents a TWR (Two-Way-Ranging)-based cooperative positioning system (CPS) that does not require location infrastructure. It is assumed that some members of CPS can obtain GNSS-based position and they are called mobile anchors. Other members unable to receive GNSS signal compute their position using TWR measurements with mobile anchors and neighboring members. Error propagation in CPS is analytically studied in this paper. Error budget for TWR measurements is modeled first. Next, location error propagation in CPS is derived in terms of range errors. To represent the location error propagation in the CPS, Location Error Propagation Indicator (LEPI) is proposed in this paper. Simulation results show that location error of tags in CPS is mainly influenced by the number of hops from anchors to the tag to be positioned as well as the network geometry of CPS.

• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.142-148
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• 2003

Reinforcement learning is considered as an important tool for robotic learning in unknown/uncertain environments. In this paper, we propose an evaluation function expressed in a vector form to realize multi-dimensional reinforcement learning. The novel feature of the proposed method is that learning one behavior induces parallel learning of other behaviors though the objectives of each behavior are different. In brief, all behaviors watch other behaviors from a critical point of view. Therefore, in the proposed method, there is cross-criticism and parallel learning that make the multi-dimensional learning process more efficient. By ap-plying the proposed learning method, we carried out multi-dimensional evaluation (reward) and multi-dimensional learning simultaneously in one trial. A special neural network (Q-net), in which the weights and the output are represented by vectors, is proposed to realize a critic net-work for Q-learning. The proposed learning method is applied for behavior planning of mobile robots.

• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2690-2692
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• 2005

CAN communication can minimize the interfacing lines between equipments because it is composed of only the input and output lines, also is used for automatic system including vehicle, aircraft, railway vehicles and robot because the reliability of data is high by the capability of data-related error detect and correcting function. It can also improve the low-reliable and inefficient system which is composed of the existing Wiring Harness(W/H), so in case of vehicle, it is used in place of the present ECU as the new electro-control unit. In this paper, we constructed the electro-control unit of vehicle by using CAN communication and implemented system that could monitor the condition of vehicle through the web or mobile by connecting the electro-control unit to imbedded system. Such a system is expected to be helpful to the intelligent vehicle and the adoption of ACC(Adaptive Cruise Control).

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2007.04a
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• pp.84-89
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• 2007

In this paper, we introduce a new technique for automatic construction of steel frames in high-rise buildings. Basically, we combine advanced robotic technologies to building construction techniques. Four main topics will be developed such as: 1) Planning and synthesis of automatic construction system, 2) Development of construction factory system with climbing oil-pressured robot, 3) Core techniques for automatic assembly for steel frames, and 4) Intelligent resource management system. We expect that this new technique will increase the construction efficiency and will alleviate the manpower shortage problem in the aging society.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.369-370
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• 2012

프로젝터를 이용하여 대형 화면을 투사할 경우, 밝기와 해상도 등으로 인하여 세세한 시각 정보 전달에 어려움이 발생한다. 본 논문에서는 공간에 설치된 프로젝터가 투영한 낮은 해상도의 대형 화면에서 사용자의 관심 영역을 하이라이트하는 방식으로 이 문제를 해결하고자 한다. 이를 위해 사용자의 관심 영역을 제스쳐 인식을 통해 파악하고, 사용자와 상호작용할 수 있는 지능화 공간과 증강된 시각정보를 투영할 수 있는 프로젝터가 탑재된 모바일 로봇을 소개한다. 본 논문에서는 지능화 공간 내에서 프로젝터가 탑재된 로봇을 이용하여 상호작용이 가능한 다중해상도 디스플레이 방식을 기술하고, 실험을 통하여 이 시스템의 가능성 및 유용성을 확인하고자 한다.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.449-456
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• 2019

This paper is a study on the construction of a wall-climbing mobile robot using vacuum suction and wheel-type movement, and a comparison of the performance of an automatic wall crack detection algorithm based on machine learning that is suitable for such an embedded environment. In the embedded system environment, we compared performance by applying recently developed learning methods such as YOLO for object learning, and compared performance with existing edge detection algorithms. Finally, in this study, we selected the optimal machine learning method suitable for the embedded environment and good for extracting the crack features, and compared performance with the existing methods and presented its superiority. In addition, intelligent problem - solving function that transmits the image and location information of the detected crack to the manager device is constructed.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.136-145
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• 2009

The objective of the Intelligent Excavation System (IES) is to recognize the work environment and produce work plan and automatically control the excavator through integrating sensor and robot technologies. This paper discusses one of the core technologies of IES development project, development of 3D work environment modeling. 3D laser scanner is used for 3-dimensional mathematical model that can be visualized in virtual space in 3D. This paper describes (1) how the most appropriate 3D imaging system has been chosen; (2) the development of user interface and customization of the s/w to control the scanner for IES project; (3) the development of the mobile station for the scanner; (4) and the algorithm for the automatic registration of laser scan segments for IES project. The development system has been tested on the construction field and lessons learned and future development requirements are suggested.