• 제어로봇시스템학회논문지
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• 제13권11호
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• pp.1074-1081
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• 2007

This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

• 로봇학회논문지
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• 제4권1호
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• pp.10-16
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• 2009

This paper is concerned with Korean students' attitudes towards robots, presenting two survey studies. The first study was concerned with a group of college students, taking the perspective of international comparison. Data were collected by administering an online survey, where 106 volunteer students had participated. In the survey, the Negative Attitude towards Robot Scale(NARS) was adopted to compare the Korean students' scores with those of multi-national groups (U.S.A, Germany, Netherland, Japan, Mexico, and China) who responded to the same scale in Bartneck et al.'s research. The analysis of the data reveals that Korean students tend to be more concerned about social impacts that robots might bring to future society and are very conscious about the uncertain influences of robots on human life. The second study investigated factors that may affect K-12 students' attitudes towards robots, with survey data garnered from 298 elementary, middle, and high school students. The data were analyzed by the method of multiple regression analysis to test the hypothesis that a student's gender, age, the extent of interest in robots, and the extent of experiences with robots may influence his or her attitude towards robots. The hypothesis was partially supported in that variables of a student's gender, age, and the extent of interest in robots were statistically significant with regard to the attitude variable. Given the results, this paper suggests three points of discussions to better understand Korean students' attitudes towards robots: social and cultural context, individual differences, and theory of mind.

• 로봇학회논문지
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• 제3권2호
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• pp.106-111
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• 2008

This paper presents a decentralized coordination for a small-scale mobile robot teams performing a task through cooperation. Robot teams are required to generate and maintain various geometric patterns adapting to an environment and/or a task in many cooperative applications. In particular, all robots must continue to strive toward achieving the team's mission even if some members fail to perform their role. Toward this end, given the number of robots in a team, an effective coordination is investigated for decentralized formation control strategies. Specifically, all members are required first to reach agreement on their coordinate system and have an identifier (ID) for role assignment in a self-organizing way. Then, employing IDs on individual robots within a common coordinate system, a decentralized neighbor-referenced formation control is realized to generate, keep, and switch between different geometric shapes. This approach is verified using an in-house simulator and physical mobile robots. We detail and evaluate the formation control approach, whose common features include self-organization, robustness, and flexibility.

• 제어로봇시스템학회논문지
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• 제14권6호
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• pp.523-529
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• 2008

In this paper, we proposed mobile LCD module test device on embedded based, when operating the existing LCD, divide flicker clearly in full frame, and configuration so as to support between other CPU interface, MDDI, SPI, 24Bit RGB interface, etc. that is based on a high-speed CPU. In addition, when demand to test about each pixel of LCD, it is possible to change IP design of H/W, FPGA, but proposed system is application possible without other design changing. Proposed system is made smaller and equipped with battery, so secure with mobility for effective test the LCD/OLED module and it is able to test the pattern by the client program, for example exiting picture, mpeg, simple pattern test and test per pixel, scale, rotation, Odd/Even pixel per video, etc. From now on, if integrating with independent test system and it is configured that is able to mutual communication and test, it is expected to reduce consumption of human resources and improve productivity for LCD module test.

• 로봇학회논문지
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• 제1권1호
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• pp.25-35
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• 2006

Improving practicality of SLAM requires various sensors to be fused effectively in order to cope with uncertainty induced from both environment and sensors. In this case, combining sonar and vision sensors possesses numerous advantages of economical efficiency and complementary cooperation. Especially, it can remedy false data association and divergence problem of sonar sensors, and overcome low frequency SLAM update caused by computational burden and weakness in illumination changes of vision sensors. In this paper, we propose a SLAM method to join sonar sensors and stereo camera together. It consists of two schemes, extracting robust point and line features from sonar data and recognizing planar visual objects using multi-scale Harris corner detector and its SIFT descriptor from pre-constructed object database. And fusing sonar features and visual objects through EKF-SLAM can give correct data association via object recognition and high frequency update via sonar features. As a result, it can increase robustness and accuracy of SLAM in indoor environment. The performance of the proposed algorithm was verified by experiments in home -like environment.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.95-98
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• 1996

Universal Learning Network(U.L.N.), which can model and control the large scale complicated systems naturally, consists of nonlinearly operated nodes and multi-branches that may have arbitrary time delays including zero or minus ones. Therefore, U.L.N. can be applied to many kinds of systems which are difficult to be expressed by ordinary first order difference equations with one sampling time delay. It has been already reported that learning algorithm of parameter variables in U.L.N. by forward and backward propagation is useful for modeling, managing and controlling of the large scale complicated systems such as industrial plants, economic, social and life phenomena. But, in the previous learning algorithm of U.L.N., time delays between the nodes were fixed, in other words, criterion function of U.L.N. was improved by adjusting only parameter variables. In this paper, a new learning algorithm is proposed, where not only parameter variables but also time delays between the nodes can be adjusted. Because time delays are integral numbers, adjustment of time delays can be carried out by a kind of random search procedure which executes intensified and diversified search in a single framework.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.96.3-96
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• 2002

A scheme of clarifying fault feature in the residual is given for model-based fault detection and diagnosis of control systems. It is based on the residual generation using a robust filter and the noise suppresion in test statistics of the residual by multi-scale discrete wavelet transform. By clarifying the fault feature in the residual, the difficulties of existing model based approaches via adopting a threshold can be overcomed and it has advantage of taking the false alarm and missed detection into acount at the same time, which can make the fault detection and diagnosis easy and correct. To show the effectiveness of our approach, the simulation results are illustrated for a linear syste...

• 한국의학물리학회지:의학물리
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• 제27권3호
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• pp.117-124
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• 2016

Intrafractional motion of patients, such as respiratory motion during radiation treatment, is an important issue in image-guided radiotherapy. The accuracy of the radiation treatment decreases as the motion range increases. We developed a control system for a robotic patient immobilization system that enables to reduce the range of tumor motion by compensating the tumor motion. Fusion technology, combining robotics and mechatronics, was developed and applied in this study. First, a small-sized prototype was established for use with an industrial miniature robot. The patient immobilization system consisted of an optical tracking system, a robotic couch, a robot controller, and a control program for managing the system components. A multi speed and position control mechanism with three degrees of freedom was designed. The parameters for operating the control system, such as the coordinate transformation parameters and calibration parameters, were measured and evaluated for a prototype device. After developing the control system using the prototype device, a feasibility test on a full-scale patient immobilization system was performed, using a large industrial robot and couch. The performances of both the prototype device and the realistic device were evaluated using a respiratory motion phantom, for several patterns of respiratory motion. For all patterns of motion, the root mean squared error of the corresponding detected motion trajectories were reduced by more than 40%. The proposed system improves the accuracy of the radiation dose delivered to the target and reduces the unwanted irradiation of normal tissue.

• 한국정밀공학회지
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• 제30권1호
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• pp.47-52
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• 2013

In order to operate a search and rescue robot in hazardous area, the robot requires high mobility and adaptable locomotion for moving in unpredictable environments. In this paper, we propose the deformable soft wheel robot that can produce three kinds of driving modes; caterpillar driving mode, normal wheel driving mode, legged-wheel driving mode. The robot changes its driving mode as it faces the various obstacles such as a small gap, stairs etc. Soft film and composite materials are used for fabrication of deformable wheel structure and Shape Memory Alloy (SMA) coil spring actuators are attached on the structure as an artificial muscle. Film lamination and an composite manufacturing process is introduced and the robot design is required to be modified and compromised to applying the manufacturing process. The prototype is developed and tested for verifying feasibility of the deformable wheel locomotion.

• International Journal of Control, Automation, and Systems
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• 제6권5호
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• pp.639-650
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• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.