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박장현(Jahng-Hyon Park),김민수(Minsoo Kim) Korean Society for Precision Engineering 2005 한국정밀공학회지 Vol.22 No.4
There is a necessity for the communication between intelligent robots and human beings because of wide spread use of them. Gesture recognition is currently being studied in regards to better conversing. On the basis of previous research, however, the gesture recognition algorithms appear to require not only complicated algorisms but also separate training process for high recognition rates. This study suggests a gesture recognition algorithm based on computer vision system, which is relatively simple and more efficient in recognizing various human gestures. After tracing the hand gesture using a marker, direction changes of the gesture trajectory were analyzed to determine the simple gesture code that has minimal information to recognize. A map is developed to recognize the gestures that can be expressed with different gesture codes. Through the use of numerical and geometrical trajectory, the advantages and disadvantages of the suggested algorithm was determined.
박준영(Joonyoung Park),박장현(Jahng-hyon Park),박지형(Jihyoung Park),박동수(Dongsoo Park) 대한기계학회 2003 대한기계학회 춘추학술대회 Vol.2003 No.4
The emotion recognition is one of the most significant interface technologies which make the high level of<br/> human-machine communication possible. The central nervous system stimulated by emotional stimuli affects<br/> the autonomous nervous system like a heart, blood vessel, endocrine organs, and so on. Therefore bio-signals<br/> like HRV, ECG and EEG can reflect one’s emotional state. This study investigates the correlation between<br/> emotional states and bio-signals to realize the emotion recognition. This study also covers classification of<br/> human emotional states, selection of the effective bio-signal and signal processing. The experimental results<br/> presented in this paper show possibility of the emotion recognition.
LSTM 기반 Model-Free LKAS 조향 각 생성
김현우(Hyun-Woo Kim),박장현(Jahng-Hyon Park) 제어로봇시스템학회 2017 제어·로봇·시스템학회 논문지 Vol.23 No.9
In this paper, we propose a lateral upper controller that predicts vehicle motion and generates a model-free LKAS steering angle by applying long-term memory (LSTM), one of the deep learning techniques. The apparent and distinct advantage of this LSTM model is that the relationship of nonlinear sensor data can be grasped and learned devoid of a mathematical model while using the time information. In this sense, the LKAS steering angle can be generated by predicting the movement of the vehicle in consideration of the past vehicle motion based on the sensor data. In addition, the time delay problem due to the difference of sampling time on each sensor can be simply solved by learning based on a time table which has a synchronized sampling time. The input values of the upper controller are the coefficient of the road model and the vehicle dynamic characteristics are obtained from the image processing data from the camera sensor. As for the target values, the steering angles in the next state are selected. The learning model was developed by learning the many-to-one LSTM prediction model with serial connection of LSTM and Fully-Connected (FC) Multilayer Perceptron (MLP). For implementation of the learning model, Tensorflow is employed and the data from a real test road was used. With this model, the learning is conducted and its effectiveness is shown by comparing with a LKAS lateral controller using a model-based multi rate Kalman Filter (MKF).
수동 RFID Tag를 기반으로 한 이동 로봇의 경로 계획 알고리즘
지용관(Yong Kwan Ji),박장현(Jahng-Hyon Park) Korean Society for Precision Engineering 2009 한국정밀공학회지 Vol.26 No.8
In this paper, a navigation algorithm is proposed using RFID tags in indoor environments. Firstly, a stochastic sensor model of RFID is derived and the design factors including the maximum identifiable distance, the identification direction and the read success rate are obtained through experiments. The obstacle avoidance algorithm is developed with consideration of those factors for a variety of RFID antenna configurations and different indoor environments. The algorithm is tested by computer simulations and implemented on a mobile robot.
로봇과 환경과의 충돌시 명령 신호 변경을 통한 충격량 감소
신완재(Wanjae Shin),박장현(Jahng-Hyon Park) 대한기계학회 2004 대한기계학회 춘추학술대회 Vol.2004 No.4
A robot manipulator is usually operated in two modes: free motion and constraint motion according to the fact whether the robot comes into contact with the environment or not. At the moment of contact, impact occurs, and sometimes, it can possibly degrade the robot’s performance such as vibration and at worst, shortens its lifetime. In this article, a new proposed algorithm is described by introducing a command signal modification method on the basis of impedance control and a validity of the proposed algorithm is demonstrated by showing the simulation study.