• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.10
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• pp.1095-1102
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• 2014

In this paper, We proposed the approach of GPU and motion vector to analysis the Human activity in real-time surveillance system. The most important part, that is detect blob(human) in the foreground. We use to detect Adaptive Gaussian Mixture, Weighted subtraction image for salient motion and motion vector. And then, We use motion vector for human activity analysis. In this paper, the activities of human recognize and classified such as meta-classes like this {Active, Inactive}, {Position Moving, Fixed Moving}, {Walking, Running}. We created approximately 300 conditions for the simulation. As a result, We showed a high success rate about 86~98%. The results also showed that the high resolution experiment by the proposed GPU-based method was over 10 times faster than the cpu-based method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.398-405
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• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.3
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• pp.471-479
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• 2019

This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.15-27
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• 2022

An omnidirectional VR treadmill is a highly-immersive walking simulator that allows identical body movements, such as walking, running, and sitting. However, the operation difficulty of an omnidirectional VR treadmill may cause data reliability problems. Therefore, this study aims to verify the effectiveness of a VR treadmill by comparing the ability to orient in the real and virtual worlds spatially. For this purpose, a rotating and searching path experiment was conducted with participants. This experiment showed that there was no statistically significant difference in the ability of the participants to orient in the real and virtual worlds spatially. In addition, the omnidirectional VR treadmill requires an adaptation time for the users due to the difficulty in the treadmill operation. However, there was no significant difference in the difficulty felt by the participants according to the adaptation time. Hence, these findings supported the possibility of collecting realistic walking data without safety concerns through an omnidirectional VR treadmill. Furthermore, this treadmill could be used in future research to solve problems directly related to pedestrian safety, such as the interaction between vehicles and pedestrians.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.87-96
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• 2022

The traffic vulnerable, including elderly pedestrians, have a relatively low walking speed and slow cognitive response time due to reduced physical ability. Although a smart crossing system has been developed and operated to improve problem, it is difficult to operate a signal that reflects the appropriate walking speed for each pedestrian. In this study, a neural network model and a multiple regression model-based traversing speed estimation model were developed using image information collected in an area with a high percentage of traffic vulnerability. to support the provision of optimal walking signals according to real-time traffic weakness. actual traffic data collected from the urban traffic network of Paju-si, Gyeonggi-do were used. The performance of the model was evaluated through seven selected indicators, including correlation coefficient and mean absolute error. The multiple linear regression model had a correlation coefficient of 0.652 and 0.182; the neural network model had a correlation coefficient of 0.823 and 0.105. The neural network model showed higher predictive power.

• ETRI Journal
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• v.42 no.1
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• pp.46-53
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• 2020

Gait analysis is an effective clinical tool across a wide range of applications. Recently, inertial measurement units have been extensively utilized for gait analysis. Effective gait analyses require good estimates of heel-strike and toe-off events. Previous studies have focused on the effective device position and type of triaxis direction to detect gait events. This study proposes an effective heel-strike and toe-off detection algorithm using a smart insole with inertial measurement units. This method detects heel-strike and toe-off events through a time-frequency analysis by limiting the range. To assess its performance, gait data for seven healthy male subjects during walking and running were acquired. The proposed heel-strike and toe-off detection algorithm yielded the largest error of 0.03 seconds for running toe-off events, and an average of 0-0.01 seconds for other gait tests. Novel gait analyses could be conducted without suffering from space limitations because gait parameters such as the cadence, stance phase time, swing phase time, single-support time, and double-support time can all be estimated using the proposed heel-strike and toe-off detection algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.1
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• pp.24-28
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• 2013

In this paper, a procedure of design and development of a child-sized humanoid robot is described. The design concept for a humanoid robot was proposed and the mechanism of the humanoid robot which is more than 1 meter tall was designed by using 3D design tools. By considering the lightweight of the robot, the hardware for the robot was designed for optimal performance. The frames and links of the robot designed by 3D design tools was manufactured through precision machining with the material which is light and have a good strength. The manufactured child-sized humanoid robot was experimented with basic motions applied inverse kinematics and balance control, and the performance of the motions were verified.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.601-607
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• 2006

This paper proposes a novel balance control scheme of a biped robot to predict the next position of ZMP using Kalman Filter. The mathematical model of the biped robot is generally approximated by 3D-LIPM(3D-Linear Inverted Pendulum Mode), but it cannot completely express the robot's dynamics. The stability of the biped robot depends on whether the ZMP(Zero Moment Point) position is in the stability region or out of. And the internal error between the robot mechanism and its model could affect the stability of a robot. Therefore, the proposed balance control not reduces the internal error, but also timely generates the proper control. The experiment of the proposed balance control is simulated on the virtual workspace where the biped robot may encounter with various difficulties.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.4
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• pp.509-515
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• 2010

In this paper, the mechanism that can walk efficiently in wet land or sand area is proposed. A vision camera is attached to the mechanism, which makes a kind of biologically inspired robot for coast guard. This visionary information enables the biologically inspired robot to react in peripheral environment by a soft-computing algorithm. In addition, the biologically inspired robot can achieve the mission appointed by a programmer connecting with outside, based on RF and Blue-tooth communication module. Therefore, the purpose of this research is the implementation of the biologically inspired robot that can operate most adaptively in sand and wet surface based on Theo Jansen mechanism.

• International Journal of Industrial Entomology and Biomaterials
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• v.1 no.2
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• pp.91-93
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• 2000

Insects have many excellent features and functions in their small bodies, such as hexapod walking, flapping flight, vision systems, sensory hairs, etc, and those characteristics can be thought as good models for many types of robots. Insects also will be good models far micro-machines because of its size. Insect behavior consists of simple reflex acts and programmed behavior, Some robots were made in order to clarify the emergent mechanism of insect behavior, Through some experiments it would be found that even if insect behavior consists of some simple action patterns, it looks intelligent through interactions its sensors and actuators with its complex environment. In the near futures small robots inspired by insects will be used in many fields of our life. I hope that insect-model based robots will play an active part in many fields and that they will make us happy.