• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.955-959
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• 2009

In this paper, we propose a novel method for analyzing human interactions based on the walking trajectories of human subjects. Our principal assumption is that an interaction episode is composed of meaningful smaller unit interactions, which we call 'sub-interactions.' The whole interactions are represented by an ordered concatenation or a network of sub-interaction models. From the experiments, we could confirm the effectiveness and robustness of the proposed method by analyzing the inner workings of an interaction network and comparing the performance with other previous approaches.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2397-2399
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• 2004

This paper deals with the messages scheduling of a CAN (Controller Area Network), based on the distributed control scheme to integrate actuators and sensors in a humanoid robot. In order to supply the distributed processing for a humanoid robot, each control unit should have the efficient control method, fast calculation and valid data exchange. The preliminary study has concluded that the performance of CAN is better and easier to implement than other network such as FIP (Factory Instrumentation Protocol), VAN (Vehicle Area Network), etc. Since humanoid robot has to treat the significant control signals from many actuators and sensors, the communication time limitation could be critical according to the transmission speed and data length of CAN specification. In this paper, the CAN message scheduling in humanoid robot was suggested under the presence of Jitter in the message group, the existence of high load of messages over the network and the presence of transmission errors. In addition, the response time under the worst case is compared with the simulation by using the simulation algorithm. As a result, the suggested messages scheduling can guarantee our CAN limitation, and utilized to generate the walking patterns for the humanoid.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.80-80
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• 2000

The GPS can provide accurate position information on the earth. But GPS receiver can't give position information inside buildings. DR(Dead-Reckoning) or INS(Inertial Navigation System) gives position information continuously indoors as well as outdoors, because they do not depend on the external navigation information. But in general, the inertial sensors severely suffer from their drift errors, the error of these navigation system increases with time. GPS and DR sensors can be integrated together with Kalman filter to overcome these problems. In this paper, we developed a personal navigation system which can be carried by person, using GPS and electronic pedometer. The person's footstep is detected by an accelerometer installed in vertical direction and the direction of movement is sensed by gyroscope and magnetic compass. In this case the step size is varying with person and changing with circumstance, so determining step size is the problem. In order to calculate the step size of detected footstep, the neural network method is used. The teaming pattern of the neural network is determined by human walking pattern data provided by 3-axis accelerometer and gyroscope. We can calculate person's location with displacement and heading from this information. And this neural network method that calculates step size gives more improved position information better than fixed step size.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.190-198
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• 2020

The development in smartphone technology has brought convenience to the life of the mankind, but an excessive use of smartphones sometimes causes various accidents. This research tried to propose an application service 'Smombie Safe Go' UI(User Interface) that allows the prevention of such accident while using smartphones when walking. For this, after research and user observations, produced walker journey maps and derived necessary main functions needed for safety, and the result showed that transparent interface, obstacle location alert, warning of dangers functions were necessary. To make the contents of the service more detailed, hazardous situations faced during smartphone use when walking were classified into 3 situations : 1. Obstacle appearing in front, 2. traffic lights on crosswalks 3. No traffic lights on crosswalks. Scenarios by hazardous situation were written, and the flow and UI of the app service that warns its users in each situation of hazards were designed. it is predicted that 'Smombie Safe Go' may be possible to be utilized as an app service that provides a safe walking experience for not only regular pedestrians but also the blind population.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.8
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• pp.915-920
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• 2015

Recently, many companies try to offer various services using drones. Especially, the drone delivery system is a good example. However, the drone delivery service has some problems since the heavy parcels flies over the people walking down streets, so many things must be considered such as dropping mails by collision of drones. To resolve the problem, in this paper, a inter-drone network communication will be used to design the topology and to simulate in the Opnet simulator for the performance evaluation. Additionally, the topology with random mobility of trajectory of drones is also designed and simulated for the result.

• Journal of Biomedical Engineering Research
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• v.28 no.1
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• pp.29-35
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• 2007

This study was designed to investigate the feasibility to utilize the electromyogram (EMG) for estimating the muscle torque. The muscle torque estimation plays an important role in functional electrical stimulation because electrical stimulation causes muscles to fatigue much faster than voluntary contraction, and the stimulation intensity should then be modified to keep the muscle torque within the desired range. We employed the neural network method which was trained using the major EMG parameters and the corresponding knee extensor torque measured and extracted during isometric contractions. The experimental results suggested that (1) our neural network algorithm and protocol was feasible to be adopted in a real-time feedback control of the stimulation intensity, (2) the training data needed to cover the entire range of the measured value, (3) different amplitudes and frequencies made little difference to the estimation quality, and (4) a single input to the neural network led to a better estimation rather than a combination of two or three. Since this study was done under a limited contraction condition, the results need more experiments under many different contraction conditions, such as during walking, for justification.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.141-156
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• 2010

In this paper, understanding there is a limitation with a comprehensive and network approach for the evaluation of existing vehicle and pedestrian environments, the authors focus on developing an integrated approach to assessing these environments. The network evaluation here means the assessment at a three-dimensional level that includes evaluation methods of lines/axes in a spatial concept as well as integration of evaluation indicators being used for vehicles and the walking environment. Grey System Theory (GST) was applied based on the theoretical background for network and comprehensive integrated evaluation, and the evaluation of the vehicle and pedestrian environment was performed by assigning target areas to walking preference zones. As a result of the comprehensive evaluation and analysis by GST, even if the service level is the same as the operating indicators (Highway Capacity Manual) of the vehicle and pedestrian environment, or relatively better, it was identified that the total score could be varied over Grey Category because the observed data are calculated after considering the weights between evaluation indicators by the range of Grey Category on the comprehensive evaluation. Considering comprehensively these points, although the indicators on the operation of roads are relatively good, in the event that the indicators on the safety of roads are bad, it was known that the scores over Grey Category also could be changed. The result is that this evaluation method can be used to evaluate the network concept per lane (per axis) as well as to diagnose the current state by type of urban street in the future.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.75-83
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• 2007

A model based approach of tracking the limbs of a walking human subject is proposed in this paper. The tracking process begins by building a data base composed of conditional probabilities of motions between the limbs of a walking subject. With a suitable amount of video footage from various human subjects included in the database, a probabilistic model characterizing the relationships between motions of limbs is developed. The motion tracking of a test subject begins with identifying and tracking limbs from the surveillance video image using the edge and silhouette detection methods. When occlusion occurs in any of the limbs being tracked, the approach uses the probabilistic motion model in conjunction with the minimum cost based edge and silhouette tracking model to determine the motion of the limb occluded in the image. The method has shown promising results of tracking occluded limbs in the validation tests.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4087-4094
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• 2010

The sensor data which is measured by Quadruped robot is utilized to recognize the physical environment or other information and to control the posture and walking of robot system. In order to control the robot precisely, high accuracy of sensor data is required, most of these sensors however, belongs to expensive and low-durable products. Moreover, these are exposed excessive load operation in a field condition if it is applied to field robot system. This issue becomes more serious one when the robot system is manufactured as a mass product. As in this context, this study suggests a virtual sensor technology to alternate or assist the main sensor system. This scheme is realized by using back-propagation algorithm of neural network theory, and the quality of estimated sensor data could be improved through the algorithmic and hardware based treatments. This study performs the various trial to identify the effective parameters which effect to the quality and reliability of estimated sensor data and tries to show the possibility of proposed methodology.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.12
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• pp.984-990
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• 2005

The aim of this paper is to investigate a control framework for mobile robots, operating in shared environment with humans. The Intelligent Space (iSpace) can sense the whole space and evaluate the situations in the space by distributing sensors. The mobile agents serve the inhabitants in the space utilizes the evaluated information by iSpace. The iSpace evaluates the situations in the space and learns the walking behavior of the inhabitants. The human intelligence manifests in the space as a behavior, as a response to the situation in the space. The iSpace learns the behavior and applies to mobile agent motion planning and control. This paper introduces the application of fuzzy-neural network to describe the obstacle avoidance behavior teamed from humans. Simulation results are introduced to demonstrate the efficiency of this method.