• Journal of the Institute of Convergence Signal Processing
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• 제24권1호
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• pp.15-20
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• 2023

In general, maintaining an incorrect sitting posture for a long time is widely known to adversely affect the spine. Recently, several researchers have been interested in the causal relationship between incorrect sitting posture and spinal diseases, and have been studying methods to precisely measure changes in sitting or standing posture to prevent spinal diseases. In previous studies, we have developed a sensor device capable of measuring real-time posture change, applied a momentum calculation algorithm to improve the accuracy of real-time posture change measurement, and verified the accuracy of the postural change measurement sensor. In this study, we developed a posture measurement and analysis device that considers changes in the center of body pressure through the developed sitting pressure measurement, and it confirmed the sensor as an auxiliary tool to increase the accuracy of posture correction training with improving the user's visual feedback.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제13권8호
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• pp.3628-3633
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• 2012

This paper proposes a model of the real time monitoring system based on Ubiquitous Sensor Network (USN) for the detection and prediction of landslides. For this purpose, the real time monitoring system with tilting sensor and USN was set up and the performance was conducted. The performance was accomplished by conducting both field examinations and the experimental evaluation of the monitoring system. The results of this study show that the angle $0^{\circ}$, $-10^{\circ}$, $-20^{\circ}$ and $0{\sim}-30^{\circ}$ of sensor position detected by the sensor module coincide with the data measured from USN monitoring system by giving a sampling time 100[msec]. Consequently, the proposed model of the real time monitoring system with tilting sensor based on USN will be widely used as a monitoring system in the exposure to dangerous landslide regions.

• Journal of Biomedical Engineering Research
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• 제41권2호
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• pp.84-93
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• 2020

Despite of a lot of studies about proprioception tests, there are little study results to investigate the relationship between the functional movement and proprioception level. In this study, we tried to perform quantitative analysis for the effect of ankle joint proprioception level on the one leg standing postural control ability. Nine healthy people volunteered for this study. Force and position aspects of proprioception were evaluated using the electromyography system (EMG) and mobile clinometer application, respectively. The center of pressure (COP) trajectories, measured by a pressure mat sensor, were used for quantitative analysis of balance for each subject. We computed indices and errors of force and position aspects of proprioception from the EMG and ankle angle. Mean velocity of total and anterior-posterior direction (Vm and Vm_ap), root mean squared distance in anterior-posterior direction (RDap), travel length (L), and area (A) of COP trajectories were also calculated as indices of postural control ability of subjects. Two aspects of proprioception showed the low correlation from each other as previous studies. However, the EMG error of gastrocnemius lateral activation showed a high correlation coefficient with COP variables such as Vm (ρ=0.817, p=0.007), Vm_ap (ρ=0.883, p=0.002), RDap (ρ=0.854, p=0.003), L (ρ=0.817, 0.007) and A (ρ=0.700, p=0.036). Within our knowledge, this is almost the first study that investigated the relationship between proprioception level and functional movement. These study results could support that the ankle joint proprioception facilitation exercise would have positive effects on functional balance rehabilitation interventions.

• Korean Journal of Remote Sensing
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• 제34권6_1호
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• pp.941-951
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• 2018

Utilization and demand of UAV (unmanned aerial vehicle) for the generation of 3D city model are increasing. In this study, we performed an experiment to adjustment position/orientation of UAV with incomplete attitude information and to extract point cloud data. In order to correct the attitude of the UAV, the rotation angle was calculated by using the continuous position information of UAV movements. Based on this, the corrected position/orientation information was obtained by applying IBA (Incremental Bundle Adjustment) based on photogrammetry. Each pair was transformed into an epipolar image, and the MDR (Multi-Dimensional Relaxation) technique was applied to obtain high precision DSM. Each extracted pair is aggregated and output in the form of a single point cloud or DSM. Using the DJI inspire1 and Phantom4 images, we can confirm that the point cloud can be extracted which expresses the railing of the building clearly. In the future, research will be conducted on improving the matching performance and establishing sensor models of oblique images. After that, we will continue the image processing technology for the generation of the 3D city model through the study of the extraction of 3D cloud It should be developed.

• Journal of Korea Multimedia Society
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• 제19권2호
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• pp.240-251
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• 2016

This paper presents a real-time indoor location and pose estimation method that utilizes simple artificial markers and image analysis techniques for the purpose of warehouse automation. The conventional indoor localization methods cannot work robustly in warehouses where severe environmental changes usually occur due to the movement of stocked goods. To overcome this problem, the proposed framework places artificial markers having different interior pattern on the predefined position of the warehouse floor. The proposed algorithm obtains marker candidate regions from a captured image by a simple binarization and labeling procedure. Then it extracts maker interior pattern information from each candidate region in order to decide whether the candidate region is a true marker or not. The extracted interior pattern information and the outer boundary of the marker are used to estimate location and heading angle of the localization system. Experimental results show that the proposed localization method can provide high performance which is almost equivalent to that of the conventional method using an expensive LIDAR sensor and AMCL algorithm.

• Journal of Institute of Control, Robotics and Systems
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• 제5권5호
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• pp.550-557
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• 1999

This paper describes a road-following controller using the proposed neural network for autonomous vehicle. Road-following with visual sensor like camera requires intelligent control algorithm because analysis of relation from road image to steering control is complex. The proposed neural network, relative similarity modular network(RSMN), is composed of some learning networks and a partitioniing network. The partitioning network divides input space into multiple sections by similarity of input data. Because divided section has simlar input patterns, RSMN can learn nonlinear relation such as road-following with visual control easily. Visual control uses two criteria on road image from camera; one is position of vanishing point of road, the other is slope of vanishing line of road. The controller using neural network has input of two criteria and output of steering angle. To confirm performance of the proposed neural network controller, a software is developed to simulate vehicle dynamics, camera image generation, visual control, and road-following. Also, prototype autonomous electric vehicle is developed, and usefulness of the controller is verified by physical driving test.

• Journal of Institute of Control, Robotics and Systems
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• 제13권2호
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• pp.140-146
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• 2007

This paper demonstrates the development of a mobile robot for patrol. We fuse differential GPS, angle sensor and odometry data using the framework of extended Kalman filter to localize a mobile robot in outdoor environments. An important feature of road environment is the existence of curbs. So, we also propose an algorithm to find out the position of curbs from laser range finder data using Hough transform. The mobile robot builds the map of the curbs of roads and the map is used fur tracking and localization. The patrol robot system consists of a mobile robot and a control station. The mobile robot sends the image data from a camera to the control station. The remote control station receives and displays the image data. Also, the patrol robot system can be used in two modes, teleoperated or autonomous. In teleoperated mode, the teleoperator commands the mobile robot based on the image data. On the other hand, in autonomous mode, the mobile robot has to autonomously track the predefined waypoints. So, we have designed a path tracking controller to track the path. We have been able to confirm that the proposed algorithms show proper performances in outdoor environment through experiments in the road.

• Journal of the Korean Society of Manufacturing Process Engineers
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• 제12권1호
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• pp.70-76
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• 2013

Recently, the performance and function of electrical and electronic system in automotive vehicles is developing at a rapid rate with the advancement of IT technologies. Combined together with micro-controller and sensor technologies, the Vehicle Smart System (VSS) being developed to improve driver's convenience and comfort has been employed to a variety of applications. In addition to the convenience system, the Auto-parking Assistance System (AAS) that is now attracting a new attention has been already applied to some vehicles, but it is currently limited to luxury car models only. In this paper, we present a fuzzy controller that enables autonomous parking assistance without the AAS. The controller can perform the assistance with information provided from moving status, current position and steering angle as one is able to park a car based on his/her experience and knowledge for driving and parking. We have evaluated its performance of the proposed controller by simulation and tested the excellence of the controller by building a model vehicle embedded with the micro-controllers.

• Journal of Sensor Science and Technology
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• 제14권4호
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• pp.278-285
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• 2005

This paper describes techniques of camera calibration and artificial landmarks detection for the automatic charging of a mobile robot, equipped with a fish-eye camera in the direction of its operation for movement or surveillance purposes. For its identification from the surrounding environments, three landmarks employed with infrared LEDs, were installed at the charging station. When the robot reaches a certain point, a signal is sent to the LEDs for activation, which allows the robot to easily detect the landmarks using its vision camera. To eliminate the effects of the outside light interference during the process, a difference image was generated by comparing the two images taken when the LEDs are on and off respectively. A fish-eye lens was used for the vision camera of the robot but the wide-angle lens resulted in a significant image distortion. The radial lens distortion was corrected after linear perspective projection transformation based on the pin-hole model. In the experiment, the designed system showed sensing accuracy of ${\pm}10$ mm in position and ${\pm}1^{\circ}$ in orientation at the distance of 550 mm.

• Journal of the Korean Institute of Intelligent Systems
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• 제23권2호
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• pp.100-106
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• 2013

This paper presents design and control of an 'Omni-directional Cleaning Robot (OdCR)' which employs omni-wheels at three edges of its triangular configuration. Those omni-wheels enable the OdCR to move in any directions so that lateral movement is possible. For OdCR to be localized, a StarGazer sensor is used to provide accurate position and heading angle based on landmarks on the ceiling. In addition to that, ultrasonic sensors are installed to detect obstacles around OdCR's way. Experimental studies are conducted to test the functionality of the system.