• Journal of Institute of Control, Robotics and Systems
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• v.18 no.1
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• pp.54-61
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• 2012

In this paper, the pose estimation method for the satellite GTB (Ground Test Bed) using vision/MEMS IMU (Inertial Measurement Unit) integrated system is presented. The GTB for verifying a satellite system on the ground is similar to the mobile robot having thrusters and a reaction wheel as actuators and floating on the floor by compressed air. The EKF (Extended Kalman Filter) is also used for fusion of MEMS IMU and vision system that consists of a single camera and infrared LEDs that is ceiling landmarks. The fusion filter generally utilizes the position of feature points from the image as measurement. However, this method can cause position error due to the bias of MEMS IMU when the camera image is not obtained if the bias is not properly estimated through the filter. Therefore, it is proposed that the fusion method which uses the position of feature points and the velocity of the camera determined from optical flow of feature points. It is verified by experiments that the performance of the proposed method is robust to the bias of IMU compared to the method that uses only the position of feature points.

• The Journal of Korea Robotics Society
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• v.14 no.1
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• pp.65-73
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• 2019

In this paper, we propose an algorithm that estimates the location of lunar rover using IMU and vision system instead of the dead-reckoning method using IMU and encoder, which is difficult to estimate the exact distance due to the accumulated error and slip. First, in the lunar environment, magnetic fields are not uniform, unlike the Earth, so only acceleration and gyro sensor data were used for the localization. These data were applied to extended kalman filter to estimate Roll, Pitch, Yaw Euler angles of the exploration rover. Also, the lunar module has special color which can not be seen in the lunar environment. Therefore, the lunar module were correctly recognized by applying the HSV color filter to the stereo image taken by lunar rover. Then, the distance between the exploration rover and the lunar module was estimated through SIFT feature point matching algorithm and geometry. Finally, the estimated Euler angles and distances were used to estimate the current position of the rover from the lunar module. The performance of the proposed algorithm was been compared to the conventional algorithm to show the superiority of the proposed algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.4
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• pp.731-736
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• 2023

Walking is a periodic motion that contains specific phases and is a basic movement method for humans. Through gait analysis, various musculoskeletal health conditions can be identified. In this study, we propose a calf wearable sensor system that can perform gait analysis without space limitations. Using a ToF(: Time-of-Flight) sensor that measures distance and an IMU(: Inertial Measurement Unit) sensor that measures inclination the heel trajectory of walking was derived by proposed method. In case of abnormal gait with risk of fall, gait is evaluated by analyzing the change pattern of the heel trajectory.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.26-34
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• 2008

The information of traversability and path planning is essential for UGV(Unmanned Ground Vehicle) navigation. Such information can be obtained by analyzing 3D terrain. In this paper, we present the method of 3D terrain modeling with color information from a camera, precise distance information from a 2D Laser Range Finder(LRF) and wheel encoder information from mobile robot with less data. And also we present the method of 3B terrain modeling with the information from GPS/IMU and 2D LRF with less data. To fuse the color information from camera and distance information from 2D LRF, we obtain extrinsic parameters between a camera and LRF using planar pattern. We set up such a fused system on a mobile robot and make an experiment on indoor environment. And we make an experiment on outdoor environment to reconstruction 3D terrain with 2D LRF and GPS/IMU(Inertial Measurement Unit). The obtained 3D terrain model is based on points and requires large amount of data. To reduce the amount of data, we use cubic grid-based model instead of point-based model.

• Journal of Sensor Science and Technology
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• v.28 no.6
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• pp.345-354
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• 2019

The 3D position of pedestrians is a physical quantity used in various fields, such as automotive navigation and augmented reality. An inertial navigation system (INS) based pedestrian dead reckoning (PDR), hereafter INS-PDR, estimates the relative position of pedestrians using an inertial measurement unit (IMU). Since an INS-PDR integrates the accelerometer signal twice, cumulative errors occur and cause a rapid increase in drifts. Various correction methods have been proposed to reduce drifts. For example, one of the most commonly applied correction method is the zero velocity update (ZUPT). This study investigated the characteristics of the existing INS-PDR methods based on shoe-mounted IMU and compared the estimation performances under various conditions. Four methods were chosen: (i) altitude correction (AC); (ii) step length correction (SLC); (iii) advanced heuristic drift elimination (AHDE); and (iv) magnetometer-based heading correction (MHC). Experimental results reveal that each of the correction methods shows condition-sensitive performance, that is, each method performs better under the test conditions for which the method was developed than it does under other conditions. Nevertheless, AC and AHDE performed better than the SLC and MHC overall. The AC and AHDE methods were complementary to each other, and a combination of the two methods yields better estimation performance.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.8
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• pp.133-140
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• 2002

In this paper, the structure of integrated navigation computer for experiment is proposed. It is designed for considering the real time processing and data storage capacity. It will be used in missile, aircraft, submarine system and experimental vehicle. The I/O device supports IMU, GPS, odometer, altimeter, depth sensor, inclinometer etc. And the main storage device uses the tape device. That can improve the system stability. Therefore it can be used in a high dynamic or shock environment. The embedded linux is used as an Operating System. For the real time capability, sensor data processing and algorithm processing units are seperated. The time synchronization is referenced by IMU data.

• Journal of Broadcast Engineering
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• v.21 no.2
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• pp.200-209
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• 2016

This paper proposes a non-uniform de-blur algorithm using IMU sensor and a long/short exposure-time image pair to efficiently remove the blur phenomenon. Conventional blur kernel estimation algorithms using sensor information do not provide acceptable performance due to limitation of sensor performance. In order to overcome such a limitation, we present a kernel refinement step based on images having different exposure times which improves accuracy of the estimated kernel. Also, in order to figure out the phenomenon that conventional non-uniform de-blur algorithms suffer from severe degradation of visual quality in case of large blur kernels, this paper a homography-based residual de-convolution which can minimize quality degradation such as ringing artifacts during de-convolution. Experimental results show that the proposed algorithm is superior to the state-of-the-art methods in terms of subjective as well as objective visual quality.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.661-662
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• 2008

• Journal of Biomedical Engineering Research
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• v.40 no.6
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• pp.223-229
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• 2019

The number of knee-related disease patients and knee joint surgeries is steadily increasing every year, and for knee rehabilitation training for these knee joint patients, it is necessary to strengthen the muscle of vastus medialis and quadriceps femoris. However, because of the cost and time-consuming difficulties of receiving regular hospital treatment in the course of knee rehabilitation, we developed knee exoskeleton using rapid prototype for knee rehabilitation with feedback from the electromyogram (EMG) and inertia motion unit (IMU) sensor. The modules was built on the basis of EMG and an IMU sensor applied complementary filter, measuring muscle activity in the vastus medialis and the range of joint operation of the knee, and then performing the game based on this measurement. The IMU sensor performed up to 97.2% accuracy in experiments with ten subjects. The functional game contents consisted of an exergaming platform based on EMG and IMU for the real-time monitoring and performance assessment of personalized isometric and isotonic exercises. This study combined EMG and IMU-based functional game with knee rehabilitation training to enable voluntary rehabilitation training by providing immediate feedback to patients through biometric information, thereby enhancing muscle strength efficiency of rehabilitation.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.361-369
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• 2006

This study conducted an initialization test to decide dynamic position using AHRS IMU sensor, and derived attitude correction angles of vehicles against time through regression analysis. It was also found that the heading angle was stabilized with variation less than 1°after 60 seconds. Using these angles, this study carried out an experiment on the determination of dynamic position for each system in the open sky and in a semi-open sky. According to the results, in the open sky, DGPS alone systems were excellent in accuracy but poor in data acquisition, so the moving distance was around 12m. In DGPS/IMU combined system, accuracy and data acquisition were satisfactory and the moving distance was around 0.3m. In a semi-open sky, DGPS alone systems were excellent in accuracy in order of DGPS < FIMU < DGPS/IMU according to average and standard errors obtained with exclusion of places where data were not be obtained. The moving distance was the same as that in the open sky. For DGPS, when places where data were not obtainable were divided into Several block and they were compared, the maximum deviation from the trajectory was up to 41.5m in DGPS alone system, but it was less than 2.2m and average and standard errors were significantly improved in the combined system. When the navigation system was applied to surveys and the result was compared with position error 0.2mm under the guideline for digital map, it was possible to work on maps on a scale of up to 1 : 1,000.