• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.226-232
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• 2016

This paper describes the design of a smart three-axis force sensor for measuring forces Fx, Fy and Fz. The smart three-axis force sensor is composed of a three-axis force sensor, a force-measuring device, housing and a cover, where the three-axis force sensor and the force-measuring device are inside the housing and the cover. The measuring device measures forces Fx, Fy and Fz from the three-axis force sensor, and calculates the resultant force using the measured forces, and then sends the resultant force and forces to a PC or other controller using RS-485 communication. The repeatability error and the non-linearity error of the smart three-axis force sensor are less than 0.03%, and the interference error of the sensor is less than 0.87%. It is thought that the sensor can be used for measuring forces in a robot, automatic systems and so on.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.288-295
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• 2022

This study shows a system identification method of a balancing loading device for a stair climbing delivery robot. The balancing loading device is designed as a 2-axes gimbal structure and is interpreted as two independent pendulum structures for simplifying. The loading device's properties such as mass, moment of inertia, and position of the center of gravity are changeable for luggage. The system identification process of the loading device is required, and the controller should be optimized for the system in real-time. In this study, the system identification method is based on least squares method to estimate the unknown parameters of the loading device's dynamic equation. It estimates the unknown parameters by calculating them that minimize the error function between the real system's motion and the estimated system's motion. This study improves the accuracy of parameter estimation using a null space solution. The null space solution can produce the correct parameters by adjusting the parameter's relative sizes. The proposed system identification method is verified by the simulation to determine how close the estimated unknown parameters are to the real parameters.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.9
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• pp.825-837
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• 2017

This paper describes a novel type of a walking rehabilitation robot that applies robot technologies to crutches used by patients with walking difficulties in the lower body. The primary features of the developed robot are divided into three parts. First, the developed robot is worn on the patient's chest, as opposed to the conventional elbow crutch that is attached to the forearm; hence, it can effectively disperse the patient's weight throughout the width of the chest, and eliminate the concentrated load at the elbow. Furthermore, it allows free arm motion during walking. Second, the developed robot can recognize the walking intention of the patient from the magnitude and direction of the ground reactive forces. This is done using three-axis force sensors attached to the feet of the robot. Third, the robot can perform a stair walking function, which can change vertical movement trajectories in order to step up and down a single stair according to the floor height. Consequently, we experimentally showed that the developed robot can effectively perform walking rehabilitation assistance by perceiving the walking intention of the patient. Moreover we quantitatively verified muscle power assistance by measuring the electromyography (EMG) signals of the muscles of the lower limb.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.246-252
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• 2020

Safety accidents have been reported due to falling accumulated snow from cables of cable-supported bridges. In addition to the direct damage caused by falling snow, secondary damage, such as traffic accidents, can occur. Various methods have been proposed to prevent these accidents, but there are still problems in safety and practicality. In this study, a cable robot type was selected as one of the active methods for removing accumulated snow on cables. An attempt was made to increase the climbing ability of the robot to improve the efficiency of snow removal. In addition, the available range of cable diameter for the robot can be adjusted flexibly to be applied to cables used in the field. A high-resolution camera was also installed to check the surface condition of the cable in real time to increase the utility, and be used as a cable inspection robot. A three-axis accelerometer and a tension conversion algorithm were added to measure the tension force of cables. To verify the performance, indoor and field experiments were conducted, and future improvements for the inspection robot were proposed.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.4
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• pp.256-262
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• 2004

A key component of an autonomous mobile robot is to localize itself and build a map of the environment simultaneously. In this paper, we propose a vision-based localization and mapping algorithm of mobile robot using fisheye lens. To acquire high-level features with scale invariance, a camera with fisheye lens facing toward to ceiling is attached to the robot. These features are used in mP building and localization. As a preprocessing, input image from fisheye lens is calibrated to remove radial distortion and then labeling and convex hull techniques are used to segment ceiling and wall region for the calibrated image. At the initial map building process, features we calculated for each segmented region and stored in map database. Features are continuously calculated for sequential input images and matched to the map. n some features are not matched, those features are added to the map. This map matching and updating process is continued until map building process is finished, Localization is used in map building process and searching the location of the robot on the map. The calculated features at the position of the robot are matched to the existing map to estimate the real position of the robot, and map building database is updated at the same time. By the proposed method, the elapsed time for map building is within 2 minutes for 50㎡ region, the positioning accuracy is ±13cm and the error about the positioning angle of the robot is ±3 degree for localization.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.490-493
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• 2003

This paper describes the development of a small 6-axis force/moment sensor for robot's finger, which measures forces Fx. Fy, Fz, and moments Mx, My, Mz simultaneously. In order to safely grasp an unknown object using the robot's gripper, and accurately perceive the position of it in the gripper, it should measure the force in the gripping direction, the force in the gravity direction and the moments each direction. and perform the control using the measured forces and moments. Thus, the robot's gripper should be composed of 6-axis force/moment sensor that can measure forces Fx, Fy, Fz, and moments Mx, My. Mz simultaneously. In this paper, the small 6-axis force/moment sensor for measuring forces Fx, Fy, Fz, and moments Mx, My, Mz simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test of made sensor was performed, and the result shows that interference errors or the developed sensor are less than 3%. Thus, the developed small 6-axis force/moment sensor may be used for robot's gripper.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.2
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• pp.129-136
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• 2014

Target-tracking systems are important for carrying out effective surveillance missions using mobile surveillance robots. In this paper, we propose a target-tracking algorithm using camera image data for a three-axis mobile surveillance robot and carry out an actual hardware test for verifying the proposed algorithm. The heading direction vector of a camera system is deduced from the position error between the viewfinder center and the object center in a camera image. The position error is obtained using the CAMShift(Continuously Adaptive Mean Shift) algorithm, an image processing technique. The performance test of an actual three-axis mobile surveillance robot was carried out for verifying the proposed target-tracking algorithm in a real environment.

• Radiation Oncology Journal
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• v.26 no.4
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• pp.263-270
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• 2008

Purpose: This study aimed to quantitatively measure the movement of tumors in real-time and evaluate the treatment accuracy, during the treatment of a liver tumor patient, who underwent radiosurgery with a Synchrony Respiratory motion tracking system of a robot CyberKnife. Materials and Methods: The study subjects included 24 liver tumor patients who underwent CyberKnife treatment, which included 64 times of treatment with the Synchrony Respiratory motion tracking system ($Synchrony^{TM}$). The treatment involved inserting 4 to 6 acupuncture needles into the vicinity of the liver tumor in all the patients using ultrasonography as a guide. A treatment plan was set up using the CT images for treatment planning uses. The position of the acupuncture needle was identified for every treatment time by Digitally Reconstructed Radiography (DRR) prepared at the time of treatment planning and X-ray images photographed in real-time. Subsequent results were stored through a Motion Tracking System (MTS) using the Mtsmain.log treatment file. In this way, movement of the tumor was measured. Besides, the accuracy of radiosurgery using CyberKnife was evaluated by the correlation errors between the real-time positions of the acupuncture needles and the predicted coordinates. Results: The maximum and the average translational movement of the liver tumor were measured 23.5 mm and $13.9{\pm}5.5\;mm$, respectively from the superior to the inferior direction, 3.9 mm and $1.9{\pm}0.9mm$, respectively from left to right, and 8.3 mm and $4.9{\pm}1.9\;mm$, respectively from the anterior to the posterior direction. The maximum and the average rotational movement of the liver tumor were measured to be $3.3^{\circ}$ and $2.6{\pm}1.3^{\circ}$, respectively for X (Left-Right) axis rotation, $4.8^{\circ}$ and $2.3{\pm}1.0^{\circ}$, respectively for Y (Crania-Caudal) axis rotation, $3.9^{\circ}$ and $2.8{\pm}1.1^{\circ}$, respectively for Z (Anterior-Posterior) axis rotation. In addition, the average correlation error, which represents the treatment's accuracy was $1.1{\pm}0.7\;mm$. Conclusion: In this study real-time movement of a liver tumor during the radiosurgery could be verified quantitatively and the accuracy of the radiosurgery with the Synchrony Respiratory motion tracking system of robot could be evaluated. On this basis, the decision of treatment volume in radiosurgery or conventional radiotherapy and useful information on the movement of liver tumor are supposed to be provided.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.632-637
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• 2012

This paper introduces a simple and efficient calibration method for three-axis accelerometers and three-axis gyroscopes using three-axis motion rate table. Usually, the performance of low cost MEMS-based inertial sensors is affected by scale and bias errors significantly. The calibration of these errors is a bothersome problem, but the previous calibration methods cannot propose simple and efficient method to calibrate the errors of three-axis inertial sensors. This paper introduces a new simple and efficient method for the calibration of accelerometer and gyroscope. By using a three-axis motion rate table, this method can calibrate the accelerometer and gyroscope simultaneously and simply. Experimental results confirm the performance of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.9
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• pp.876-882
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• 2010

Stroke patients can't use their hands because of the paralysis their fingers. Their fingers are recovered by rehabilitating training, and the rehabilitating extent can be judged by measuring the pressing force to be contacted with two fingers (thumb and first finger, thumb and middle finger, thumb and ring finger, thumb and little finger). But, at present, the grasping finger force of two-finger can't be accurately measured, because there is not a proper finger-force measuring system. Therefore, doctors can't correctly judge the rehabilitating extent. So, the finger-force measuring system which can measure the grasping force of two-finger must be developed. In this paper, the finger-force measuring system with a three-axis force sensor which can measure the pressing force was developed. The three-axis force sensor was designed and fabricated, and the force measuring device was designed and manufactured using DSP (Digital Signal Processing). Also, the grasping force test of men was performed using the developed finger-force measuring system, it was confirmed that the grasping forces of men were different according to grasping methods.