• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.663-666
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• 2003

This paper presents a speed controller method based on the disturbance torque observer of high performance brushless DC (BLDC) motor drives. In case of the speed control of robot arms and tracking applications with lower stiffness, we cannot design the speed controller gain to be very large from tile viewpoint of the system stability. Thus, the feedforward compensator using disturbance torque observer was proposed. This method can improve the speed characteristic without increasing the speed controller gain. The enhanced speed control performance can be achieved and the speed response against the disturbance torque can be Improved for high-performance BLDC motor drive systems in which the bandwidth of tile speed controller cannot be made large enough. Consequently, speed control for high-performance BLDC motor drives become improved. The simulation results for BLDC motor drive systems confirm the validity of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.2
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Journal of Sensor Science and Technology
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• v.13 no.3
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• pp.188-194
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• 2004

With a remarkable advance in CMOS (complimentary metal-oxide-semiconductor) process technology, a variety of vision sensors with signal processing circuits for complicated functions are actively being developed. Especially, as the principles of signal processing in human retina have been revealed, a series of vision chips imitating human retina have been reported. Human retina is able to detect the edge and motion of an object effectively. The edge detection among the several functions of the retina is accomplished by the cells called photoreceptor, horizontal cell and bipolar cell. We designed a CMOS vision chip by modeling cells of the retina as hardwares involved in edge and motion detection. The designed vision chip was fabricated using $0.6{\mu}m$ CMOS process and the characteristics were measured. Having reliable output characteristics, this chip can be used at the input stage for many applications, like targe tracking system, fingerprint recognition system, human-friendly robot system and etc.

• The Journal of Korea Robotics Society
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• v.6 no.3
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• pp.210-219
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• 2011

This paper studies how to combine devices such as monocular/stereo cameras, motors for panning/tilting, fisheye lens and convex mirrors, in order to solve vision-based robotic problems. To overcome the well-known trade-offs between optical properties, we present two mixed versions of the new systems. The first system is the robot photographer with a conventional pan/tilt perspective camera and fisheye lens. The second system is the omnidirectional detector for a complete 360-degree field-of-view surveillance system. We build an original device that combines a stereo-catadioptric camera and a pan/tilt stereo-perspective camera, and also apply it in the real environment. Compared to the previous systems, we show benefits of two proposed systems in aspects of maintaining both high-speed and high resolution with collaborative moving cameras and having enormous search space with hybrid configuration. The experimental results are provided to show the effectiveness of the mixing collaborative and hybrid systems.

• Journal of Auto-vehicle Safety Association
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• v.12 no.2
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• pp.33-39
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• 2020

This paper presents an Around View Monitoring (AVM) stop-line detection based longitudinal position correction algorithm for automated driving on urban roads. Poor positioning accuracy of low-cost GPS has many problems for precise path tracking. Therefore, this study aims to improve the longitudinal positioning accuracy of low-cost GPS. The algorithm has three main processes. The first process is a stop-line detection. In this process, the stop-line is detected using Hough Transform from the AVM camera. The second process is a map matching. In the map matching process, to find the corrected vehicle position, the detected line is matched to the stop-line of the HD map using the Iterative Closest Point (ICP) method. Third, longitudinal position of low-cost GPS is updated using a corrected vehicle position with Kalman Filter. The proposed algorithm is implemented in the Robot Operating System (ROS) environment and verified on the actual urban road driving data. Compared to low-cost GPS only, Test results show the longitudinal localization performance was improved.

• Physical Therapy Korea
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• v.27 no.1
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• pp.11-18
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• 2020

Background: As technology has progressed, various robot-assisted devices have been developed to reduce therapists' labor and assist in therapy. However, due to their many limitations, it is more practical to use traditional mechanical devices. The grahamizer is one such traditional mechanical device used clinically to rehabilitate the upper extremities. No study has yet established the efficacy of the grahamizer in individuals with stroke. Objects: This study investigated the immediate change in arm reaching after the use of a grahamizer. Methods: Twenty-two stroke survivors participated in this study (11 males and 11 females). The reaching of the more-affected arm was measured three times using the three-dimentional electromagnetic motion tracking system "trakSTAR". After the first measurement, the subjects performed 500 rotatory arm exercises using the grahamizer. To assess the grahamizer's effect, the subjects were remeasured in the same way. Results: There were significant increases in the reaching distance (p < 0.05) and movement smoothness (p < 0.05) of the more-affected arm after using the grahamizer. Conclusion: Our study confirms that using the grahamizer is beneficial in the rehabilitation for improving movement of the more-affected arm in stroke survivors.

• Journal of Power System Engineering
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• v.21 no.4
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• pp.77-83
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• 2017

The aim of this paper is to solve the chattering and delayed response problems caused by gear backlash. In the gear mechanism based systems, for example, in robot systems, the actuators provide the reduction gear with motors to transfer effectively electric power to mechanical power. Therefore, the gear backlash exists and is an unavoidable fact which makes many undesirable problems. In this paper, the authors try to make a solution for this issue and, introduce several control methods which are PID only, PID with Smith predictor and super-twisting algorithm based SMC(sliding mode control). Each control method is applied to the real plant in which strong backlash is included. By comparison results, it is clear that SMC gives the best control performance with little backlash effects. Also, the usefulness and effectiveness of proposed control method is verified by experiment.

• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1647-1658
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• 2016

RGB+D database has been widely used in object recognition, object tracking, robot control, to name a few. While rapid advance of active depth sensing technologies allows for the widespread of indoor RGB+D databases, there are only few outdoor RGB+D databases largely due to an inherent limitation of active depth cameras. In this paper, we propose a novel method used to build outdoor RGB+D databases. Instead of using active depth cameras such as Kinect or LIDAR, we acquire a pair of stereo image using high-resolution stereo camera and then obtain a depth map by applying stereo matching algorithm. To deal with estimation errors that inevitably exist in the depth map obtained from stereo matching methods, we develop an approach that estimates confidence of depth maps based on unsupervised learning. Unlike existing confidence estimation approaches, we explicitly consider a spatial correlation that may exist in the confidence map. Specifically, we focus on refining confidence feature with the assumption that the confidence feature and resultant confidence map are smoothly-varying in spatial domain and are highly correlated to each other. Experimental result shows that the proposed method outperforms existing confidence measure based approaches in various benchmark dataset.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.291-296
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• 2008

This paper presents the dodecagon-based Q-leaning and SVM algorithm for object search with multiple robots. We organized an experimental environment with several mobile robots, obstacles, and an object. Then we sent the robots to a hallway, where some obstacles were tying about, to search for a hidden object. In experiment, we used four different control methods: a random search, a fusion model with Distance-based action making(DBAM) and Area-based action making(ABAM) process to determine the next action of the robots, and hexagon-based Q-learning and dodecagon-based Q-learning and SVM to enhance the fusion model with Distance-based action making(DBAM) and Area-based action making(ABAM) process.

• Progress in Medical Physics
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• v.29 no.4
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• pp.115-122
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• 2018

Although the current internationally recommended standard for the use factor (U) applied to CyberKnife is 0.05 (5%), the CyberKnife shielding standard is applied more stringently. This study, based on clinical data, was aimed at examining the appropriateness of existing shielding guidelines. Sixty patients treated with G4 CyberKnife were selected. The patients were divided into two groups, according to whether they underwent skull or spine tracking. Based on the results, the use factors for each wall ranged from 0.028 (2.8%) to 0.031 (3.1%) for the intracranial treatment and 0.020 (2.0%) to 0.022 (2.2%) for the body treatment. Excessive barrier thickness resulted in inefficient use of space and higher cost to the institutions. Furthermore, because the use factor is influenced by the position of the robot, the use factor determined based on the clinical data of this study would facilitate more reasonable treatment room design.