• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.253-264
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• 1999

Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.

• Journal of Computing Science and Engineering
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• v.5 no.3
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• pp.161-166
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• 2011

We present a fast algorithm for Korean text extraction and segmentation from subway signboards using smart phone sensors in order to minimize computational time and memory usage. The algorithm can be used as preprocessing steps for optical character recognition (OCR): binarization, text location, and segmentation. An image of a signboard captured by smart phone camera while holding smart phone by an arbitrary angle is rotated by the detected angle, as if the image was taken by holding a smart phone horizontally. Binarization is only performed once on the subset of connected components instead of the whole image area, resulting in a large reduction in computational time. Text location is guided by user's marker-line placed over the region of interest in binarized image via smart phone touch screen. Then, text segmentation utilizes the data of connected components received in the binarization step, and cuts the string into individual images for designated characters. The resulting data could be used as OCR input, hence solving the most difficult part of OCR on text area included in natural scene images. The experimental results showed that the binarization algorithm of our method is 3.5 and 3.7 times faster than Niblack and Sauvola adaptive-thresholding algorithms, respectively. In addition, our method achieved better quality than other methods.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.39-45
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• 2007

This paper proposes a method of container position measurement using automatic landing system that is estimated by a laser range finder. In the most of container position measurement methods, CCD cameras or laser scanners have been used to get the source data. However those sensors are not only weak for disturbances, for examples, the light, fog, and rain, but also the system cost is high. When the spreader arrives at the goal position, it is still swung by inertia or by wind effect. In this paper, the spreader swung data have been used to find the container position. The laser range finder is equipped in the front side of spreader. It can measure distance and relative position between spreader and container. This laser range finder can be rotated as desired by a motor. And a tilt sensor is equipped on the spreader to measure spreader sway. The relative position information between the spreader and a container using the laser range finder and tilt sensor is estimated through the geometrical analysis.

• Geomechanics and Engineering
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• v.14 no.3
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• pp.257-269
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• 2018

Analysis of slope stability failures, as one of the complex natural hazards, is one of the important research issues in the field of civil engineering. Present paper adopts and investigates four soft computing-based techniques for this problem: Patient Rule-Induction Method (PRIM), M5' algorithm, Group Method of data Handling (GMDH) and Multivariate Adaptive Regression Splines (MARS). A comprehensive database consisting of 168 case histories is used to calibrate and test the developed models. Six predictive variables including slope height, slope angle, bulk density, cohesion, angle of internal friction, and pore water pressure ratio were considered to generate new models. The results of test studies are used for feasibility, effectiveness and practicality comparison of techniques with each other, and with the other available well-known methods in the literature. Results show that all methods not only are feasible but also result in better performance than previously developed soft computing based predictive models and tools. It is shown that M5' and PRIM algorithms are the most effective and practical prediction models.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.1
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• pp.29-36
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• 2017

In this paper, we propose a method for recognizing eating behavior with almost no motion acceleration. First, by using the acceleration of gravity acting on the wrist direction, we calculate the angle between the gravity and the wrist direction. After that, detect wrist reciprocating motion when peak and vally exist in specific angle band. And then, when accumulate the number of wrist reciprocating motion occurrences are up to 10, then regard as the meal time 5 minutes before the detection time. Also, estimate the meal time only if its duration is more than 7 minutes. Using the data of 2128 minutes, which was collected from four graduate student, the result of the meal time estimation shows 95.63% accuracy.

• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.130-138
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• 2024

High-precision 3D Object Detection is a crucial component within autonomous driving systems, with far-reaching implications for subsequent tasks like multi-object tracking and path planning. In this paper, we propose a novel approach designed to enhance the performance of 3D Object Detection, especially in heading angle estimation by employing a moving object segmentation technique. Our method starts with extracting point-wise moving labels via a process of moving object segmentation. Subsequently, these labels are integrated into the LiDAR Pointcloud data and integrated data is used as inputs for 3D Object Detection. We conducted an extensive evaluation of our approach using the KITTI-road dataset and achieved notably superior performance, particularly in terms of AOS, a pivotal metric for assessing the precision of 3D Object Detection. Our findings not only underscore the positive impact of our proposed method on the advancement of detection performance in lidar-based 3D Object Detection methods, but also suggest substantial potential in augmenting the overall perception task capabilities of autonomous driving systems.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.1
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• pp.63-72
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• 2022

Objectives This study was conducted to characterize scoliosis patients visiting Korean medicine hospital and to analyze the demands and factors affecting discomfort. Methods This retrospective study analyzed 33 scoliosis patients who visited Korean medicine hospital from March, 2021 to October, 2021. The data analysis consisted of three factors: (1) demographic characteristics, (2) characteristics of demands on Korean medicine (reasons for choosing Korean medical treatment, preferred treatment methods, most uncomfortable part, treatment priorities) and (3) discomfort factors (treatment experiences, diagnosed age and Cobb's angle). Statistical analyses were performed and a p-value≤0.05 was considered to be statistically significant. Results 43.75% of the patients chose 'effectiveness' for the reason why they preferred Korean medicine treatment. 'Chuna treatment' was the most preferred treatment method. The patients chose 'lower back' for the most uncomfortable part and 'pain' for the highest priority of improvement. The Cobb's angle of included patients was 16.02±7.65° and it is not much differ to average of Cobb's angle in Korean. Discomfort was more severe in the patients with treatment-experienced than treatment-naive. The score of discomfort in appearance and psychological were higher in the patients diagnosed in childhood or adolescent period than who were diagnosed after adult. Classification based on Cobb's angle showed no statistical difference. Conclusions Not only Cobb's angle but also other clinical factors should be considered for effective treatment in scoliosis. Also, It is necessary to pay attention to adult scoliosis patients.

• Archives of design research
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• v.17 no.4
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• pp.141-148
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• 2004

The purpose of this study is to define the emotion that expressed in step animation and to quantify the intuitional expression of emotion that related step for using extract, measure, analysis the stimulate element about step. The survey of relation with 27 word of emotional expressions and 36 moving pictures of step sample is used for method of this test. The emotional mental structure is transferred to 2 dimensional planes as applying the results of analysis of integrated data using Quantification Method 3, which the integrated data is composed two axial - confidential axial and stabling axial. Analysis of distribution of 2 dimensional diagram shows that the second of the plane and the third of the plane have much data. However, the first of the plane and the forth of the plane have a little data. Through this kind of analysis of graph, it is difficult to express a different emotion between unstable the timidity mind and stable feel the timidity mind using only step analysis. Six difference types about physical elements affecting to emotion are selected and analyzed such as the paces of step, the rate of step, the movement angle of pelvis, the swing range of arm, angle of backbone and the lean angle of body. The result is that the rate of stop and the lean angle of body are the major element that effects to emotional stimulate of stop. This thesis argues about methods transforming subjective expression to objective and quantitative expression with the state of delicate emotion of character apply to step animation naturally. Those data to apply to multi-contents in future are the main target in this study.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.142-145
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• 2003

Many control applications using Neural Network need a priori information about the objective system. But it is impossible to get exact information about the objective system in real world. To solve this problem, several control methods were proposed. Reinforcement learning control using neural network is one of them. Basically reinforcement learning control doesn't need a priori information of objective system. This method uses reinforcement signal from interaction of objective system and environment and observable states of objective system as input data. But many methods take too much time to apply to real-world. So we focus on faster learning to apply reinforcement learning control to real-world. Two data types are used for reinforcement learning. One is reinforcement signal data. It has only two fixed scalar values that are assigned for each success and fail state. The other is observable state data. There are infinitive states in real-world system. So the number of observable state data is also infinitive. This requires too much learning time for applying to real-world. So we try to reduce the number of observable states by classification of states with Self-Organizing Map. We also use neural dynamic programming for controller design. An inverted pendulum on the cart system is simulated. Failure signal is used for reinforcement signal. The failure signal occurs when the pendulum angle or cart position deviate from the defined control range. The control objective is to maintain the balanced pole and centered cart. And four states that is, position and velocity of cart, angle and angular velocity of pole are used for state signal. Learning controller is composed of serial connection of Self-Organizing Map and two Multi-layer Feed-Forward Neural Networks.

• Journal of Biosystems Engineering
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• v.16 no.3
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• pp.228-238
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• 1991

Cam plays very important roles due to continuous requirement for the high-speed and automation of the machinery. A large number of studies of cam curve were carried out by many researchers, and CNC milling and machining center for manufacturing cam have been widely used recently. The purpose of this study was to develop a CAD/CAM system for cam using QuickBasic language in 16-bit PC for application of cam design and manufacturing. Results obtained were as follows : 1. It was possible to input data by entering cam angle and its corresponding R, from 0 to 360 deg. of cam angle. The tediousness at entering data was minimized because of the same data format for both cylindrical cam and disc cam, and free format used for data file. 2. It was possible to design cam by choosing only the number of cam curve because of developing the CAD/CAM program with dimensionless method of cam curves including widely used 19 kinds. After selecting the number of the cam curve, the CAD/CAM system automatically shows the characteristics of cam motion enough to help a designer to decide : displacement, velocity, acceleration and jerk. 3. It was possible to execute, in an efficient way, both the cam profile synthesis and the generation of NC program for CNC machining center by using the input data. 4. This NC program generated by the CAD/CAM system developed here, was evaluated as positive in relation with actual manufacturing experiments and thought to be useful in its application without any modification. It can be said that this CAD/CAM system could be used by the beginners to design and manufacture the cam automatically as the system consists of very simple dialogue methods. In addition, self-developed QuickBasic would be would used as a basic tool for further stuides in this area of research, together with application.