• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.448-453
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• 2012

There are many researches to develop robots that improve its mobility to adapt in various uneven environments. In the paper, a hybrid wheeled and legged mobile robot is designed and a obstacle avoidance algorithm is proposed based on low power walking using LRF(Laser Range Finder). In order to stabilize the robot's motion and reduce energy consumption, we implement a low-power walking algorithm through comparison of the current value of each motors and correction of posture balance. A low-power obstacle avoidance algorithm is proposed by using LRF sensor. We improve walking stability by distributing power consumption and reduce energy consumption by selecting a shortest navigation path of the robot. The proposed methods are verified through walking and navigation experiments with the developed hybrid robot.

• Journal of the Optical Society of Korea
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• v.19 no.1
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• pp.1-6
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• 2015

We investigate the propagation characteristics of a pulse laser in a time-of-flight laser range finder (TOF-LRF) system with variations in atmospheric conditions, such as temperature, pressure, relative humidity, and the concentration of $CO_2$. The measurement error of distance related with the group velocity change in the TOF-LRF system is analyzed by considering the refractive index of the standard atmosphere with variations in atmospheric conditions. The dependence of the pulse width broadening induced by chromatic dispersion of the standard atmosphere on the operating wavelength and the initial pulse width of the light sources is discussed. The transmission of air with variations in the relative humidity or the concentration of $CO_2$ is analyzed by using different values of absorption coefficients depending on the operation wavelength of the light source in the TOF-LRF system.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.11
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• pp.1153-1163
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• 2014

An efficient 3D SLAM (Simultaneous Localization and Map Building) method is developed for urban building environments using a tilted 2D LRF (Laser Range Finder), in which a 3D map is composed of perpendicular/horizontal planar polygons. While the mobile robot is moving, from the LRF scan distance data in each scan period, line segments on the scan plane are successively extracted. We propose an "expected line segment" concept for matching: to add each of these scan line segments to the most suitable line segment group for each perpendicular/horizontal planar polygon in the 3D map. After performing 2D localization to determine the pose of the mobile robot, we construct updated perpendicular/horizontal infinite planes and then determine their boundaries to obtain the perpendicular/horizontal planar polygons which constitute our 3D map. Finally, the proposed SLAM algorithm is validated via extensive simulations and experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.5
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• pp.465-470
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• 2015

This paper proposes a robust 3D mapping system for a UAV (Unmanned Aerial Vehicle) that carries a LRF (Laser Range Finder) using the sinusoidal trajectory algorithm. In the case of previous 3D mapping research, the UAV usually takes off vertically and flights up and down while the LRF is measuring horizontally. In such cases, the measuring range is limited and it takes a long time to do mapping. By using the sinusoidal trajectory algorithm proposed in this research, the 3D mapping can be time-efficient and the measuring range can be widened. The 3D mapping experiments have been done to evaluate the performance of the sinusoidal trajectory algorithm by scanning indoor walls.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.521-525
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• 2011

Lane marking detection is one of important issues in the field of autonomous mobile robot. Especially, in urban environment, like pavement roads of downtown or tour tracks of Science Park, which have continuous patterns on the surface of the road, the lane marking detection becomes more important ability. Although there were many researches about lane detection and lane tracing, many of them used vision sensors mainly to detect lane marking. In this paper, we obtain 2 dimensional library data of 'Intensity' and 'Distance' using one laser rangefinder only. We design a simple classifier and filtering algorithm for the lane detection which uses only one LRF (Laser Range Finder). Allowing extended usage of LRF, this research provides more functionality not only in range finding but also in lane detecting to mobile robots. This work will be technically helpful for robot developers to design more simple and efficient autonomous driving system using LRF.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.10
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• pp.995-1005
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• 2011

An efficient outdoor local localization method is suggested using multi-sensor fusion with MU-EKF (Multi-Update Extended Kalman Filter) for car-like mobile robots. In outdoor environments, where mobile robots are used for explorations or military services, accurate localization with multiple sensors is indispensable. In this paper, multi-sensor fusion outdoor local localization algorithm is proposed, which fuses sensor data from LRF (Laser Range Finder), Encoder, and GPS. First, encoder data is used for the prediction stage of MU-EKF. Then the LRF data obtained by scanning the environment is used to extract objects, and estimates the robot position and orientation by mapping with map objects, as the first update stage of MU-EKF. This estimation is finally fused with GPS as the second update stage of MU-EKF. This MU-EKF algorithm can also fuse more than three sensor data efficiently even with different sensor data sampling periods, and ensures high accuracy in localization. The validity of the proposed algorithm is revealed via experiments.

• Nuclear Engineering and Technology
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• v.51 no.7
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• pp.1758-1764
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• 2019

As the safety level of nuclear power plants (NPPs) relates to the safety of individuals, society, and the environment, it is important to establish NPP safety goals. In Korea, two quantitative health objectives and one large release frequency (LRF) criterion were formally set as quantitative safety goals for NPPs by the Nuclear Safety and Security Commission in 2016. The risks of prompt and cancer fatalities from NPPs should be less than 0.1% of the overall risk, and the frequency of nuclear accidents releasing more than 100 TBq of Cs-137 should not exceed 1E-06 per reactor year. This paper reviews the hierarchical structure of safety goals in Korea, its relationship with those of other countries, and the relationships among safety goals and subsidiary criteria like core damage frequency and large early release frequency. By analyzing the effect of the release of 100 TBq of Cs-137 via consequence analysis codes in eight different accident scenarios, it was shown that meeting the LRF criterion results in negligible prompt fatalities in the surrounding area. Hence, the LRF criterion dominates the safety goals for Korean NPPs. Safety goals must be consistent with national policy, international standards, and the goals of other counties.

• Korean Journal of Applied Biomechanics
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• v.24 no.1
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• pp.19-26
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• 2014

This study investigated foot pressure patterns between experienced skiers and intermediate skiers during alpine skiing. Five experienced skiers and five intermediate skiers participated in this study. Foot pressure measurement system was used to measure vertical ground reaction force (vGRF) and contact area under the six plantar regions. Each participant was asked to perform basic parallel turns and carved turns on a $18^{\circ}$ groomed slope. Each right turn was divided into the initiation phase, the steering phase 1 and 2. For the initiation phase of the basic parallel turns, significantly greater contact area was found on the LRF and RRF of the intermediate skiers (p<.05) and significantly greater vGRF was found on the LRF of the intermediate skiers (p<.05). Also significantly greater vGRF and contact area were found on the LRF and RRF of the intermediate skiers at the steering phase 1 (p<.05) and on the LRF of the intermediate skiers at the steering phase 2 (p<.05). For the carved turns, significantly greater vGRF and contact area were found on the LRF and RRF of the intermediate skiers at all three phase (p<.05). On the other hand, significantly greater vGRF was found on the RFF of the experienced skiers at the steering phase 1 (p<.05). Also significantly greater vGRF and contact area were found on the RMF of the experienced skiers at the steering phase 2 (p<.05). In order to increase performance, we suggest that the intermediate skiers should be unweighted at the initiation phase and shift the body weight to the forefoot of the outer foot at the steering phase 1. Also, the outer ski should be loaded more than the both skis at the steering phase 1 and 2.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.106-109
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• 2004

In this project, we have developed the eye-safe LRF system of 1.54 ${\mu}{\textrm}{m}$ wavelength using OPO. The maximum measured distance was 3.7km in outdoor experiment. We used Nd：YAG (1064nm) as a laser medium. It was applied BBO to construct the system. We also developed a time-counter for the range finder using a method of TOF (time of flight). The counter-clock used at the time counter was 320MHz making resolution within $\pm$1m. Start and stop signals were detected by two channel systems using PIN and APD. The LRF's repetition rate was 4 times per minute. The energy was measured to be over 9mJ. And, pulse-duration was 23ns. Resolution was $\pm$2m at the distance measurement using a target.

• The Journal of Korea Robotics Society
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• v.6 no.1
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• pp.86-96
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• 2011

The human-following is one of the significant procedure in human-friendly navigation of mobile robots. There are many approaches of human-following technology. Many approaches have adopted various multiple sensors such as vision system and Laser Range Finder (LRF). In this paper, we propose detection and tracking approaches for human legs by the use of a single LRF. We extract four simple attributes of human legs. To define the boundary of extracted attributes mathematically, we used a Support Vector Data Description (SVDD) scheme. We establish an efficient leg-tracking scheme by exploiting a human walking model to achieve robust tracking under occlusions. The proposed approaches were successfully verified through various experiments.