• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.784-789
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• 1994

In the mobile robot research, monitoring the present status and self-navigating the robot in various environment are signifiant. This paper treates a navigation algorithm using a fuzzy logic and a sensor system - laser range finder. The navigation algorithm using a fuzzy logic is achieved by organizing the knoweledge base for self-navigation of mobile robot. In order that mobile robot is economically arrived the goal, the knowledge base is applied to acquire the informations of moving distance, direction, and velocity in every cycle time.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.945-946
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• 2015

Laser Range Finder를 이용하여 생성한 3차원 점군 정보는 단면적인 부분만 볼 수 있으며, 잡음이 포함되어 작은 물체를 추출하는데 많은 영향이 생긴다. 이러한 잡음이 있는 3차원 점군 정보 사이에서 밸브의 중심의 위치에 대한 추가적인 입력을 받아 원환체, 원통, 평면의 정보를 복합적으로 포함하고 있는 밸브의 모델을 추출한다.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.22 no.1
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• pp.6-10
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• 1986

The feasibility of passive detection of fishes which had been caught in the fishing grounds near the Korean peninsula was theoretically investigated. Considering the commercial importance and the acoustical informations readily identified, although many species of fish make noise, Croaker is clarified to be a representative fish for passive fish detection. Assuming a source level of the sound produced by croakers is given as 150-18OdB (re 1l'pa, 500 Hz bandwidth), The range detected by a passive line array sonar is estimated to be about 3-20km. In addition, the tonal noise (700~800Hz) made by croaker that is easily separated from underwater noise is expected to increase the ability to discriminate from the other species of fish.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.5
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• pp.367-373
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• 2016

In this paper, range measurement performance of LRF (Laser Range Finder) module and image contrast of color CCD camera are evaluated under the aerosol (high temperature steam) environments, which are simulated severe accident conditions of the LWR (Light-Water-Reactor) nuclear power plant. Data of LRF and color CCD camera are key informations, which are needed in the implementation of SLAM (Simultaneous Localization and Mapping) function for emergency response robot system to cope with urgently accidents of the nuclear power plant.

• The Journal of the Acoustical Society of Korea
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• v.11 no.1
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• pp.42-51
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• 1992

This paper proposes an acquisition and the representation method of the 3-dimensional information. The proposed range finder system can reduce the computation time by only calculating the ${\triangle}R$ of each pixel compared to the existing methods. We also propose a shape feature extraction method by considering the sign change of the acquired range data. Finally, the effectiveness of this system is demonstrated by several experiments.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.539-543
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• 2005

The research presented in this paper enables real-time 3D modeling to help make construction processes ultimately faster, more predictable and safer. Initial research efforts used an emerging sensor technology and proved its usefulness in the acquisition of range information for the detection and efficient representation of static and moving objects. Based on the time-of-flight principle, the sensor acquires range and intensity information of each image pixel within the entire sensor's field-of-view in real-time with frequencies of up to 30 Hz. However, real-time working range data processing algorithms need to be developed to rapidly process range information into meaningful 3D computer models. This research ultimately focuses on the application of safer heavy equipment operation. The paper compares (a) a previous research effort in convex hull modeling using sparse range point clouds from a single laser beam range finder, to (b) high-frame rate update Flash LADAR (Laser Detection and Ranging) scanning for complete scene modeling. The presented research will demonstrate if the FlashLADAR technology can play an important role in real-time modeling of infrastructure assets in the near future.

• Restorative Dentistry and Endodontics
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• v.33 no.1
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• pp.20-27
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• 2008

The purpose of this study was to evaluate the consistency of two electronic apex locators in vitro model. Materials consisted of fifty two extracted premolars and two electronic apex locators; Root ZX (J. Morita, Osaka, Japan) and E-Magic Finder Deluxe (S-Denti. Cheonan, Korea). After access preparation, the teeth were embedded in a saline-mixed alginate model. Canal lengths of each tooth were measured at "0.5" and "Apex" mark of the apex locators, respectively so that each tooth had two measurements from 0.5 and Apex points. The file was fixed at final measurement using a glass ionomer cement. The apical 4 mm from the apex was exposed to measure the distance from the file tip to the major apical foramen of each tooth. Average distances and standard deviations were used to evaluate the consistency. Results showed that all measurements of both Root ZX and E-Magic Finder located the major foramen the range of ${\pm}0.5\;mm$ level. Both apex locators showed better consistency at Apex mark than at 0.5 mark. The average distance of file tip-major foramen was - 0.18 mm at 0.5 mark and - 0.07 mm at Apex mark in Root ZX, - 0.25 mm at 0.5 mark and - 0.02 mm at Apex mark in E-Magic Finder. Standard deviation was 0.21 at 0.5 mark and 0.12 at Apex mark in Root ZX, 0.12 at 0.5 mark and 0.09 at Apex mark in E-Magic Finder.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.4
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• pp.361-368
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• 2015

This paper reports an unscented Kalman filter approach for localization of a mobile robot in an indoor environment. The method proposes a new model of measurement uncertainty which adjusts the error covariance according to the measured distance. The method also uses non-zero off diagonal values in error covariance matrices of motion uncertainty and measurement uncertainty. The method is tested through experiments in an indoor environment of 100*40 m working space using a differential drive robot which uses Laser range finder as an exteroceptive sensor. The results compare the localization performance of the proposed method with the conventional method which doesn't use adaptive measurement uncertainty model. Also, the experiment verifies the improvement due to non-zero off diagonal elements in covariance matrices. This paper contributes to implementing and evaluating a practical UKF approach for mobile robot localization.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.2
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• pp.36-54
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• 2017

The purpose of this paper is to develop a multi-sensor fusion-based traffic information acquisition system with robust to environmental changes. it combines the characteristics of each sensor and is more robust to the environmental changes than the video detector. Moreover, it is not affected by the time of day and night, and has less maintenance cost than the inductive-loop traffic detector. This is accomplished by synthesizing object tracking informations based on a radar, vehicle classification informations based on a video detector and reliable object detections of a infrared range finder. To prove the effectiveness of the proposed system, I conducted experiments for 6 hours over 5 days of the daytime and early evening on the pedestrian - accessible road. According to the experimental results, it has 88.7% classification accuracy and 95.5% vehicle detection rate. If the parameters of this system is optimized to adapt to the experimental environment changes, it is expected that it will contribute to the advancement of ITS.

• 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.