• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.21 no.3
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• pp.212-219
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• 2011

In this paper, intrusion detection technique based on the sound field variation of audio frequency in the security space is proposed. The sound field formed by sound source can be detected with the microphone when the obstacle or intruder is positioned. The sound field variation due to the intruder is mainly caused by the interference of audio wave. With the help of numerical simulation of sound field formations, the increase or decrease of sound pressure level is analyzed not only by the obstacle, but also by the intruder. Even the microphone is positioned behind the source, sound pressure level can be increased or decreased due to the interference of sound wave. Frequency response test is performed with Gaussian white noise signal to get the whole frequency response from 0 to half of sampling frequency. There are three security cases. Case 1 is the situation of empty space with and without intruder, case 2 is the situation of blocking obstacle with and without intruder, and case 3 is the situation of side blocking obstacle with and without intruder. At each case, the frequency response is obtained first at the security space without intruder, and second with intruder. From the experiment, intruder size of diameter of 50 cm pillar can be successfully detected with the proposed technique. Moreover, the case 2 and case 3 bring about bigger sound field variation. It means that the proposed technique have the potential of more credible security guarantee in real situation.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.623-629
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• 2018

In this paper, we propose a real-time obstacle detection and avoidance path generation algorithm for UAV. 2-D Lidar is used to detect obstacles, and the detected obstacle data is used to generate real-time histogram for local avoidance path and a 2-D SLAM map used for global avoidance path generation to the target point. The VFH algorithm for local avoidance path generation generates a real-time histogram of how much the obstacles are distributed in the vector direction and distance, and this histogram is used to generate the local avoidance path when detecting near fixed or dynamic obstacles. We propose an algorithm, called modified $RRT^*-Smart$, to overcome existing limitations. That generates global avoidance path to the target point by creating lower costs because nodes are checked whether or not straight path to a target point, and given arbitrary lengths and directionality to the target points when nodes are created. In this paper, we prove the efficient avoidance maneuvering through various simulation experiment environment by creating efficient avoidance paths.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.639-644
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• 2003

An unstructured environment requires a robot to possess outstanding mobility and advanced control algorithms since there exist complicated configurations such as obstacle, uneven surface, etc. Especially, when a quadruped robot walks in these environments, obstacles in the walking route will obstruct the walking or may give rise to a serious trouble. In this paper, we introduce a strategy for the stable walking in unstructured environment. The proposed strategy consists of two control algorithms. One is a collision{free algorithm to avoid obstacles and the other is an algorithm to overcome any obstacle. These are based on the obstacle detection method and a shape reconstruction algorithm, Which algorithms are described in detail. In addition, the validity of these algorithms have been demonstrated through experiments using a quadruped walking robot called "MRWALLSPECT III(Multifunctional Robot for Wall inSPECTion version 3 )".

• International Journal of Railway
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• v.3 no.3
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• pp.106-112
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• 2010

Accidents at level crossing have large portion on train accidents, and causes economical loss by train delay and operational interruption. Various safety equipments are employed to reduce the accident at level crossing, but existing warning device, and crossing barrier are simple train-oriented protection equipments. In this paper, intelligent railway level crossing system is proposed to prevent and reduce accidents. For train driver's prompt action, image of level crossing and obstacle warning message are continuously provided to train driver through wireless communication in level crossing control zone. Obstacle warning messages, which are extracted by computer vision processing of captured image at level crossing, are recognized by train driver through message color, flickering and warning sound. It helps train driver to decide how to take an action. Meanwhile, for vehicle driver's attention, location and speed of approaching train are given to roadside equipments. We identified the effect of proposed system through test installation at Sea train and Airport level crossing of Yeong-dong line.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.6
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• pp.1006-1012
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• 2010

For the autonomous navigation of an unmanned ground vehicle in the rough terrain and combat, the dust environment should necessarily be overcome. Therefore, we propose a robust obstacle detection methodology using laser range sensor and radar. Laser range sensor has a good angle and distance accuracy, however, it has a weakness in the dust environment. On the other hand, radar has not better the angle and distance accuracy than laser range sensor, it has a robustness in the dust environment. Using these characteristics of laser range sensor and radar, we use laser range sensor as a main sensor for normal times and radar as a assist sensor for the dust environment. For fusion of laser range sensor and radar information, the angle and distance data of the laser range sensor and radar are separately transformed to the angle and distance data of virtual range sensor which is located in the center of the vehicle. Through distance comparison of laser range sensor and radar in the same angle, the distance data of a fused virtual range sensor are changed to the distance data of the laser range sensor, if the distance of laser range sensor and radar are similar. In the other case, the distance data of the fused virtual range sensor are changed to the distance data of the radar. The suggested methodology is verified by real experiment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1925-1936
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• 2010

In this paper, multi-legged robot was designed and produced using stable walking pattern algorithm. The robot had embedded camera and wireless communication function and it is possible to recognize both hand posture and obstacles. The algorithm decided moving paths, and recognized and avoided obstacles through Hough Transform using Edge Detection of inputed image from image sensor. The robot can be controlled by hand posture using Mahalanobis Distance and average value of skin's color pixel, which is previously learned in order to decide the destination. The developed system has shown obstacle detection rate of 96% and hand posture recognition rate of 94%.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.1
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• pp.99-107
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• 2014

Abruptly occurred obstacles on highway threaten driving safety. Radar draws the attention to the collision avoidance system because it can be fully operational in all weather, and day and night condition. This paper presents the design, implementation and performance test results of pulsed Doppler radar system for detection and warning of road obstacles. The system is designed to consider highway environment and detection capability about various fixed and moving obstacles. The system consists of 4 subsystems, which include antenna unit, transmitter and receiver unit, radar signal & data processing unit, and controller & display unit. The core technologies include clutter map based change detection for fixed obstacles detection, Doppler estimation for velocity detection of moving targets, and azimuth angle estimation method using monopulse for lane estimation and tracking. The design performance of the developed radar system is verified through experiments using a fixed reference target and moving vehicles in test highway.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2000.11a
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• pp.207-217
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• 2000

In this paper, we describe an image processing algorithm which is able to recognize the road lane. This algorithm performs to recognize the interrelation between AGV and the other vehicle. We experimented on AGV driving test with color CCD camera which is setup on the top of vehicle and acquires the digital signal. This paper is composed of two parts. One is image preprocessing part to measure the condition of the lane and vehicle. This finds the information of lines using RGB ratio cutting algorithm, the edge detection and Hough transform. The other obtains the situation of other vehicles using the image processing and viewport. At first, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, if vehicle knows the driving conditions which are angle, distance error and real position of other vehicles, we should calculate the reference steering angle.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.1
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• pp.43-62
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• 2017

Mobile pulse scanning Light Detection And Ranging (LIDAR) are essential components of intelligent vehicles capable of autonomous travel. Obstacle detection functions of autonomous vehicles require very low failure rates. With the increasing number of autonomous vehicles equipped with scanning LIDARs to detect and avoid obstacles and navigate safely through the environment, the probability of mutual interference becomes an important issue. The reception of foreign laser pulses can lead to problems such as ghost targets or a reduced signal-to-noise ratio. This paper will show the probability that any two scanning LIDARs will interfere mutually by considering spatial and temporal overlaps. We have conducted four experiments to investigate the occurrence of the mutual interference between scanning LIDARs. These four experimental results introduced the effects of mutual interference and indicated that the interference has spatial and temporal locality. It is hard to ignore consecutive mutual interference on the same line or the same angle because it is possible the real object not noise or error. It may make serious faults because the obstacle detection functions of autonomous vehicle rely on heavily the scanning LIDAR.

• Spatial Information Research
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• v.22 no.1
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• pp.75-84
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• 2014

Power lines are one of the main obstacles causing an aircraft crash and thus their realtime detection is significantly important during flight. To avoid such flight obstacles, the use of LIDAR has been recently increasing thanks to its advantages that it is less sensitive to weather conditions and can operate in day and night. In this study, we suggest a fast method to detect power lines from LIDAR data for flight obstacle avoidance. The proposed method first extracts non-ground points by eliminating the points reflected from ground surfaces using a filtering process. Second, we calculate the eigenvalues for the covariance matrix from the coordinates of the generated non-ground points and obtain the ratio of eigenvalues. Based on the ratio of eigenvalues, we can classify the points on a linear structure. Finally, among them, we select the points forming horizontally long straight as power-line points. To verify the algorithm, we used both real and simulated data as the input data. From the experimental results, it is shown that the average detection rate and time are 80% and 0.2 second, respectively. If we would improve the method based on the experiment results from the various flight scenario, it will be effectively utilized for a flight obstacle avoidance system.