• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.156-158
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• 2009

A graphic simulator is efficient to see what will happen to the target robot. But it is not exactly same as the real world. Because there are so many physical laws to be concerned. In this paper, we propose a simulator with physics engine to create motions for quadruped robot. It is not only to show more real simulations but also to be more efficient for teaching motions to quadruped robot. To solve the quadruped robot's dynamics or inverse kinematics, It takes much times and hard effort. Using physics engine make it easy to setup motions without calculating inverse kinematics or dynamics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2767-2780
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• 2016

Video-based human-activity recognition has become increasingly popular due to the prominent corresponding applications in a variety of fields such as computer vision, image processing, smart-home healthcare, and human-computer interactions. The essential goals of a video-based activity-recognition system include the provision of behavior-based information to enable functionality that proactively assists a person with his/her tasks. The target of this work is the development of a novel approach for human-activity recognition, whereby human-body-joint features that are extracted from depth videos are used. From silhouette images taken at every depth, the direction and magnitude features are first obtained from each connected body-joint pair so that they can be augmented later with motion direction, as well as with the magnitude features of each joint in the next frame. A generalized discriminant analysis (GDA) is applied to make the spatiotemporal features more robust, followed by the feeding of the time-sequence features into a Hidden Markov Model (HMM) for the training of each activity. Lastly, all of the trained-activity HMMs are used for depth-video activity recognition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.639-646
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• 2016

In this study, the contactless measurement method with a optical displacement sensor(ODS, ADNS 9500) was proposed to overcome flaws in a rotary encoder based measurement under particular circumstances, such as a slippage and a case of little rotational inertia. The performance tests of the optical displacement sensor using data acquisition board and National Instruments's LabVIEW program were performed to accomplish accurate displacement measurements and the performance characteristics according to measurement direction, speed, acceleration, height and surface types were discovered through the repetitive tests. The experimental results indicate that, in order to get an accurate in-plane motion, the height(distance between the ODS and the target surface) has to be maintained at the range of 2.4 mm to 3.2 mm and the sensitivity(resolution) should be modified and applied to the formulae for displacement calculation, considering its measurement direction, speed and surface type.

• The Journal of Korean Institute of Information Technology
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• v.17 no.9
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• pp.91-97
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• 2019

When a radar tracks the warhead of a ballistic missile, decoys of a ballistic missile put a heavy burden on the radar resource management tracking the targets. To reduce this burden, it is necessary to be able to separate the signal of the warhead from the received dynamic radar cross section (RCS) signal on the radar. In this paper, we propose the method of separating the dynamic RCS of each target from the received signal by the Hough transform which extracts straight lines from the image. The micro motion of the targets was implemented using a 3D CAD model of the warhead and decoys. Then, we calculated the dynamic RCS from the 3D CAD model having micromotion and verified the performance by applying the proposed algorithm. Simulation results show that the proposed method can separate the signals of the warhead and decoys at the signal-to-noise ratio (SNR) of 10dB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1183-1188
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• 2016

Kinect sensor version 2 is a kind of camera released by Microsoft as a computer vision and a natural user interface for game consoles like Xbox one. It allows acquiring color images, depth images, audio input and skeletal data with a high frame rate. In this paper, using depth image, we present a surveillance system of a certain area within Kinect's field of view. With computer vision library(Emgu CV), if an object is detected in the target area, it is tracked and kinect camera takes RGB image to send it in database server. Therefore, a mobile application on android platform was developed in order to notify the user that Kinect has sensed strange motion in the target region and display the RGB image of the scene. User gets the notification in real-time to react in the best way in the case of valuable things in monitored area or other cases related to a reserved zone.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.11-19
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• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Radiation Oncology Journal
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• v.20 no.1
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• pp.41-52
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• 2002

Purpose : 3D conformal radiotherapy, the optimum dose delivered to the tumor and provided the risk of normal tissue unless marginal miss, was restricted by organ motion. For tumors in the thorax and abdomen, the planning target volume (PTV) is decided including the margin for movement of tumor volumes during treatment due to patients breathing. We designed the respiratory gating radiotherapy device (RGRD) for using during CT simulation, dose planning and beam delivery at identical breathing period conditions. Using RGRD, reducing the treatment margin for organ (thorax or abdomen) motion due to breathing and improve dose distribution for 3D conformal radiotherapy. Materials and Methods : The internal organ motion data for lung cancer patients were obtained by examining the diaphragm in the supine position to find the position dependency. We made a respiratory gating radiotherapy device (RGRD) that is composed of a strip band, drug sensor, micro switch, and a connected on-off switch in a LINAC control box. During same breathing period by RGRD, spiral CT scan, virtual simulation, and 3D dose planing for lung cancer patients were peformed, without an extended PTV margin for free breathing, and then the dose was delivered at the same positions. We calculated effective volumes and normal tissue complication probabilities (NTCP) using dose volume histograms for normal lung, and analyzed changes in doses associated with selected NTCP levels and tumor control probabilities (TCP) at these new dose levels. The effects of 3D conformal radiotherapy by RGRD were evaluated with DVH (Dose Volume Histogram), TCP, NTCP and dose statistics. Results : The average movement of a diaphragm was 1.5 cm in the supine position when patients breathed freely. Depending on the location of the tumor, the magnitude of the PTV margin needs to be extended from 1 cm to 3 cm, which can greatly increase normal tissue irradiation, and hence, results in increase of the normal tissue complications probabiliy. Simple and precise RGRD is very easy to setup on patients and is sensitive to length variation (+2 mm), it also delivers on-off information to patients and the LINAC machine. We evaluated the treatment plans of patients who had received conformal partial organ lung irradiation for the treatment of thorax malignancies. Using RGRD, the PTV margin by free breathing can be reduced about 2 cm for moving organs by breathing. TCP values are almost the same values $(4\~5\%\;increased)$ for lung cancer regardless of increasing the PTV margin to 2.0 cm but NTCP values are rapidly increased $(50\~70\%\;increased)$ for upon extending PTV margins by 2.0 cm. Conclusion : Internal organ motion due to breathing can be reduced effectively using our simple RGRD. This method can be used in clinical treatments to reduce organ motion induced margin, thereby reducing normal tissue irradiation. Using treatment planning software, the dose to normal tissues was analyzed by comparing dose statistics with and without RGRD. Potential benefits of radiotherapy derived from reduction or elimination of planning target volume (PTV) margins associated with patient breathing through the evaluation of the lung cancer patients treated with 3D conformal radiotherapy.

• Journal of the Korean Magnetics Society
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• v.25 no.3
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• pp.83-86
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• 2015

Nowadays the weapon systems are employed air bursting munition (ABM) as smart programmable 40 mm shells which have been developed in order to hit the target with programmed munition that can be air burst after a set distance in the battlefield. In order to improve the accuracy of such a bursting time, by measuring the speed of the munition from the barrel, weapon systems calculate the exact time of flight to the target and then the time information must be inputted to the munition. In this study, we introduce a device capable of detecting a shot at K4 40 mm automatic grenade. The shot is composed of a rotating copper band to convert linear motion into rotary motion when it passes through the barrel, the steel section is exert the effect of fragment and aluminum section to give fuze information. The aluminum section was used to detect munition using eddy current method. To measure muzzle velocity by means of non-contact method, two eddy current probes separated 10 cm was employed. Time interval between two eddy current probe detection times was used as muzzle velocity. The eddy current probe was fabricated U-shape Mn-Zn ferrite core with enamelled copper wire, and 200 kHz alternating current was used to detect inductance change. Measured muzzle velocity using the developed sensor was compared to the Doppler radar system. The difference was smaller than 1%.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.52-58
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• 2002

This Paper describes the method of real time object tracking using variable searching window. Monitoring systems require real time object tracking in video, efficiencies depend on environment of monitoring target. To get a position of object using a difference between background image and input image, the system extracts contour and centroid of the object. This method track motion of object using variable searching window from size and position of object. The background imgaes and camera are limited as fixed environment. The test result of proposed method Is 17-23FPS, this shows more fast process speed than average(10-14FPS) of existing object tracking method.

• Annual Conference of KIPS
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• 2004.05a
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• pp.873-876
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• 2004

사람의 동작을 인식하는 것에 대한 연구는 게임, 유비쿼터스 컴퓨팅 등의 발전에 따라 그 중요성이 증가하고 있다. 그러나, 대부분의 기존 연구에서는 극히 소수의 동작만을 정의하거나 특정 부위의 동작만을 다루므로 실제 응용에 적용하기에는 적합하지 않다. 본 논문에서는 특정 도메인의 사용 없이, 카메라 영상 입력으로 취득된 동작 패턴 정보만을 이용하여 40종 전신 연속 동작을 구분하는 동작인식 방법을 연구하였다. 인식에 사용된 입력 데이터는 동작자 관절들의 위치 및 회전 값들이며, 다수의 동작들을 인식하기 위해서는 기존의 인식 알고리즘들인 특징기반 인식, HMM, 신경망(Neural Network)등을 사용하여 복합적인 인식 엔진을 구성하여야 했다. 입력 데이터별로 적합한 인식 모듈을 거치게 하기 위해서는, 동작에 의한 입력 데이터에서 동작자 움직임의 주요 신체 부위를 추출함으로써 입력 데이터가 해당 그룹의 인식 모듈로 자동적으로 분류되게 하는 방법을 사용한다. 이는 다층의 인식 레이어 중 복잡도가 증가하는 하위 레이어일수록 자동 분류에 의해 걸러진 데이터만을 취급하게 되므로 효과적이다. 전체 실험 결과 단계별로 약 79~97%의 인식률을 보였다. 이는 향후 특정 컨텍스트 정보와 결합할 때 매우 높은 인식률을 기대할 수 있게 하는 수치이다.