• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1996년도 춘계학술대회 논문집
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• pp.680-684
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• 1996

Welding systems cannot adapt to changes in the joint geometry which may occur due to a variety of reason. Automatic seam tracking technigue is essential to adjust the welding torch position in real time as it moves along the seam. Automatic tracking system must keep the welding speed constant unrelation to the change of the welding path. Therefore, the information from the laser displacement sensor must be converted into the input to operate the X-Y table and to rotate the desired torch position by proposed algorithm. In this research, laser displacement sensor is used as a seam finder in the automatic tracking system. X-Y moving table manipulated by ac servo motor controls the position and velocity of the torch-and-sensor part. DC motor controls the position and velocity of the torch. X-Y table controls the position of sensor and relative position of torch is controlled by dc motor which is mounted at sensor-and-torch part. Sensor is always ahead of torch to preview the weld line. From the experimental results, we could see the possiblity that the laser displacement sensor can be used as a seam finder in welding process and that the seam tracking system controlled by proposed algorithm is well done.

• 한국지능시스템학회논문지
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• 제27권2호
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• pp.170-178
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• 2017

본 논문은 무인잠수정의 동특성을 고려하지 않아 실제로 항행이 불가능한 급격히 변화하는 경로를 계획하기도 하는 기존 $A^*$ 알고리즘 기반 경로계획의 단점을 개선하기 위하여, 무인잠수정의 동특성을 고려한 항행궤적에 기반한 개선된 경로계획 알고리즘을 제안한다. 기존의 $A^*$ 기반 알고리즘은 무인잠수정이 인접노드로 이동하는 경로를 직선으로 가정하여 이동비용을 계산하는 반면, 개선된 경로계획 알고리즘은 경로점 제어에 의하여 생성된 현실적 항행궤적을 노드 간의 이동경로로 설정하고 이동비용을 계산하여 최적의 경로를 계획한다. 모의실험에서 제안한 기법과 기존의 기법의 경로계획을 비교하여 본 논문의 논의가 타당함을 보인다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.1261-1264
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• 2005

In this paper, a new intelligent moving target tracking and surveillance system basing on the pan/tilt-embedded stereo camera system is suggested and implemented. In the proposed system, once the face area of a target is detected from the input stereo image by using a YCbCr color model and then, using this data as well as the geometric information of the tracking system, the distance and 3D information of the target are effectively extracted in real-time.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1138-1141
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• 1995

An arc sensor for seam tracking is developed to automate sub-assembly welding in shipbuilding. We utilize a moving average method, which produces an effect of low-pass filter, to generate the position compensation. Therefore the sensor is able to modify the path of the weld seam in real time. By simplifying the compension process, the tunning time is reduced so that operators react quickly. It turns out that this sensor is highly reliable and it is installed and being used in SHI Keoje shipbuilding yard.

• ETRI Journal
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• 제43권4호
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• pp.617-629
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• 2021

Although the actual visual simultaneous localization and mapping (SLAM) algorithms provide highly accurate tracking and mapping, most algorithms are too heavy to run live on embedded devices. In addition, the maps they produce are often unsuitable for path planning. To mitigate these issues, we propose a completely closed-loop online dense RGB-D SLAM algorithm targeting autonomous indoor mobile robot navigation tasks. The proposed algorithm runs live on an NVIDIA Jetson board embedded on a two-wheel differential-drive robot. It exhibits lightweight three-dimensional mapping, room-scale consistency, accurate pose tracking, and robustness to moving objects. Further, we introduce a navigation strategy based on the proposed algorithm. Experimental results demonstrate the robustness of the proposed SLAM algorithm, its computational efficiency, and its benefits for on-the-fly navigation while mapping.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제10권2호
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• pp.101-106
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• 2010

We propose an approach to estimate the real-time moving trajectory of an object in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the inputoutput relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• 대한임베디드공학회논문지
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• 제3권2호
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• pp.57-65
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• 2008

Recently many researches on intelligent robots have been studied. An intelligent robot is capable of recognizing environments or objects to autonomously perform specific tasks using sensor readings. One of fundamental problems in vision-based robot applications is to recognize where it is and to decide safe path to perform autonomous navigation. However, previous approaches only consider well-organized environments that there is no moving object and environment changes. In this paper, we introduce a novel navigation strategy to handle occlusions caused by moving objects using various computer vision techniques. Experimental results demonstrate the capability to overcome such difficulties for autonomous navigation.

• 전기전자학회논문지
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• 제13권2호
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• pp.150-158
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• 2009

로봇의 자율적 이동을 위해서는 현재지점에서부터 목표지점까지를 연결하는 최적 경로의 계획이 필수적이다. 그리고 이동 로봇의 최적 경로는 장애물과의 충돌 없이 목표물까지 최단 이동 거리로 이동 할 수 있도록 하는 경로를 뜻한다. 실제 많은 이동 로봇은 주위 장애물에 대한 정보 없이, 미지의 환경에서도 자율적 이동이 가능해야 한다. 이에, 본 논문에서는 미지 환경에 적합한 새로운 형태의 경로 계획 및 장애물 회피 방법을 제안한다. 이 경로 계획 방법은 매 순간 최적이라 예측되는 지역적 목표를 지정하여 추적하며, 이러한 추적의 연속들의 결과가 로봇의 1차적 이동 경로가 된다. 하지만 이 경로는 장애물과의 충돌이 배제된 경로이다. 이에, 본 논문에서는 Potential Field 방법을 모방한 새로운 방법의 장애물 회피 방법을 제안한다. 그리고 위의 본 논문에서 제안한 경로 계획과 장애물 회피 방법의 성능 및 정확성을 모의실험을 통해 검증한다.

• 디지털콘텐츠학회 논문지
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• 제14권4호
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• pp.447-454
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• 2013

수많은 CCTV에서 기록 보관되는 영상 데이터가 폭발적으로 증가하면서, 빅데이터 환경에 적합한 CCTV 영상 데이터의 처리와 응용이 큰 이슈가 되고 있다. 본 논문에서는 대규모 CCTV 영상 데이터를 하둡 기반으로 병렬처리하고, 이를 활용한 VRT(Vehicle Route Tracking) 시스템을 설계 구현한다. VRT 시스템은 대규모 차량 번호판 인식 시스템의 특성을 가지며, 구글 맵을 통해 특정 차량의 이동경로를 빠른 시간 내에 추적 가능케 한다. 그리고 VRT 시스템의 성능 평가를 위한 실험을 통하여 단일 PC와 하둡 환경에서 대규모 CCTV 영상 데이터의 번호판 인식 시간을 비교 분석한다.

• 로봇학회논문지
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• 제15권3호
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• pp.221-232
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• 2020

In a four-wheel independent drive platform, four wheels and motors are connected directly, and the rotation of the motors generates the power of the platform. It uses a skid steering system that steers based on the difference in rotational power between wheel motors. The platform can control the speed of each wheel individually and has excellent mobility on dirt roads. However, the difficulty of the straight-running is caused due to torque distribution variation in each wheel's motor, and the direction of rotation of the wheel, and moving direction of the platform, and the difference of the platform's target direction. This paper describes an algorithm to detect the slip generated on each wheel when a four-wheel independent drive platform is traveling in a harsh environment. When the slip is detected, a compensation control algorithm is activated to compensate the torque of the motor mounted on the platform to improve the trajectory tracking performance of the platform. The four-wheel independent drive platform developed for this study verified the algorithm. The wheel slip detection and the compensation control algorithm of the platform are expected to improve the stability of trajectory tracking.