위성 영상감시 센서망을 위한 스마트 비젼 센서

김원호,임재유 한국위성정보통신학회 2015 한국위성정보통신학회논문지 Vol.10 No.2

본 논문은 위성통신 기반의 위성 영상감시 센서 네트워크 적용을 위한 스마트 비젼 센서에 대해 기술한다. 스마트 비젼센서 단말은 현장에서 산불, 연기, 침입자 움직임 등의 이벤트를 자동감지하면서 높은 성능 신뢰도, 견고한 하드웨어 내구성, 용이한 유지보수, 끊김없는 통신유지 기능들이 요구된다. 이러한 요구사항들을 만족시키기 위하여 스마트 비젼 센서가 내장된 초소형 위성통신 단말 을 제안하며 위성 송수신 기능과 더불어 고 신뢰도의 임베디드 영상분석 및 영상압축 기능을 처리한다. 제안하는 비젼 센서 알고리 즘의 컴퓨터 시뮬레이션과 비젼 센서 시제품 시험을 통하여 영상감시 성능을 검증하였으며 실용성을 확인하였다. In this paper, satellite communication based video surveillance system that consisted of ultra-small aperture terminals with small-size smart vision sensor is proposed. The events such as forest fire, smoke, intruder movement are detected automatically in field and false alarms are minimized by using intelligent and high-reliable video analysis algorithms. The smart vision sensor is necessary to achieve high-confidence, high hardware endurance, seamless communication and easy maintenance requirements. To satisfy these requirements, real-time digital signal processor, camera module and satellite transceiver are integrated as a smart vision sensor-based ultra-small aperture terminal. Also, high-performance video analysis and image coding algorithms are embedded. The video analysis functions and performances were verified and confirmed practicality through computer simulation and vision sensor prototype test.

Performance Analysis of an INS/SLAM Integrated System with Respect to the Geometrical Arrangement of Multiple Vision Sensors

천세범,이영재,원대희,허문범 제어·로봇·시스템학회 2012 International Journal of Control, Automation, and Vol.10 No.2

A single vision system is the simplest vision-based method of simultaneous localization and mapping (SLAM) but it cannot reduce navigation errors that occur in the direction of the optical axis of vision sensors. Moreover, the limited observation area of vision sensors sometimes leads to failure in tracking a feature point. A vision sensor–based inertial navigation system INS/SLAM integrated system performs better with multiple vision sensors than with a single vision sensor because the observation area is wider and the impact of the sensitivity of the vision sensors is considerably smaller. However, the geometrical arrangement of multiple vision sensors induces navigation errors. This paper analyzes how the performance of the vision sensor–based INS/SLAM integrated system varies in relation to the geometrical arrangement of multiple vision sensors and the observation area of the vision sensors. The analysis shows that vertical navigation errors decline when the vision sensors are aimed horizontally, and that horizontal navigation errors decline in a similar manner when the vision sensor is aimed vertically; moreover, this behavior is especially evident when the level of sensitivity peaks in the horizontal direction.

융합 센서 네트워크 정보로 보정된 관성항법센서를 이용한 추측항법의 위치추정 향상에 관한 연구

최재영(Jae-Young Choi),김성관(Sung-Gaun Kim) 제어로봇시스템학회 2012 제어·로봇·시스템학회 논문지 Vol.18 No.8

In this paper, we suggest that how to improve an accuracy of mobile robot’s localization by using the sensor network information which fuses the machine vision camera, encoder and IMU sensor. The heading value of IMU sensor is measured using terrestrial magnetism sensor which is based on magnetic field. However, this sensor is constantly affected by its surrounding environment. So, we isolated template of ceiling using vision camera to increase the sensor’s accuracy when we use IMU sensor; we measured the angles by pattern matching algorithm; and to calibrate IMU sensor, we compared the obtained values with IMU sensor values and the offset value. The values that were used to obtain information on the robot’s position which were of Encoder, IMU sensor, angle sensor of vision camera are transferred to the Host PC by wireless network. Then, the Host PC estimates the location of robot using all these values. As a result, we were able to get more accurate information on estimated positions than when using IMU sensor calibration solely.

차량용 통합 센서 모듈 제어를 위한 시뮬레이터 개발

전진영 ( Jin Young Jeon ),박정연 ( Jeong Yeon Park ),변형기 ( Hyung Gi Byun1 ) 한국센서학회 2013 센서학회지 Vol.22 No.1

The integrated sensor module of vehicle combines the functions of rain sensor, auto defog sensor, and sun angle sensor into a single module. These functions originally were applied to work separatively. This integrated sensor module should meet the each performance which appears from the individual modules up to the same level or higher. Therefore, it is important to verify the stability and the accuracy considering the characteristics of the integrated sensor module according to various situations. For the verification, we need to use the actual data of integrated sensor module measured but, a lot of time and money is needed to collect data measured under various circumstances when operating. Thus, through the development of this simulator for the control of the integrated sensor module, we can use it effectively for the initial verification of integrated sensor module by implementing the various situations. In this paper, the simulator for controlling the integrated sensor module which combines vision-based rain sensor, auto defog sensor, auto light sensor, and sun angle sensor has been developed.

비전과 초음파 센서를 이용한 임의 환경에서 2족 로봇의 경로계획을 위한 맵 빌딩

차재환(J. W. Cha),김동일(D. I. Kim),기창두(C. D. Kee) 한국정밀공학회 2004 한국정밀공학회 학술발표대회 논문집 Vol.2004 No.10월

This paper describes map building for the path planning to avoid obstacles with vision sensor and ultrasonic sensor. We get the 2 dimensional information from the processed images of CCD sensor and 1 dimensional range information from ultrasonic sensor. I proposed a way to generate the map which contains these two kinds of information in the program. And we made the biped robot which have 20 DOF with these sensors and get good experimental result to prove the validity of the proposed method.

Parametric study of sensor placement for vision-based relative navigation system of multiple spacecraft

Jeong, Junho,Kim, Seungkeun,Suk, Jinyoung Elsevier 2017 Acta astronautica Vol.141 No.-

<P><B>Abstract</B></P> <P>In order to overcome the limited range of GPS-based techniques, vision-based relative navigation methods have recently emerged as alternative approaches for a high Earth orbit (HEO) or deep space missions. Therefore, various vision-based relative navigation systems use for proximity operations between two spacecraft. For the implementation of these systems, a sensor placement problem can occur on the exterior of spacecraft due to its limited space. To deal with the sensor placement, this paper proposes a novel methodology for a vision-based relative navigation based on multiple position sensitive diode (PSD) sensors and multiple infrared beacon modules. For the proposed method, an iterated parametric study is used based on the farthest point optimization (FPO) and a constrained extended Kalman filter (CEKF). Each algorithm is applied to set the location of the sensors and to estimate relative positions and attitudes according to each combination by the PSDs and beacons. After that, scores for the sensor placement are calculated with respect to parameters: the number of the PSDs, number of the beacons, and accuracy of relative estimates. Then, the best scoring candidate is determined for the sensor placement. Moreover, the results of the iterated estimation show that the accuracy improves dramatically, as the number of the PSDs increases from one to three.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A sensor placement methodology is proposed for vision-based relative navigation. </LI> <LI> Multiple PSDs/beacons are used for relative navigation of satellite formation. </LI> <LI> Farthest point optimization (FPO) is applied to configure sensor locations. </LI> <LI> The methodology is comprised of the FPO and constrained Extended Kalman filter. </LI> <LI> The performance of relative navigation are analyzed depending on sensor locations. </LI> </UL> </P>

멀티센서 시스템을 이용한 3차원 형상의 기상측정에 관한 연구

권양훈,윤길상,조명우 한국공작기계학회 2002 한국공작기계학회 추계학술대회논문집 Vol.2002 No.-

This paper presents a multiple sensor system for rapid and high-precision coordinate data acquisition in the OMM (On-machine measurement) process. In this research, three sensors (touch probe, laser, and vision sensor) are integrated to obtain more accurate measuring results. The touch-type probe has high accuracy, but is time-consuming. Vision sensor can acquire many point data rapidly over a spatial range but its accuracy is less than other sensors. Also, it is not possible to acquire data for invisible areas. Laser sensor has medium accuracy and measuring speed among the sensors, and can acquire data for sharp or rounded edge and the features with very small holes and/or grooves. However, it has range-constraints to use because of its system structure. In this research, a new optimum sensor integration method for OMM is proposed by integrating the multiple-sensor to accomplish more effective inspection planning. To verify the effectiveness of the proposed method, simulation and experimental works are performed, and the results are analyzed.

인간형 로봇의 자세제어를 위한 안정화 제어를 이용한 퓨전 센서 시스템 개발

박진성(Jinseong Park),박영진(Youngjin Park),박윤식(Youn-Sik Park),홍덕화(Deokhwa Hong),이현기(Hyunki Lee),조형석(Hyungsuck Cho) 대한기계학회 2009 대한기계학회 춘추학술대회 Vol.2009 No.11

Position estimating fusion sensor system is proposed to control attitude of the humanoid robot. To apply vision sensor to control the attitude of the humanoid robot we should solve limitations of vision sensor which are low sampling frequency, estimation time delay and limited estimation range. Sensor fusion with MEMS gyro sensor can remove estimation time delay and increase sampling frequency. Stabilization control can remove limited estimation range by regulating of the vision sensor to initial position all the time. In this research, humanoid robot is modeled as one axis inverted pendulum which represents a leg of the humanoid robot.

스테레오 비전 센서 기반 프리팹 강구조물 조립부 형상 품질 평가

김종혁,전해민 한국전산구조공학회 2024 한국전산구조공학회논문집 Vol.37 No.3

본 논문에서는 스테레오 비전 센서를 이용한 프리팹 강구조물(PSS: Prefabricated Steel Structures)의 조립부 형상 품질 평가 기법을 소개한다. 스테레오 비전 센서를 통해 모형의 조립부 영상과 포인트 클라우드 데이터를 수집하였으며, 퍼지 기반 엣지 검출, 허프 변환 기반 원형의 볼트 홀 검출 등의 영상처리 알고리즘을 적용하여 조립부 영역의 볼트홀을 검출하였다. 영상 내 추출된 볼트홀 외곽선 위 세 점의 위치 정보에 대응되는 3차원 실세계 위치 정보를 깊이 영상으로부터 획득하였으며, 이를 기반으로 각 볼트홀의 3차원 중심 위치를 계산하였다. 통계적 기법 중 하나인 주성분 분석 알고리즘(PCA: Principal component analysis) 알고리즘을 적용함으로써 3차원 위치 정보를 대표하는 최적의 좌표축을 계산하였다. 이를 통해 센서의 설치 방향 및 위치에 따라 센서와 부재 간 평행이 아니더라도 안정적으로 볼트홀 간의 거리를 계측하도록 하였다. 각 볼트홀의 2차원 위치 정보를 기반으로 볼트홀의 순서를 정렬하였으며, 정렬된 볼트홀의 위치 정보를 바탕으로 인접한 볼트홀 간의 각 축의 거리 정보를 계산하여 조립부 볼트홀 위치 중심의 형상 품질을 분석하였다. 측정된 볼트홀 간의 거리 정보는 실제 도면의 거리 정보와의 절대오차와 상대오차를 계산하여 성능 비교를 진행하였으며, 중앙값 기준 1mm 내의 절대오차와 4% 이내의 상대오차의 계측 성능을 확인하였다. This study presents a technique for assessing the dimensional quality of assembly parts in Prefabricated Steel Structures (PSS) using a stereo vision sensor. The stereo vision system captures images and point cloud data of the assembly area, followed by applying image processing algorithms such as fuzzy-based edge detection and Hough transform-based circular bolt hole detection to identify bolt hole locations. The 3D center positions of each bolt hole are determined by correlating 3D real-world position information from depth images with the extracted bolt hole positions. Principal Component Analysis (PCA) is then employed to calculate coordinate axes for precise measurement of distances between bolt holes, even when the sensor and structure orientations differ. Bolt holes are sorted based on their 2D positions, and the distances between sorted bolt holes are calculated to assess the assembly part's dimensional quality. Comparison with actual drawing data confirms measurement accuracy with an absolute error of 1mm and a relative error within 4% based on median criteria.

레이저포인터와 단일카메라를 이용한 거리측정 시스템

전영산(Yeongsan Jeon),박정근(Jungkeun Park),강태삼(Taesam Kang),이정욱(Jeong-Oog Lee) 한국항공우주학회 2013 韓國航空宇宙學會誌 Vol.41 No.5

최근에 소형무인기(small UAV)에 대한 관심이 증대되고 있는데, 이는 소형무인기가 비용대비 효율적이고 사람의 접근이 어려운 재난 환경 등에 적합하기 때문이다. 이러한 소형무인기에서 거리측정을 통한 매핑(mapping)은 필수적인 기술이다. 기존의 무인시스템 연구에서 거리 측정 센서는 주로 레이저 센서와 스테레오 비전 센서를 많이 사용하였다. 레이저 센서는 정확도와 신뢰성이 우수하지만 대부분 고가의 장비이고 스테레오 비전 센서는 구현이 용이하지만 무게 측면에서 소형무인기에 탑재하여 사용하기에는 적합하지 않다. 본 논문에서는 레이저 포인터와 단일 카메라를 사용하여 저가의 거리측정기를 구성하는 방안을 소개한다. 제안한 시스템을 이용하여 거리를 측정하고 이로부터 맵을 구성하는 실험을 수행하였고 실제 데이터와 비교 분석하여 시스템의 신뢰성을 검증하였다. Recently, many unmanned aerial vehicle (UAV) studies have focused on small UAVs, because they are cost effective and suitable in dangerous indoor environments where human entry is limited. Map building through distance measurement is a key technology for the autonomous flight of small UAVs. In many researches for unmanned systems, distance could be measured by using laser range finders or stereo vision sensors. Even though a laser range finder provides accurate distance measurements, it has a disadvantage of high cost. Calculating the distance using a stereo vision sensor is straightforward. However, the sensor is large and heavy, which is not suitable for small UAVs with limited payload. This paper suggests a low-cost distance measurement system using a laser pointer and a monocular vision sensor. A method to measure distance using the suggested system is explained and some experiments on map building are conducted with these distance measurements. The experimental results are compared to the actual data and the reliability of the suggested system is verified.