• 제목/요약/키워드: Sensor fusion

검색결과 815건 처리시간 0.035초

이동 로봇 절대위치 추적 제어 시스템 (Mobile robot absolute position tracking system)

  • 최현승;현웅근
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.1811-1812
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    • 2008
  • This paper represents a absolute position tracking system with sensor fusion and PD-gain. this paper presents an accurate localization method by relative and absolute sensor fusion and PD control for position tracking of mobile robot. we developed a sensor based absolution position tracking and smooth moving algorithm using this algorithm.

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MULTI SENSOR DATA FUSION FOR IMPROVING PERFORMANCE AND RELIABILITY OF FULLY AUTOMATED MULTIPASS WELDING

  • Beattie, R.J.
    • 대한용접접합학회:학술대회논문집
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    • 대한용접접합학회 2002년도 Proceedings of the International Welding/Joining Conference-Korea
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    • pp.336-341
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    • 2002
  • Recent developments in sensor hardware and in advanced software have made it feasible to consider automating some of the most difficult welding operations. This paper describes some techniques used to automate successfully multipass submerged arc welding operations typically used in pressure vessel manufacture, shipbuilding, production of offshore structures and in pipe mills.

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네트워크 기반 자율이동로봇을 위한 장애물 회피 알고리즘 개발 (Development of an Obstacle Avoidance Algorithm for a Network-based Autonomous Mobile Robot)

  • 김홍열;김대원;김홍석;손수경
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권5호
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    • pp.291-299
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    • 2005
  • An obstacle avoidance algorithm for a network-based autonomous mobile robot is proposed in this paper. The obstacle avoidance algorithm is based on the VFH(Vector Field Histogram) algorithm and two delay compensation methods with the VFH algorithm are proposed for a network-based robot with distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the environmental sensor information is compensated by prospection with acquired environmental sensor information, measured network delays, and the kinematic model of the robot. The compensated environmental sensor information is used for building polar histogram with the VFH algorithm. Secondly, a sensor fusion algorithm for localization of the robot is proposed to compensate the delay of odometry sensor information and the delay of environmental sensor information. Through some simulation tests, the performance enhancement of the proposed algorithm in the viewpoint of efficient path generation and accurate goal positioning is shown here.

가스절연기기의 부분방전검출을 위한 SWNT-UHF 융합센서 (SWNT-UHF Fusion Sensor for GIS Partial Discharge Detection)

  • 이상욱;장용무;백승현;이종철
    • 한국전기전자재료학회:학술대회논문집
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    • 한국전기전자재료학회 2010년도 하계학술대회 논문집
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    • pp.120-120
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    • 2010
  • To detect the PD events, we have studied a fusion sensor, the UHF sensor and the single-walled carbon nanotube(SWNT) gas sensor. We are accustomed to the UHF sensor which have employed to detect the partial discharges in apparatus GIS-like. But the SWNT gas sense is a newly way proposed to detect the partial discharges. In this study, we monitored not only the changes of the electrical conductance of the SWNT sensors in responding to the PD events but also the signal of the UHF sensor at the same time with IEC 60270 standard method for reference on the partial discharge events.

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Information-Theoretic Approaches for Sensor Selection and Placement in Sensor Networks for Target Localization and Tracking

  • Wang Hanbiao;Yao Kung;Estrin Deborah
    • Journal of Communications and Networks
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    • 제7권4호
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    • pp.438-449
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    • 2005
  • In this paper, we describes the information-theoretic approaches to sensor selection and sensor placement in sensor net­works for target localization and tracking. We have developed a sensor selection heuristic to activate the most informative candidate sensor for collaborative target localization and tracking. The fusion of the observation by the selected sensor with the prior target location distribution yields nearly the greatest reduction of the entropy of the expected posterior target location distribution. Our sensor selection heuristic is computationally less complex and thus more suitable to sensor networks with moderate computing power than the mutual information sensor selection criteria. We have also developed a method to compute the posterior target location distribution with the minimum entropy that could be achieved by the fusion of observations of the sensor network with a given deployment geometry. We have found that the covariance matrix of the posterior target location distribution with the minimum entropy is consistent with the Cramer-Rao lower bound (CRB) of the target location estimate. Using the minimum entropy of the posterior target location distribution, we have characterized the effect of the sensor placement geometry on the localization accuracy.

융합 센서 네트워크 정보로 보정된 관성항법센서를 이용한 추측항법의 위치추정 향상에 관한 연구 (Study on the Localization Improvement of the Dead Reckoning using the INS Calibrated by the Fusion Sensor Network Information)

  • 최재영;김성관
    • 제어로봇시스템학회논문지
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    • 제18권8호
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    • pp.744-749
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    • 2012
  • 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.

수동 소나 쌍을 이용한 에너지 인식 분산탐지 체계의 설계 및 성능 분석 (Design and Performance Analysis of Energy-Aware Distributed Detection Systems with Two Passive Sonar Sensors)

  • 도주환;김송근;홍순목
    • 대한전자공학회논문지SP
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    • 제46권4호
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    • pp.139-147
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    • 2009
  • 이 논문에서는 한 쌍의 수동 광대역 소나로 구성된 병렬구조 분산센서 망에 적용할 수 있는 에너지 인식 분산탐지 체계의 설계 및 성능분석에 대해 검토한다. 이 분산탐지기는 융합규칙으로 AND 규칙과 OR 규칙을 사용하였다. 이 경우 각 센서노드의 문턱값 규칙은 전체 분산센서망의 탐지확률을 최대로 하는 UMP(uniformly most powerful)임을 증명하였다. 그리고 소나 체계에서 오경보에 의해 발생하는 에너지 비용을 제한 조건으로 주었을 때, 탐지확률을 최대화하는 센서노드의 최적 문턱값이 갖는 특성을 이론적으로 검토하였다. 나아가 신호 강도, 에너지 비용에 대한 제한조건, 센서노드 사이의 간격등이 탐지성능에 미치는 영향을 수치실험을 통해 분석하였다.

영상처리와 센서융합을 활용한 지능형 6족 이동 로봇 (Intelligent Hexapod Mobile Robot using Image Processing and Sensor Fusion)

  • 이상무;김상훈
    • 제어로봇시스템학회논문지
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    • 제15권4호
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    • pp.365-371
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    • 2009
  • A intelligent mobile hexapod robot with various types of sensors and wireless camera is introduced. We show this mobile robot can detect objects well by combining the results of active sensors and image processing algorithm. First, to detect objects, active sensors such as infrared rays sensors and supersonic waves sensors are employed together and calculates the distance in real time between the object and the robot using sensor's output. The difference between the measured value and calculated value is less than 5%. This paper suggests effective visual detecting system for moving objects with specified color and motion information. The proposed method includes the object extraction and definition process which uses color transformation and AWUPC computation to decide the existence of moving object. We add weighing values to each results from sensors and the camera. Final results are combined to only one value which represents the probability of an object in the limited distance. Sensor fusion technique improves the detection rate at least 7% higher than the technique using individual sensor.

센서 융합을 이용한 MAF 공정 특성 분석 (Characterization of Magnetic Abrasive Finishing Using Sensor Fusion)

  • 김설빔;안병운;이성환
    • 대한기계학회논문집A
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    • 제33권5호
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    • pp.514-520
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    • 2009
  • In configuring an automated polishing system, a monitoring scheme to estimate the surface roughness is necessary. In this study, a precision polishing process, magnetic abrasive finishing (MAF), along with an in-process monitoring setup was investigated. A magnetic tooling is connected to a CNC machining to polish the surface of stavax(S136) die steel workpieces. During finishing experiments, both AE signals and force signals were sampled and analysed. The finishing results show that MAF has nano scale finishing capability (upto 8nm in surface roughness) and the sensor signals have strong correlations with the parameters such as gap between the tool and workpiece, feed rate and abrasive size. In addition, the signals were utilized as the input parameters of artificial neural networks to predict generated surface roughness. Among the three networks constructed -AE rms input, force input, AE+force input- the ANN with sensor fusion (AE+force) produced most stable results. From above, it has been shown that the proposed sensor fusion scheme is appropriate for the monitoring and prediction of the nano scale precision finishing process.