• Title/Summary/Keyword: Estimating Position

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Sensor Fusion for Underwater Navigation of Unmanned Underwater Vehicle (무인잠수정의 수중합법을 위한 센서융합)

  • Sur, Joo-No
    • Journal of the Korea Institute of Military Science and Technology
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    • v.8 no.4 s.23
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    • pp.14-23
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    • 2005
  • In this paper we propose a sensor fusion method for the navigation algorithm which can be used to estimate state vectors such as position and velocity for its motion control using multi-sensor output measurements. The output measurement we will use in estimating the state is a series of known multi-sensor asynchronous outputs with measurement noise. This paper investigates the Extended Kalman Filtering method to merge asynchronous heading, heading rate, velocity of DVL, and SSBL information to produce a single state vector. Different complexity of Kalman Filter, with. biases and measurement noise, are investigated with theoretically data from MOERI's SAUV. All levels of complexity of the Kalman Filters are shown to be much more close and smooth to real trajectories then the basic underwater acoustic navigation system commonly used aboard underwater vehicle.

RAY-SPACE INTERPOLATION BYWARPING DISPARITY MAPS

  • Moriy, Yuji;Yendoy, Tomohiro;Tanimotoy, Masayuki;Fujiiz, Toshiaki
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.583-587
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    • 2009
  • In this paper we propose a new method of Depth-Image-Based Rendering (DIBR) for Free-viewpoint TV (FTV). In the proposed method, virtual viewpoint images are rendered with 3D warping instead of estimating the view-dependent depth since depth estimation is usually costly and it is desirable to eliminate it from the rendering process. However, 3D warping causes some problems that do not occur in the method with view-dependent depth estimation; for example, the appearance of holes on the rendered image, and the occurrence of depth discontinuity on the surface of the object at virtual image plane. Depth discontinuity causes artifacts on the rendered image. In this paper, these problems are solved by reconstructing disparity information at virtual camera position from neighboring two real cameras. In the experiments, high quality arbitrary viewpoint images were obtained.

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A Study on Development of a Reconfigurable Mobile Robot and Dead-Reckoning Using Extended Kalman Filter (가변구조형 주행로봇 개발 및 확장형 칼만필터를 이용한 추측 항법에 대한 연구)

  • Kang, Bong-Soo;Yeo, Gee-Hwan
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.33 no.5
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    • pp.455-462
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    • 2009
  • This paper presents design concepts of a reconfigurable mobile robot for both of indoor and outdoor applications. A linkage mechanism and wheel-in-motors give the proposed mobile robot various driving modes in maneuver and good adaptability to irregular surface. Since the mobile robot receives multiple sensor signals from odometers and an orientation sensor, states related to the position and the orientation of the mobile robot are optimally estimated by an extended Kalman filter. Simulations and experimental results show that the performance of dead reckoning on estimating the pose of a mobile robot can be improved remarkably by the optimal state observer.

To collect the data of deduction of distance Estimating Position of Mobiles by Multi-Criteria Decision Making System (거리추정 데이터를 수집하여 공간적 의사결정을 이용한 이동물체 위치 인식 시스템)

  • Jang, Hae-Suk;Jung, Kyu-Cheol;Lee, Jin-Kwan;Park, Ki-Hong
    • Annual Conference of KIPS
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    • 2005.11a
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    • pp.1215-1218
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    • 2005
  • 이동물체의 인식기능은 인간을 대신하여 수행하기위한 컴퓨터비젼 시스템이다. 공간적 의사결정지원시스템(SDSS: Spatial Decision Support Systems)을 이용한 이동물체의 위치를 인식하는 시스템은 실세계의 복잡하고 다양한 조건들을 만족시키는 대안들을 도출시키고 보다 객관적이고 과학적으로 평가받는 연구가 될것이다.본 연구에서는 거리 추정 데이터를 수집하여 공간적 의사결정을 이용하여 이동 물체의 위치를 인식하는 방법을 제안한다.

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Pre-filtering and Location Estimation of a Loose Part

  • Kim, Jung-Soo;Kim, Tae-Wan;Joon Lyou
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.522-522
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    • 2000
  • In this paper, two pre-filtering techniques are presented for accurately estimating the impact location of a loose part. The reason why a pre-filterng technique Is necessary in a Loose Part Monitoring System is that the effects of background noise on the signal to noise ratio (SNR) can be reduced considerably resulting in improved estimation accuracy. The first method is to take d moving average operation in the time domain. The second one is to adopt band-pass filters designed in the frequency domain such as a Butterworth filter, Chebyshev filter I & II and an Elliptic Filter. To show the effectiveness, the impact test data (signals) from the YGN3 power plant are first preprocessed and then used to estimate the loose pan impact position. Resultantly. we observed that SNR is much improved and the average estimation error is below 7.5%.

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Sensor Fusion for Underwater Navigation of Unmanned Underwater Vehicle (무인잠수체의 수중항법을 위한 센서퓨전)

  • 주민근;서주노;송광섭;이판묵;홍석원;박영일
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.175-175
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    • 2000
  • In this Paper we propose a navigation algorithm which can be used to estimate state vectors such as position and velocity for its motion control using multi-sensor output measurements. The output measurement we will use in estimating the state is a series of known multi-sensor asynchronous outputs with measurement noise. This paper investigates the Extended Kalman Filtering method to merge asynchronous heading, heading rate, velocity of DVL, and SSBL information to produce a single state vector. Different complexity of Kalman Filter, with biases and measurement noise, are investigated with theoretically data from KRISO's AUV. All levels of complexity of the Kalman Filters are shown to be much more close and smooth to real trajectories then the basic underwater acoustic navigation system comment)'used aboard underwater vehicle.

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Predicting the Human Multi-Joint Stiffness by Utilizing EMG and ANN (인공신경망과 근전도를 이용한 인간의 관절 강성 예측)

  • Kang, Byung-Duk;Kim, Byung-Chan;Park, Shin-Suk;Kim, Hyun-Kyu
    • The Journal of Korea Robotics Society
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    • v.3 no.1
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    • pp.9-15
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    • 2008
  • Unlike robotic systems, humans excel at a variety of tasks by utilizing their intrinsic impedance, force sensation, and tactile contact clues. By examining human strategy in arm impedance control, we may be able to teach robotic manipulators human''s superior motor skills in contact tasks. This paper develops a novel method for estimating and predicting the human joint impedance using the electromyogram(EMG) signals and limb position measurements. The EMG signal is the summation of MUAPs (motor unit action potentials). Determination of the relationship between the EMG signals and joint stiffness is difficult, due to irregularities and uncertainties of the EMG signals. In this research, an artificial neural network(ANN) model was developed to model the relation between the EMG and joint stiffness. The proposed method estimates and predicts the multi joint stiffness without complex calculation and specialized apparatus. The feasibility of the developed model was confirmed by experiments and simulations.

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Tracking Algorithm of Vessel's Contour using ML estimation (ML 추정을 이용한 혈관 윤곽 추적 알고리듬)

  • Park, S.I.;Lee, J.S.;Koo, J.Y.;Hong, S.H.
    • Proceedings of the KOSOMBE Conference
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    • v.1997 no.11
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    • pp.150-153
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    • 1997
  • The proposed tracking algorithm approaches geometrical method or position, direction, width of vessel. This algorithm using continuity of vessel in spatial coordinates used to determine direction of the center point, after estimating boundary point in dynamic region. Therefore the tracking of vessel's contour is tracked contour as direction of entire contour in coronary artery. This algorithm is automatically processed by DIP as a compared with conventional method, because searching area varies adaptively to allocate searching region from extracted information at past. And ML estimation expressed robust method or angiography as evaluating sample values after preprocessing.

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Remote Localization of an Underground Acoustic Source by a Passive Sonar System

  • Jarng, Soon-Suck
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.138-148
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    • 1998
  • The aim of the work described in this paper is to develop a complex underground acoustic system which detects and localizes the origin of an underground hammering sound using an array of hydrophones located about loom underground. Three different methods for the sound localization will be presented, a time-delay method, a power-attenuation method and a hybrid method. In the time-delay method, the cross correlation of the signals received from the way of sensors is used to calculate the time delays between those signals. In the power-attenuation method, the powers of the received signals provide a measure of the distances of the source from the sensors. A new hybrid method has been developed for estimating the origin of the underground acoustic source by coupling both methods. The Nelder-Meade simplex search algorithm is then used to numerically estimate the position of the source in those methods. For each method the sound localization is carried out in three dimensions underground. The distance between the true and estimated origins of the source is in some cases less than 6m for a search area of radius 250m.

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Docking System for Unmanned Underwater Vehicle using Reduced Signal Strength Indicator (전자기파의 감쇄신호를 이용한 무인 잠수정의 도킹시스템 개발)

  • Lee, Gi-Hyeon;Kim, Jin-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.9
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    • pp.830-836
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    • 2012
  • According to increasing the importance of underwater environments, the needs of UUV are growing. This paper represents the mechanism and algorithm of UUV docking system with 21-inch torpedo tubes for military submarines as a docking station. To improve the reliability of the docking, torpedo tubes launch a wired ROV and next the ROV combined with UUV is retrieved. For estimating the relative position between the ROV and UUV, in this paper, combining RF sensors and vision system is proposed. The RSSI method of RF sensors is used to estimate the distance and the optical image is combined for the directional information.