• 한국해양공학회지
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• 제29권5호
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• pp.392-397
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• 2015

An autonomous underwater vehicle (AUV) can perform flexible operations even in complex underwater environments because of its autonomy. Localization is one of the key components of this autonomous navigation. Because the inertial navigation system of an AUV suffers from drift, observing fixed objects in an inertial reference system can enhance the localization performance. In this paper, we propose a method of AUV localization using visual measurements of underwater structures. A camera measurement model that emulates the camera’s observations of underwater structures is designed in a particle filtering framework. Then, the particle weight is updated based on the extracted visual information of the underwater structures. The proposed method is validated based on the results of experiments performed in a structured basin environment.

• ETRI Journal
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• 제37권3호
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• pp.551-561
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• 2015

We propose a novel multiple-object tracking algorithm for real-time intelligent video surveillance. We adopt particle filtering as our tracking framework. Background modeling and subtraction are used to generate a region of interest. A two-step pedestrian detection is employed to reduce the computation time of the algorithm, and an iterative particle repropagation method is proposed to enhance its tracking accuracy. A matching score for greedy data association is proposed to assign the detection results of the two-step pedestrian detector to trackers. Various experimental results demonstrate that the proposed algorithm tracks multiple objects accurately and precisely in real time.

• International Journal of Contents
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• 제9권3호
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• pp.9-14
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• 2013

In this paper, we will examine single face tracking algorithms with scaling function in a mobile device. Face detection and tracking either in PC or mobile device with scaling function is an unsolved problem. Standard single face tracking method with particle filter has a problem in tracking the objects where the object can move closer or farther from the camera. Therefore, we create an algorithm which can work in a mobile device and perform a scaling function. The key idea of our proposed method is to extract the average of skin color in face detection, then we compare the skin color distribution between the detected face and the tracking face. This method works well if the face position is located in front of the camera. However, this method will not work if the camera moves closer from the initial point of detection. Apart from our weakness of algorithm, we can improve the accuracy of tracking.

• Nuclear Engineering and Technology
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• 제53권12호
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• pp.3979-3989
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• 2021

Several parametric effects on the magnetic collection have been evaluated considering dimension, strength of external magnetic field, injected velocity and particle concentration in the working fluid. Besides, accidental environments, expected in the containment of nuclear power plants, have also been addressed for the capture efficiency. The capture efficiency is especially enhanced with magnetic particle size and magnetic field strength through increased magnetic force; the non-magnetic coating thickness and fluid velocity hinder the magnetic collection. Based on the assessment, the magnetic withdrawal system can effectively capture magnetic particles even under accidental environments. Withdrawal of multifunctional magnetic particles or filtering of magnetic impurities can be effectively realized through the system.

• Nuclear Engineering and Technology
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• 제54권6호
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• pp.2107-2119
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• 2022

Accurate remaining useful life (RUL) prediction for critical components of nuclear power equipment is an important way to realize aging management of nuclear power equipment. The electric gate valve is one of the most safety-critical and widely distributed mechanical equipment in nuclear power installations. However, the electric gate valve's extended service in nuclear installations causes aging and degradation induced by crack propagation and leakages. Hence, it is necessary to develop a robust RUL prediction method to evaluate its operating state. Although the particle filter(PF) algorithm and its variants can deal with this nonlinear problem effectively, they suffer from severe particle degeneracy and depletion, which leads to its sub-optimal performance. In this study, we combined the whale algorithm with regularized particle filtering(RPF) to rationalize the particle distribution before resampling, so as to solve the problem of particle degradation, and for valve RUL prediction. The valve's crack propagation is studied using the RPF approach, which takes the Paris Law as a condition function. The crack growth is observed and updated using the root-mean-square (RMS) signal collected from the acoustic emission sensor. At the same time, the proposed method is compared with other optimization algorithms, such as particle swarm optimization algorithm, and verified by the realistic valve aging experimental data. The conclusion shows that the proposed method can effectively predict and analyze the typical valve degradation patterns.

• 제어로봇시스템학회논문지
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• 제19권8호
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• pp.682-687
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• 2013

Navigation is a crucial capability for all types of manned or unmanned vehicles. However, vehicle navigation in underwater environments still remains a challenging problem since GPS signals for position fixes are not available in the water. Terrain-referenced underwater navigation is an alternative navigation technique that utilizes geometric information of the subsea terrain to correct drift errors due to dead-reckoning or inertial navigation. Terrain-referenced navigation requires the description of an undulating terrain surface as a mathematical function or table, which often leads to a highly nonlinear estimation problem. Recently, PFs (Particle Filters), which do not require any restrictive assumptions about the system dynamics and uncertainty distributions, have been widely used for nonlinear filtering applications. However, PF has considerable computational requirements which used to limit its applicability to problems of relatively low state dimensions. This study proposes the use of a Rao-Blackwellized particle filter that is computationally more efficient than the standard PF for terrain-referenced underwater navigation involving a moderate number of states, and its performance is compared with that of the extended Kalman filter algorithm. The validity and feasibility of the proposed algorithm is demonstrated through numerical simulations.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권8호
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• pp.883-887
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• 2010

3D 얼굴 추적(Face tracking)은 보안감시, HCI(Human-Computer Interface), 엔터테인먼트(Entertainment)등 컴퓨터 비전과 관련된 여러 분야의 핵심 기술로서 많은 연구가 진행되고 있다. 하지만, 광범위한 응용분야에도 불구하고 3D 얼굴 추적의 기본적인 높은 연산 비용으로 인하여 그 응용 분야가 모바일 단말기 등의 저 사양 플랫폼에는 많은 한계가 있어왔다. 본 논문에서는 이러한 3D얼굴 추적의 연산 비용을 효과적으로 해결하고 폭 넓게 응용 분야를 확대하기 위하여 MLESAC(Maximum Likelihood Estimation by Sampling Consensus)을 이용한 움직임 추정(Motion Estimation) 기법과 기존의 파티클 필터(Particle Filter)를 결합하여 실행 속도 면에서 빠르면서도 성능 면에서도 우수한 3D 얼굴 추적 알고리즘을 제안한다.

• International Journal of Naval Architecture and Ocean Engineering
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• 제8권3호
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• pp.243-251
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• 2016

Autonomous Underwater Vehicles (AUVs) generally work in complex marine environments. Any fault in AUVs may cause significant losses. Thus, system reliability and automatic fault diagnosis are important. To address the actuator failure of AUVs, a fault diagnosis method based on the Gaussian particle filter is proposed in this study. Six free-space motion equation mathematical models are established in accordance with the actuator configuration of AUVs. The value of the control (moment) loss parameter is adopted on the basis of these models to represent underwater vehicle malfunction, and an actuator failure model is established. An improved Gaussian particle filtering algorithm is proposed and is used to estimate the AUV failure model and motion state. Bayes algorithm is employed to perform robot fault detection. The sliding window method is adopted for fault magnitude estimation. The feasibility and validity of the proposed method are verified through simulation experiments and experimental data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권4호
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• pp.1200-1215
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• 2023

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

• 항공우주시스템공학회지
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• 제10권1호
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• pp.8-14
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• 2016

The optimal estimation of a bearing only target tracking problem be achieved through the solution of the Fokker-Planck equation and the Bayesian update. Recently, a nonlinear filtering algorithm using a direct quadrature method of moments in which the associated Fokker-Planck equation can be propagated efficiently and accurately was proposed. Although this approach has demonstrated its promising in the field of nonlinear filtering in several examples, the "degeneracy" phenomenon, similar to that which exists in a typical particle filter, occasionally appears because only the weights are updated in the modified Bayesian rule in this algorithm. Therefore, in this paper to enhance the performance, a more stable measurement update process based upon the update equation in the Extended Kalman filters and a more accurate initialization and re-sampling strategy for weight and abscissas are proposed. Simulations are used to show the effectiveness of the proposed filter and the obtained results are promising.