• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.1348-1351
• /
• 1997

The federated Kaman filter(FKF) is being widely used in many multisensor navigatiion systems. It is know that the FKF has advantages of simplicity and fault-tolerance over other decentralized filter techniques. In this paper, optimal and suboptimal FKF configuratiions are mentioned and a covariance analysis technique for the suboptimal FKF is newly presented. The suboptimal FKF configuration, known as No-reset(NR) mode, has better fault tolerance capability than the optimal FKF coniguratioin. In the suggested technique, a suboptimal fusion process of FKF is considered a swell as suboptimal gains of local filters. An upper boun of error covariance for suboptimal FKF is derived. Also, it is mathematically shown that this bound is smaller thanexisting bound in the literatrue. A vehicle-navigaion system is designed using the FKF. In thissystem, a map constraing equation is introduced and used as a measurement equatioin of Kalman filter. Performance analysis is done by the suggested covariance analysis techniques.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
• /
• pp.107-109
• /
• 2003

Optical sensor-based land cover categories produce spectral signature confusion along with degraded classification accuracy. In the classification tasks, the goal of fusing data from different sensors is to reduce the classification error rate obtained by single source classification. This paper describes the result of land cover/land use classification derived from solely of Landsat TM (TM) and multisensor image fusion between JERS 1 SAR (JERS) and TM data. The best radar data manipulation is fused with TM through various techniques. Classification results are relatively good. The highest Kappa Coefficient is derived from classification using principal component analysis-high pass filtering (PCA+HPF) technique with the Overall Accuracy significantly high.

• 한국음향학회:학술대회논문집
• /
• 한국음향학회 2004년도 추계학술발표대회논문집 제23권 2호
• /
• pp.475-478
• /
• 2004

본 논문에서는 multistatic 소나망의 효과도 분석을 하였다. 특히 본 논문에서는 multistatic 소나망의 탐지 성능 분석을 통해 효용성을 알아보았다. Multistatic 소나망은 송/수신기가 분리된 일종의 다중 분산 센서 시스템으로, 최적의 탐지 성능을 갖기 위해서는 적절한 융합 규칙 및 센서 배치가 필요하다. 분산 센서 융합 기법으로 bayesian 결정 기법을 기반으로 한 융합 기법을 적용하였으며, 실제 해양 환경하에서의 탐지 성능 분석을 위해 개선된 bistatic 표적 강도 모델과 거리 종속 전송 손실 모델을 이용한 multistatic 소나망 탐지 모델을 제안하였다. 기존 소나망과의 모의 비교 실험을 통해 multistatic 소나망의 우수성을 입증하였다.

• 한국산업융합학회 논문집
• /
• 제21권3호
• /
• pp.125-131
• /
• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles using multi-ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.628-631
• /
• 1996

This paper proposes a surface recognition algorithm which determines the types of contact surfaces by fusing the information collected by the multisensor system, consisted of the optical tactile and force/torque sensors. Since the image shape measured by the optical tactile sensor system, which is used for determining the surface type, varies depending on the forces provided at the measuring moment, the force information measured by the f/t sensor takes an important role. In this paper, an image contour is represented by the long and short axes and they are fuzzified individually by the membership function formulated by observing the variation of the lengths of the long and short axes depending on the provided force. The fuzzified values of the long and short axes are fused using the average Minkowski's distance. Compared to the case where only the contour information is used, the proposed algorithm has shown about 14% of enhancement in the recognition ratio. Especially, when imposing the optimal force determined by the experiments, the recognition ratio has been measured over 91%.

• 센서학회지
• /
• 제5권4호
• /
• pp.57-70
• /
• 1996

Motion can be estimated continuously from each sensor through the analysis of the instantaneous states of an object. This paper is aimed to introduce a method to estimate the general 3D motion of a planar object from the instantaneous states of an object using multi-sensor data fusion. The instantaneous states of an object is estimated using the linear feedback estimation algorithm. The motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown planar object. We present a fusion algorithm which combines averaging and deciding. With the assumption that the motion is smooth, the approach can handle the data sequences from multiple sensors with different sampling times. Simulation results show proposed algorithm is advantageous in terms of accuracy, speed, and versatility.

• 한국항행학회논문지
• /
• 제15권4호
• /
• pp.556-561
• /
• 2011

일반적으로 비선형 시스템에서 particle filter가 Kalman Filter보다 표적추적 성능이 뛰어나다고 알려져 있다. 그러나 particle filter는 많은 연산량을 요구하는 단점이 있다. 본 논문에서는 particle filter 보다 적은 particle의 수, 즉 적은 연산량으로 동일한 성능을 가지는 Rao-Blackwellized particle filter의 모델의 민감성을 줄인 Rao-Blackwellized Multiple Model Particle Filter(RBMMPF)의 알고리즘을 소개하고 이에 다중센서 정보를 융합하는 자료융합 기법을 적용하였다. 시뮬레이션을 통해 단일센서 정보를 이용한 RBMMPF 표적추적 성능과 다중센서정보를 융합한 RBMMPF의 표적추적 성능을 비교, 분석하였다.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2000년도 추계학술대회논문집 - 한국공작기계학회
• /
• pp.454-459
• /
• 2000

The high hardened materials that are remarkable in aspects of durability have been used for die and mold industry. As the high hardened materials are hard to machine, the high-speed machining is essential to manufacture these materials. Currently, in the general turning and milling, experiments to the tool wear monitoring have studied, but those have not applied in high-speed machining. In this study, the cutting mechanism was analysed by the cutting force according to cutting conditions, and the parameters to monitor the tool wear were selected from the tendency of the cutting force and acceleration according to cutting length in the high-speed machining of the high hardened materials(STD11).

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1997년도 하계학술대회 논문집 B
• /
• pp.414-417
• /
• 1997

We propose a decentralized $H_{\infty}$ state estimation method in the multisensor state estimation problem. The proposed method bounds the maximum energy gain from unknown external disturbances to the estimation errors in the suboptimal case. And we formulate the decentralized state estimation method in the general case of different global and local models using alternative gain equation of the $H_{\infty}$ state estimator which can calculate global state estimates from the the linear combination of local state estimates. In addition, the proposed update equation between global and local Riccati solutions can reduce unnecessary calculation burden efficiently.

• International Journal of Control, Automation, and Systems
• /
• 제3권1호
• /
• pp.15-31
• /
• 2005

Nowadays, the road safety is an important research field. One of the principal research topics in this field is the vehicle localization in the road network. This article presents an approach of multi sensor fusion able to locate a vehicle with a decimeter precision. The different informations used in this method come from the following sensors: a low cost GPS, a numeric camera, an odometer and a steer angle sensor. Taking into account a complete model of errors on GPS data (bias on position and nonwhite errors) as well as the data provided by an original approach coupling a vision algorithm with a precise numerical map allow us to get this precision.