Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480)最新文献_第4页

A generalized look-ahead method for adaptive multiple sequential data fusion and decision making 一种自适应多序列数据融合与决策的广义前瞻方法

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815989

T. Chen, R. Luo

{"title":"A generalized look-ahead method for adaptive multiple sequential data fusion and decision making","authors":"T. Chen, R. Luo","doi":"10.1109/MFI.1999.815989","DOIUrl":"https://doi.org/10.1109/MFI.1999.815989","url":null,"abstract":"This paper presents a formulation of look-ahead decision-making algorithm for sensor fusion systems across levels with the I/O mode characterizations of feature in-decision out or data in-decision out methods. The sequential data fusion is conducted through a dynamic behavior modeling method capable of estimating the observed system parameters from the raw sensory measurements over period of time. The temporal estimated model is used for forward prediction of the observed system output for decision-making. A self-evaluation method to estimate the prediction quality is used to generate the individual decision confidence for final decision integration which is conducted through a multi-layered fuzzy linguistic reasoning engine. The validity of the proposed technique is confirmed by experimental results in which we perform sensor fusion of ultrasonic range data and vision detection information for motion decision on target tracking applications. The experimental results demonstrate the feasibility and accuracy of the multisensor fusion method.","PeriodicalId":148154,"journal":{"name":"Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125899569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Control system for spherical direct drive actuators with Hall sensors [mobile robots] 带有霍尔传感器的球形直接驱动执行器控制系统[移动机器人]

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815986

S. Sokolov, O. V. Trifonov, V.S. Yaroshevsky

引用次数: 2

Inspection of steel sheets based on CCD image sensors 基于CCD图像传感器的钢板检测

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815967

P. Marino, M. Domínguez, M. Alonso

引用次数: 5

An efficient bias estimation method in multisensor fusion for navigation by adaptive prototype selection in a bank of Kalman filters 一种基于卡尔曼滤波器自适应原型选择的导航多传感器融合中的有效偏差估计方法

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.816003

I. Sen, Sunmee Kang, Chein-I. Chang, Hanseok Ko

{"title":"An efficient bias estimation method in multisensor fusion for navigation by adaptive prototype selection in a bank of Kalman filters","authors":"I. Sen, Sunmee Kang, Chein-I. Chang, Hanseok Ko","doi":"10.1109/MFI.1999.816003","DOIUrl":"https://doi.org/10.1109/MFI.1999.816003","url":null,"abstract":"A navigation system usually employs multiple sensors to combine the strength of individual sensors such as GPS, gyroscope, and accelerometer. However, the multiple sensor fusion for navigation objectives encounters noise and time-variant bias present in individual sensor measurement. This paper proposes an efficient method to estimate the unknown bias for cancellation in a fused navigation system involving multiple sensors using an adaptive bias prototype selection employed over a bank of parallel Kalman filters. The conventional method which focuses on a special case of bias characteristics revolving around the semi-Markov process model is recognized for its excessive computation if the bias prototype set is chosen too large. This means that a huge discrete set of bias is needed to obtain the bias estimation accurately. Focusing on solving the problem of large bias prototypes, we propose a two-step selection process: (1) the decision part that locks on a new bias set from estimated bias covariance and (2) the balance part that regulates the newly selected bias set to enable a smooth transition under inadvertent bias overshoots. Simulation results show a substantial improvement in bias estimation accuracy while maintaining a minimal computation compared to the nonadaptive randomly switching bias estimators.","PeriodicalId":148154,"journal":{"name":"Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480)","volume":"AES-5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126503705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Visual tracking of unknown moving object by adaptive binocular visual servoing 基于自适应双目视觉伺服的未知运动目标视觉跟踪

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815998

M. Asada, T. Tanaka, K. Hosoda

引用次数: 27

The role of sensing in motion stability of mobile robots 传感在移动机器人运动稳定性中的作用

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815966

Jindong Tan, N. Xi, W. Kang

引用次数: 0

A review of high-level multisensor fusion: approaches and applications 高水平多传感器融合研究进展:方法与应用

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815960

Ren C. Luo, K. L. Su

引用次数: 34

Object recognition using local EGI and 3D models with M-estimators 基于局部EGI和带m估计量的三维模型的目标识别

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815969

K. Kawarnura, K. Hasegawa, O. Yamashita, Y. Sato, K. Ikeuchi

引用次数: 6

A MEMS high-speed rotation measurement system with MCNC fabricated motion and reference sensors using wireless transmission 一种采用无线传输的MEMS高速旋转测量系统，由MCNC制造运动和参考传感器

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815994

W. Sun, T. Mei, W.-T. Ho, W.J. Li

引用次数: 3

Achieving efficient multi-sensory perception through predictive correction of monitoring errors 通过预测修正监测误差，实现高效的多感官感知

Proceedings. 1999 IEEE/SICE/RSJ. International Conference on Multisensor Fusion and Integration for Intelligent Systems. MFI'99 (Cat. No.99TH8480) Pub Date : 1999-08-15 DOI: 10.1109/MFI.1999.815971

T. Celinski, B. McCarragher

引用次数: 1