{"title":"Tutorial A: Sensor data fusion, principles and applications","authors":"B. Moshiri","doi":"10.1109/ISOT.2010.5687380","DOIUrl":null,"url":null,"abstract":"Sensor Data Fusion deals with the synergistic combination of data made available by various sources such as sensors in order to provide a better understanding of a given scene. The use of sensor/data fusion concept has advantages such as “Redundancy”, “Complementary”, “Timeliness” and “Less Costly Information”. The following issues will be presented in this tutorial: • Background• Sensor/Data fusion overview • Definition & Formulation • Fusion: A Fission inversion model • Fusion characterization: ○ Application domain ○ Fusion objective ○ Fusion process input/output characteristics ○ Sensor suite configuration • Different Techniques of Sensor fusion ○ Conventional Approaches ○ Knowledge based Systems/Intelligent Approaches • Different Level Fusion Architectures • Different Fusion Model Architectures • Integration of Mechatronics & Sensor Data Fusion • Some typical applications of Sensor Data Fusion in Robotics & Mechatronics.","PeriodicalId":91154,"journal":{"name":"Optomechatronic Technologies (ISOT), 2010 International Symposium on : 25-27 Oct. 2010 : [Toronto, ON]. International Symposium on Optomechatronic Technologies (2010 : Toronto, Ont.)","volume":"73 1","pages":"1-2"},"PeriodicalIF":0.0000,"publicationDate":"2010-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Optomechatronic Technologies (ISOT), 2010 International Symposium on : 25-27 Oct. 2010 : [Toronto, ON]. International Symposium on Optomechatronic Technologies (2010 : Toronto, Ont.)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISOT.2010.5687380","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

Sensor Data Fusion deals with the synergistic combination of data made available by various sources such as sensors in order to provide a better understanding of a given scene. The use of sensor/data fusion concept has advantages such as “Redundancy”, “Complementary”, “Timeliness” and “Less Costly Information”. The following issues will be presented in this tutorial: • Background• Sensor/Data fusion overview • Definition & Formulation • Fusion: A Fission inversion model • Fusion characterization: ○ Application domain ○ Fusion objective ○ Fusion process input/output characteristics ○ Sensor suite configuration • Different Techniques of Sensor fusion ○ Conventional Approaches ○ Knowledge based Systems/Intelligent Approaches • Different Level Fusion Architectures • Different Fusion Model Architectures • Integration of Mechatronics & Sensor Data Fusion • Some typical applications of Sensor Data Fusion in Robotics & Mechatronics.
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A:传感器数据融合,原理和应用
传感器数据融合处理各种来源(如传感器)提供的数据的协同组合,以便更好地理解给定场景。采用传感器/数据融合概念具有“冗余”、“互补”、“及时性”和“信息成本更低”等优点。以下问题将在本教程中提出:•背景•传感器/数据融合概述•定义与公式•融合:裂变反转模型•融合表征:〇应用领域〇融合目标〇融合过程输入/输出特性〇传感器组件配置•传感器融合的不同技术〇传统方法〇基于知识的系统/智能方法•不同层次的融合架构•不同的融合模型架构•机电一体化与传感器数据融合的集成•传感器数据融合在机器人与机电一体化中的一些典型应用。
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