Sensor Fusion Algorithms培训

课程编码

sfa

课程时长

14 小时 通常来说是2天,包括中间休息。

课程概览

传感器融合是来自多个传感器的数据的组合和整合,以提供更准确,可靠和上下文的数据视图。 传感器融合实施需要算法来过滤和集成不同的数据源。 听众 本课程面向处理多传感器实施的工程师,程序员和架构师。

Machine Translated

课程大纲

Introduction to Sensor Fusion

  • Sensor Fusion Overview
  • Errors in Raw Data

Multisensor Fusion Architecture

  • Architectural Taxonomy
  • Centralized vs Decentralized
  • Local vs Global Interaction
  • Hierarchy 

Fusion Methods

  • Bayesian Networks
  • Probabilistic Grids 
  • The Kalman Filter  
  • Markov chain Monte Carlo
  • Alternatives to Probability

 

 

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