Recursive State Estimation Lecture 7 Perception as a Continuous - - PowerPoint PPT Presentation

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Recursive State Estimation Lecture 7 Perception as a Continuous - - PowerPoint PPT Presentation

Recursive State Estimation Lecture 7 Perception as a Continuous Process Perception as a Multi-Modal Experience Perception as Inference Helmholtz (1821-1894) Plato (I BC) Recursive State Estimation Mathematical Formalism to: continuously


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SLIDE 1

Recursive State Estimation

Lecture 7

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SLIDE 2

Perception as a Continuous Process

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SLIDE 3

Perception as a Multi-Modal Experience

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SLIDE 4

Perception as Inference

Plato (I BC) Helmholtz (1821-1894)

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SLIDE 5

Recursive State Estimation Mathematical Formalism to:

continuously integrate measurements

from different sensor sources

to infer the state of a latent variable

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SLIDE 6

Why is this Useful for Robotics?

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SLIDE 7

Today

  • Intro: why state estimation?
  • Bayes Filter
  • Kalman Filter
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SLIDE 8

The Agent and the Environment

Perception World Model Decision Making

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SLIDE 9

Notation

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SLIDE 10

Probability Theory Refresh

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SLIDE 11

Probability Theory Refresh 2

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SLIDE 12

Probability Theory Refresh 3

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SLIDE 13

The Bayes Filter

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SLIDE 14

The Bayes Filter

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SLIDE 15
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SLIDE 16

Limitations

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SLIDE 17
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SLIDE 18
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SLIDE 19
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SLIDE 20

Kalman Filter