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

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 integrate measurements ○ from different sensor sources ○ to infer the state of a latent variable ○
Why is this Useful for Robotics?
Today Intro: why state estimation? ● Bayes Filter ● Kalman Filter ●
The Agent and the Environment Decision Making World Model Perception
Notation
Probability Theory Refresh
Probability Theory Refresh 2
Probability Theory Refresh 3
The Bayes Filter
The Bayes Filter
Limitations
Kalman Filter

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