> ## Documentation Index
> Fetch the complete documentation index at: https://aegean.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# State Estimation

> Recursive state estimation, Bayes filters, and Kalman filtering.

This chapter covers state estimation techniques essential for robotics, including Bayesian filtering and Kalman filters.

## Topics

<CardGroup cols={2}>
  <Card title="Hidden Markov Models" icon="diagram-project">
    Introduction to HMMs for state estimation.
  </Card>

  <Card title="Bayes Filter" icon="filter">
    The fundamental Bayesian filtering algorithm.
  </Card>

  <Card title="Kalman Filter" icon="wave-square">
    Optimal state estimation under Gaussian assumptions.
  </Card>

  <Card title="Particle Filters" icon="circle-nodes">
    Monte Carlo methods for non-linear state estimation.
  </Card>
</CardGroup>

<Note>
  Video lectures on state estimation are available in the Media section under the Robotics course.
</Note>

***

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