Simultaneous Localization and Mapping

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In GNSS limited or denied environments it is often useful to navigate based on landmarks, using exteroceptive sensors (lidar, camera etc).

The state vector $\mathbf{x}$ consists of two components, the pose $x$ and the map $m$.

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SLAM: Recursive Methods

Resources: page=203 Ch. 11

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Online SLAM

• Find the posterior density $p({\eta }_k,m|z_{1:k})$
• Where the robot actually is Full SLAM
• Find a representation of the posterior density $p({\eta }_{1:k},m|z_{1:k})$.
• Where the robot has been at any past time (reconstructing the full trajectory).

Fast-SLAM