08. Introduction to FastSLAM

The FastSLAM algorithm solves the Full SLAM problem with known correspondences.

• Estimating the Trajectory: FastSLAM estimates a posterior over the trajectory using a particle filter approach. This will give an advantage to SLAM to solve the problem of mapping with known poses.
• Estimating the Map: FastSLAM uses a low dimensional Extended Kalman Filter to solve independent features of the map which are modeled with local Gaussian.

The custom approach of representing the posterior with particle filter and Gaussian is known by the Rao-Blackwellized particle filter approach.