Part III: State Estimation and Classical Inference
Chapter 11  [A]

Factor Graphs and Smoothing

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Sections

  1. 11.1 From filters to factor graphs
  2. 11.2 MAP estimation and nonlinear least squares
  3. 11.3 Incremental smoothing (iSAM2) and GTSAM
  4. 11.4 Loop closure and marginalization
  5. 11.5 Robust cost functions
  6. 11.6 Uncertainty from the information matrix
  7. 11.7 Why modern SLAM and VIO use this

Lab 11

build a factor-graph pose estimator fusing odometry and landmark measurements with GTSAM.