Random sample consensus (RANSAC)

RANSAC is an iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers.

RANSAC is good for detecting outliers.


Rahul also mentioned this in the F1TENTH lecture on Scan Matching for outlier rejection.

Ransac Algorithm


  1. Sample the number of data points required to fit the model
  2. Compute model parameters using the sampled data points
  3. Score by the fraction of inliers within a preset threshold of the model

Repeat 1-3 until the best model is found with high confidence.

Taken from the Cyrill Stachniss video.