Date: November 08, 2016
Presenter: Dr. Xiaotong SHEN
Supervisor: Prof. Daniela RUS (MIT)
Robust data association for feature cloud matching is of great importance for autonomous vehicles to build an accurate map. For matching two feature clouds observed at two different poses, we discover that the covariance matrix of the measurement prediction error can be written as the sum of a low rank matrix and a block diagonal matrix, if we assume that the features are observed independently at each pose.