In reply to David.

You are correct. The classical PCA generates scores with diagonal covariance because the data are standardized by (X - mean(X))/ std(X) and cov(X) is used for the eigen decomposition. In robust PCA, the data are not centered and scaled in the same way. Therefore the classical geometry is distorted. in the robust PCA, you should not expect the CLASSICAL covariance of the robust scores to be diagonal; you expect the ROBUST covariance of the scores to be diagonal.