A clustering algorithm similar to KMeans is implemented, it has two main advantages, namely (a) The estimator is resistant to outliers, that means that results of estimator are still correct when there are atypical values in the sample and (b) The estimator is efficient, roughly speaking, if there are no outliers in the sample, results will be similar than those obtained by a classic algorithm (KMeans). Clustering procedure is carried out by minimizing the overall robust scale socalled tau scale. (see Gonzalez, Yohai and Zamar (2019) <arxiv:1906.08198>).
Package details 


Author  Juan Domingo Gonzalez [cre, aut], Victor J. Yohai [aut], Ruben H. Zamar [aut] 
Maintainer  Juan Domingo Gonzalez <juanrst@hotmail.com> 
License  GPL (>= 2) 
Version  0.1.0 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.