Implement the k-Means clustering algorithm from scratch. Given a set of n-dimensional points, an integer k, and a set of initial centroids, perform the assignment and update steps for a maximum of 'max_iterations'. Return the final centroid coordinates rounded to four decimal places. Ensure the implementation handles convergence (early exit) and accounts for potential empty clusters.