Selecting initial centroids in Kmeans in R

Question

I am using k means for clustering of users. I want to further improve my clusters formed by selecting initial centroids myself.

Since in a dataframe kmeans allot random rows as initial centroids and that impact final clusters formed.

Is there a way to assign initial centroids manually in R ? I used elbow method to get optimal number of clusters.

My code here:

for (i in 2:15) wss[i] <- sum(kmeans(db, 
                          centers=i, iter.max = 20)$withinss)
plot(1:15, wss, type="b", xlab="Number of Clusters",
    ylab="Within groups sum of squares")

fit <- kmeans(db, 7)
aggregate(db, by=list(fit$cluster),FUN=mean)
mydata <- data.frame(db, fit$cluster)