  We give methods for the construction of designs for linear models, when the
purpose of the investigation is the estimation of the conditional quantile
function and the estimation method is quantile regression. The designs are
robust against misspecified response functions, and against unanticipated
heteroscedasticity. The methods are illustrated by example, and in a case study
in which they are applied to growth charts.
