This paper proposes a method to improve robustness of the robot programs generated by genetic programming. The main idea is to inject perturbation into the simulation during the evolution of the solutions. The resulting robot programs are more robust because they have been evolved to tolerate the changes in their environment. We set out to test this idea using the problem of navigating a mobile...