Self-reconfigurable robots are built from modules which are autonomously able to change the way they are connected, thus changing the overall shape of the robot. This self-reconfiguration process is difficult to control, because it involves the distributed coordination of large numbers of identical modules connected in time-varying ways. We present an approach where a desired shape is grown based on a scalable representation of the desired configuration which is automatically generated from a 3D CAD model. The size of the configuration is adjusted continually to match the number of modules in the system. This has the advantage that if modules are removed or added, the system automatically adjusts its scale and thus self-repair is obtained as a side effect This capability is achieved by distributed, local rules for module movement that are independent of the goal configuration. We compare the scale independent approach to one where the desired configuration is grown directly at a fixed scale. We find that the features of the scale independent approach come at the expense of an increased number of moves, messages, and time steps taken to reconfigure.