  We present a number of powerful local mechanisms for maintaining a dynamic
swarm of robots with limited capabilities and information, in the presence of
external forces and permanent node failures. We propose a set of local
continuous algorithms that together produce a generalization of a Euclidean
Steiner tree. At any stage, the resulting overall shape achieves a good
compromise between local thickness, global connectivity, and flexibility to
further continuous motion of the terminals. The resulting swarm behavior scales
well, is robust against node failures, and performs close to the best known
approximation bound for a corresponding centralized static optimization
problem.
