Dynamical systems theory is used here as a theoretical language and tool to design a distributed control archictecture that generates navigation in formation, integrated with obstacle avoidance, for a team of three autonomous robots. In this approach the level of modeling is at the level of behaviors. A “dynamics” of behavior is defined over a state space of behavioral variables. The environment is also modeled in these terms by representing task constraints as attractors (i.e. asymptotically stable states) or reppelers (i.e. unstable states) of behavioral dynamics. For each robot attractors and repellers are combined into a vector field that governs the behavior. The resulting dynamical systems that generate the behavior of the robots are non-linear. Computer simulations support the validity of our dynamic model architectures.