For a system of cooperative mobile robots to be effective in real-world applications, it must be able to efficiently execute a wide class of complex tasks in potentially unknown and unstructured environments. Previous research in multi-robot systems has either been limited to relatively structured domains or to small classes of feasible missions. This paper describes a field-capable system called GRAMMPS which addresses this problem by coupling a general-purpose interpreted grammar for task definition with dynamic planning techniques. GRAMMPS supports a general class of local navigation systems and heterogeneous groups of robots, providing optimal execution of missions given current world knowledge. Simulation runs illustrating the capabilities of this system are provided. Results showing successful runs of this system on two autonomous off-road vehicles are also given.