This paper introduces an original framework for planning and acting with hierarchical input/output automata for systems defined by the parallel composition of the models of their components. Typical applications are, for example, in harbor or warehouse automation. The framework extends the usual parallel composition operation of I/O au-tomata with a hierarchical composition operation that can refine a task. It defines planning as the synthesis of a control component to drive, through I/O interactions and task refinement, the system toward desired states. A new nondeterministic algorithm performs this synthesis. We tackle these issues on a theoretical basis. We formally define the representation and prove that the two operations of parallel and hierarchical composition are distributive, which is essential for the correctness and completeness of the proposed planning algorithm.