The main contribution of this paper is a planning language that can handle temporal constraints, resources and background knowledge. We provide a solver for this language based on problem decomposition that uses constraint satisfaction problems (CSPs) as a common ground. We argue that the usage of more expressive languages not only allows a more direct modeling of planning domains, but can speed up the planning process as well. We also present an experiment in support of that argument.