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Decision processes in Artificial Intelligence are often organized hierarchically. One example is robot navigation with a global path planner and a local executor. This paper examines whether a shift from optimizing the two typical modules in navigation towards a dynamic interaction of more, not necessarily hierarchically linked, modules leads to robust navigation behavior. We empirically evaluate different organizations of modules for navigation in a simulated household with a simulated PR2 robot.

A Modular Approach of Decision-Making in the Context of Robot Navigation in Domestic Environments