Temporal projection, the process of predicting what will happen when a
robot executes its plan, is essential for autonomous service robots to
successfully plan their missions. This paper describes a causal model of
the behavior exhibited by a mobile robot when running concurrent
reactive plans. The model represents aspects of robot behavior that
cannot be represented by most action models used in AI planning: it
represents the temporal structure of continuous control processes,
several modes of their interferences, and various kinds of uncertainty.
This enhanced expressiveness enables robot action planning systems to
predict, and therefore forestall, various kinds of behavior flaws
including missed deadlines whilst expoiting incidental opportunities.
the proposed causal model is experimentally validated.