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.