Modern telerobotic systems proposed for space applications will require the flexibility for transfer of human operator control between multiple levels of abstraction in the system hierarchy. In the presence of higher levels of autonomy such as task planning and path planning, the transfer of control requires that the integrity of abstract models of the work environment be maintained. In current systems the model updates are provided manually by the user or are hard coded in the task definition. In this paper we present a hierarchical approach to a system for telerobotic situation assessment where teleoperator action interpretations are automatically generated in terms of geometric model updates. At the lowest level of the hierarchy, high frequency robot data containing synchronous position and force information is preprocessed so that interesting events can be detected with filtered data flowing up to the next higher level of absiraction. As intermediate levels receive information from lower levels, comparisons are made with expectations from the current context to produce world model updates. Sequences of events potentially interesting to the next higher level are then reported so that abstractions can progress to the topmost level. The autonomous model updates increase the effectiveness of performing teleoperation tasks using different levels of autonomy since manual updates to the world model are unnecessary.