Evaluating Situation Awareness of Autonomous Systems



Autonomous systems proved to be successful in various application areas. But their perception, reasoning, planning and behavior capabilities are generally designed to fit special purposes only. For instance, a robotic agent perceives its environment in a way that was defined in advance by a human designer. The agent does not exhibit a certain perception behavior because it actually thinks it would be reasonable to do so. But with an increasing level of autonomy as well as a larger temporal and spatial scope of agent operation higher-level situation analysis and assessment become essential. This chapter examines approaches for knowledge representation, reasoning, and acquisition that enable autonomous systems to evaluate and maintain their current situation awareness. An example application scenario is presented that provides initial results for evaluating situation-aware systems.


Sensor Node Autonomous System Situation Awareness Information Acquisition Closed World Assumption 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This research is funded by the German Research Foundation (DFG) within the Collaborative Research Center 637 “Autonomous Cooperating Logistic Processes: A Paradigm Shift and its Limitations” (SFB 637) at the University of Bremen, Germany.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Center for Computing and Communication Technologies – TZI, Universität BremenBremenGermany

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