Fredrik Heintz
Dept. Of Computer and Information Science, Linköping University, Sweden
Jonas Kvarnström
Dept. of Computer and Information Science, Linköping University, Sweden
Patrick Doherty
Dept. of Computer and Information Science, Linköping University, Sweden
Ladda ner artikel
Ingår i: The Swedish AI Society Workshop May 20-21; 2010; Uppsala University
Linköping Electronic Conference Proceedings 48:6, s. 25-25
Publicerad: 2010-05-19
ISBN:
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
For autonomous systems such as unmanned aerial vehicles to successfully perform complex missions; a great deal of embedded reasoning is required at varying levels of abstraction. To support the integration and use of diverse reasoning modules we have developed DyKnow; a stream-based knowledge processing middleware framework. By using streams; DyKnow captures the incremental nature of sensor data and supports the continuous reasoning necessary to react to rapid changes in the environment.
DyKnow has a formal basis and pragmatically deals with many of the architectural issues which arise in autonomous systems. This includes a systematic stream-based method for handling the sense-reasoning gap; caused by the wide difference in abstraction levels between the noisy data generally available from sensors and the symbolic; semantically meaningful information required by many high-level reasoning modules. As concrete examples; stream-based support for anchoring and planning are presented.
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