Bridging the Sense-Reasoning Gap Using DyKnow: A Knowledge Processing Middleware Framework Export

@inproceedings{citeulike:3839950, abstract = {To achieve complex missions an autonomous unmanned aerial vehicle (UAV) operating in dynamic environments must have and maintain situational awareness. This can be achieved by continually gathering information from many sources, selecting the relevant information for current tasks, and deriving models about the environment and the UAV itself. It is often the case models suitable for traditional control, are not sufficient for deliberation. The need for more abstract models creates a sense-reasoning gap. This paper presents DyKnow, a knowledge processing middleware framework, and shows how it supports bridging the gap in a concrete UAV traffic monitoring application. In the example, sequences of color and thermal images are used to construct and maintain qualitative object structures. They model the parts of the environment necessary to recognize traffic behavior of tracked vehicles in real-time. The system has been implemented and tested in simulation and on data collected during flight tests.}, address = {Berlin, Heidelberg}, author = {Heintz, Fredrik and Rudol, Piotr and Doherty, Patrick}, booktitle = {KI '07: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence}, citeulike-article-id = {3839950}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1421450.1421493}, citeulike-linkout-1 = {http://dx.doi.org/10.1007/978-3-540-74565-5_40}, doi = {10.1007/978-3-540-74565-5_40}, isbn = {978-3-540-74564-8}, keywords = {my\_papers}, location = {Osnabr\"uck, Germany}, pages = {460--463}, posted-at = {2009-01-01 15:26:29}, priority = {2}, publisher = {Springer-Verlag}, title = {Bridging the Sense-Reasoning Gap Using DyKnow: A Knowledge Processing Middleware Framework}, url = {http://dx.doi.org/10.1007/978-3-540-74565-5_40}, year = {2007} }

TY - CONF ID - citeulike:3839950 L3 - citeulike-article-id:3839950 N2 - To achieve complex missions an autonomous unmanned aerial vehicle (UAV) operating in dynamic environments must have and maintain situational awareness. This can be achieved by continually gathering information from many sources, selecting the relevant information for current tasks, and deriving models about the environment and the UAV itself. It is often the case models suitable for traditional control, are not sufficient for deliberation. The need for more abstract models creates a sense-reasoning gap. This paper presents DyKnow, a knowledge processing middleware framework, and shows how it supports bridging the gap in a concrete UAV traffic monitoring application. In the example, sequences of color and thermal images are used to construct and maintain qualitative object structures. They model the parts of the environment necessary to recognize traffic behavior of tracked vehicles in real-time. The system has been implemented and tested in simulation and on data collected during flight tests. CY - Osnabr\"uck, Germany SN - 978-3-540-74564-8 AD - Berlin, Heidelberg EP - 463 TI - Bridging the Sense-Reasoning Gap Using DyKnow: A Knowledge Processing Middleware Framework PB - Springer-Verlag T2 - KI '07: Proceedings of the 30th annual German conference on Advances in Artificial Intelligence SP - 460 KW - my_papers AU - Heintz, Fredrik AU - Rudol, Piotr AU - Doherty, Patrick PY - 2007/// UR - http://dx.doi.org/10.1007/978-3-540-74565-5_40 ER -