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DyKnow: A Dynamically Reconfigurable Stream Reasoning Framework as an Extension to the Robot Operating System
Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten. (KPLAB - Knowledge Processing Lab)
Linköpings universitet, Institutionen för datavetenskap, Artificiell intelligens och integrerade datorsystem. Linköpings universitet, Tekniska fakulteten. (KPLAB - Knowledge Processing Lab)
2016 (engelsk)Inngår i: Proceedings of the Fifth IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots (SIMPAR), IEEE conference proceedings, 2016, s. 55-60Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

DyKnow is a framework for stream reasoning aimed at robot applications that need to reason over a wide and varying array of sensor data for e.g. situation awareness. The framework extends the Robot Operating System (ROS). This paper presents the architecture and services behind DyKnow's run-time reconfiguration capabilities and offers an analysis of the quantitative and qualitative overhead. Run-time reconfiguration offers interesting advantages, such as fault recovery and the handling of changes to the set of computational and information resources that are available to a robot system. Reconfiguration capabilities are becoming increasingly important with the advances in areas such as the Internet of Things (IoT). We show the effectiveness of the suggested reconfiguration support by considering practical case studies alongside an empirical evaluation of the minimal overhead introduced when compared to standard ROS.

sted, utgiver, år, opplag, sider
IEEE conference proceedings, 2016. s. 55-60
Emneord [en]
stream reasoning framework, middleware, reconfiguration, robotics
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-132266DOI: 10.1109/SIMPAR.2016.7862375ISI: 000405933700009ISBN: 978-1-5090-4616-4 (digital)ISBN: 978-1-5090-4617-1 (tryckt)OAI: oai:DiVA.org:liu-132266DiVA, id: diva2:1039601
Konferanse
IEEE International Conference on Simulation, Modeling, and Programming for Autonomous Robots, San Francisco CA, USA, 13-16 December, 2016
Prosjekter
CUGSNFFP6CUASCADICSELLIIT
Forskningsfinansiär
CUGS (National Graduate School in Computer Science)ELLIIT - The Linköping‐Lund Initiative on IT and Mobile Communications
Merknad

Funding agencies: National Graduate School in Computer Science, Sweden (CUGS); Swedish Foundation for Strategic Research (SSF) project CUAS; Swedish Research Council (VR) Linnaeus Center CADICS; ELLIIT Excellence Center at Linkoping- Lund for Information Technology; Swedis

Tilgjengelig fra: 2016-10-24 Laget: 2016-10-24 Sist oppdatert: 2018-01-14

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