LiU Electronic Press
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Author:
Hongslo, Anders (Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems) (Linköping University, The Institute of Technology)
Title:
Stream Processing in the Robot Operating System framework
Department:
Linköping University, Department of Computer and Information Science, Artificial Intelligence and Intergrated Computer systems
Linköping University, The Institute of Technology
Publication type:
Student thesis
Language:
English
Level:
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE credits
Undergraduate subject:
Computer Engineering
Uppsok:
Technology
Pages:
79
Year of publ.:
2012
URI:
urn:nbn:se:liu:diva-79846
Permanent link:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-79846
ISRN:
LIU-IDA/LITH-EX-A--12/030--SE
Subject category:
Computer Engineering
Keywords(en) :
Artificial Intelligence, Stream Processing, Robotics
Abstract(en) :

Streams of information rather than static databases are becoming increasingly important with the rapid changes involved in a number of fields such as finance, social media and robotics. DyKnow is a stream-based knowledge processing middleware which has been used in autonomous Unmanned Aerial Vehicle (UAV) research. ROS (Robot Operating System) is an open-source robotics framework providing hardware abstraction, device drivers, communication infrastructure, tools, libraries as well as other functionalities.

This thesis describes a design and a realization of stream processing in ROS based on the stream-based knowledge processing middleware DyKnow. It describes how relevant information in ROS can be selected, labeled, merged and synchronized to provide streams of states. There are a lot of applications for such stream processing such as execution monitoring or evaluating metric temporal logic formulas through progression over state sequences containing the features of the formulas. Overviews are given of DyKnow and ROS before comparing the two and describing the design. The stream processing capabilities implemented in ROS are demonstrated through performance evaluations which show that such stream processing is fast and efficient. The resulting realization in ROS is also readily extensible to provide further stream processing functionality.

Presentation:
2012-06-11, Kurt Gödel, IDA, Linköping University, Linköping, 15:00 (English)
Supervisor:
Heintz, Fredrik, Ph.D (Linköping University, Department of Computer and Information Science) (Linköping University, The Institute of Technology)
Examiner:
Heintz, Fredrik, Ph.D (Linköping University, Department of Computer and Information Science) (Linköping University, The Institute of Technology)
Available from:
2012-08-16
Created:
2012-08-14
Last updated:
2012-08-16
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