Real-time diagnostics for ROS running systems based on probabilistic patterns identification

0508667 - ÚT 2020 RIV CZ eng C - Conference Paper (international conference)
Věchet, Stanislav - Krejsa, Jiří
Real-time diagnostics for ROS running systems based on probabilistic patterns identification.
Engineering mechanics 2019. Book of full texts. Prague: Institute of Thermomechanics of the Czech Academy of Sciences, 2019 - (Zolotarev, I.; Radolf, V.), s. 383-386. ISBN 978-80-87012-71-0. ISSN 1805-8248.
[Engineering mechanics 2019 /25./. Svratka (CZ), 13.05.2019-16.05.2019]
Institutional support: RVO:61388998
Keywords : diagnostic expert system * bayesian network * system diagnostic
OECD category: Automation and control systems

Autonomous mobile robots consists of various software modules to achieve given goal, including solving complex navigation tasks as localization, mapping or path planning. These tasks are highly dependent on the quality of data measured and gathered from hardware subsystems. Using Robot Operating System (ROS) as integration basis reduces the development effort and time to market. While ROS framework itself is considered as reliable and stable to run even soft real-time tasks, in case of any internal failures on data misreadings can be problematic to debug or even identify the problem for common user. Due to this unpleasant situations we develop a virtual assistant, internally represented as diagnostic expert system, to help users to identify and possibly fix the problem.
Permanent Link: http://hdl.handle.net/11104/0304959