Název: Anomalies detection in time-series data for the internal diagnostics of autonomous mobile robot
Autoři: Věchet, Stanislav ; Krejsa, Jiří ; Chen, K.S.
Typ dokumentu: Příspěvky z konference
Konference/Akce: International Conference Engineering Mechanics 2020 /26./, Brno (CZ), 20201124
Rok: 2020
Jazyk: eng
Abstrakt: Autonomous mobile robots are complex mechatronic machines which consists of numerous hardware and software modules working asynchronously to achieve desired behaviour. As there are many frameworks which helps to overcome the flat learning curve the problem of internal diagnostics arises. While users and developers are able to focus only on solving the high level problem algorithm or methods the internal states of the system is hidden. This helps to separate the users from solving hardware issues, which is helping until everything works properly. We present an algorithm which is able to detect anomalies in time based behaviour of the robot to improve the users confidence that the internal robot framework works correctly and as desired. The algorithm is based on probabilistic patterns detection based on Bayesian probabilistic theory.
Klíčová slova: anomalies detection; robot operating system; system diagnostic
Číslo projektu: MOST-20-06 (CEP)
Poskytovatel projektu: AV ČR
Zdrojový dokument: ENGINEERING MECHANICS 2020, ISBN 978-80-214-5896-3, ISSN 1805-8248

Instituce: Ústav termomechaniky AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný v příslušném ústavu Akademie věd ČR.
Původní záznam: http://hdl.handle.net/11104/0316605

Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-432766


Záznam je zařazen do těchto sbírek:
Věda a výzkum > AV ČR > Ústav termomechaniky
Konferenční materiály > Příspěvky z konference