Engineering Mechanics

International Conference

Proceedings Vol. 26 (2020)


ENGINEERING MECHANICS 2020

26th INTERNATIONAL CONFERENCE
November 24 – 25, 2020, Brno, Czech Republic
;
Editors: Vladimír Fuis

Copyright © 2020 Brno University of Technology Institute of Solid Mechanics, Mechatronics and Biomechanics

ISBN 978-80-214-5896-3 (printed)
ISSN 1805-8248 (printed)
ISSN 1805-8256 (electronic)

list of papers scientific commitee

ANOMALIES DETECTION IN TIME-SERIES DATA FOR THE INTERNAL DIAGNOSTICS OF AUTONOMOUS MOBILE ROBOT
Vechet S., Krejsa J., Chen K. S.
pages 508 - 511, full text

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 are 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.


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Ownership of copyright in original research articles remains with the Authors, and provided that, when reproducing parts of the contribution, the Authors acknowledge and/or reference the Proceedings, the Authors do not need to seek permission for re-use of their material.

All papers were reviewed by members of the scientific committee.


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