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Publication
Sub-system Integration and Health Dashboard for Autonomous Mobile Robots
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Advisor(s)
Abstract(s)
Data visualization has become increasingly important to
improve equipment monitoring, reduce operational costs and increase
process efficiency with the ever-increasing amount of data being generated
and collected in various fields. This paper proposes the development
of a health monitoring system for an Autonomous Mobile Robot (AMR)
that allows data acquisition and analysis for decision-making. The implementation
of the proposed system showed favourable results in data
acquisition, analysis, and visualization for decision-making. Through the
use of a hybrid control architecture, the data acquisition and processing
demonstrated efficiency without significant impact on battery consumption
or resource usage of the AMR embedded microcomputer. The
developed dashboard proved to be efficient in navigating and visualizing
the data, providing important tools for the platform manager’s decisionmaking.
This work contributes to the health monitoring of devices based
on Robot Operating System (ROS), which may be of interest to professionals
and researchers in fields related to robotics and automation.
Furthermore, the system presented will be open source, making it accessible
and adaptable for use in different contexts and applications.
Description
Keywords
Human machine interface Data visualization Autonomous mobile robot Robot operating system Open source software
Pedagogical Context
Citation
França, André; Loures, Eduardo; Jorge, Luísa; Mendes, André (2024). Sub-system Integration and Health Dashboard for Autonomous Mobile Robots. In 3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A 2023). Cham: Springer Nature, Vol. 2, p. 280-293. ISBN 978-3-031-53035-7.
Publisher
Springer Nature