research-article

A skill fault model for autonomous systems

Authors:

Gabriela Catalán Medina,

Jérémie Guiochet,

Charles Lesire,

Augustin ManecyAuthors Info & Claims

RoSE '22: Proceedings of the 4th International Workshop on Robotics Software Engineering

Pages 55 - 62

https://doi.org/10.1145/3526071.3527513

Published: 02 February 2023 Publication History

Abstract

Autonomous systems are now deployed for many applications to perform more and more complex tasks in open environments. To manage complexity of their control software architecture, a current trend is to use a 3-layers approach, with a decisional layer (able to formulate decisions), a functional layer (low level control actions), and between them a skill layer. This layer is dedicated to convert high level plan objectives into low level atomic actions, sent to the functional layer. In order to deal with failures that may happen at runtime, detection mechanisms and reaction strategies may be implemented in these layers, or even in external devices. However, no generic technique is available to guarantee that all these mechanisms will be consistent. We present in this paper an approach that focus on the skill layer, with a proposal of a generic skill fault model used to design and analyze failure detection and reactions mechanisms. This approach has been successfully applied to a real drone application, and we present an extract of the resulting fault analysis models.

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Cited By

Tolossa TManohar PJahnavi ABhavsingh TTeja SJangir YHote YOrlando M(2024)Fault Detection and Analysis of a Mobile Robot using Radial Basis Function Network2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)10.1109/ICPC2T60072.2024.10474654(1-6)Online publication date: 18-Jan-2024
https://doi.org/10.1109/ICPC2T60072.2024.10474654
Stadler MVierhauser M(2023)ROMoSu: Flexible Runtime Monitoring Support for ROS-based Applications2023 IEEE/ACM 5th International Workshop on Robotics Software Engineering (RoSE)10.1109/RoSE59155.2023.00013(53-60)Online publication date: May-2023
https://doi.org/10.1109/RoSE59155.2023.00013
Albore ADoose DGrand CGuiochet JLesire CManecy A(2023)Skill-based design of dependable robotic architecturesRobotics and Autonomous Systems10.1016/j.robot.2022.104318160:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.robot.2022.104318
Show More Cited By

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A skill fault model for autonomous systems

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cover image ACM Conferences

RoSE '22: Proceedings of the 4th International Workshop on Robotics Software Engineering

May 2022

71 pages

ISBN:9781450393171

DOI:10.1145/3526071

Conference Chairs:
Andreas Angerer
XITASO GmbH, Germany
,
Federico Ciccozzi
Mälardalen University, Västerås, Sweden
,
Ivano Malavolta
Vrije Universiteit Amsterdam, The Netherlands
,
Andreas Wortmann
University of Stuttgart, Germany

Copyright © 2022 ACM.

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Published: 02 February 2023

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ICSE '22: 44th International Conference on Software Engineering

May 9, 2022

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Cited By

Tolossa TManohar PJahnavi ABhavsingh TTeja SJangir YHote YOrlando M(2024)Fault Detection and Analysis of a Mobile Robot using Radial Basis Function Network2024 Third International Conference on Power, Control and Computing Technologies (ICPC2T)10.1109/ICPC2T60072.2024.10474654(1-6)Online publication date: 18-Jan-2024
https://doi.org/10.1109/ICPC2T60072.2024.10474654
Stadler MVierhauser M(2023)ROMoSu: Flexible Runtime Monitoring Support for ROS-based Applications2023 IEEE/ACM 5th International Workshop on Robotics Software Engineering (RoSE)10.1109/RoSE59155.2023.00013(53-60)Online publication date: May-2023
https://doi.org/10.1109/RoSE59155.2023.00013
Albore ADoose DGrand CGuiochet JLesire CManecy A(2023)Skill-based design of dependable robotic architecturesRobotics and Autonomous Systems10.1016/j.robot.2022.104318160:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.robot.2022.104318
Castellano-Quero MCastillo-López MFernández-Madrigal JArévalo-Espejo VVoos HGarcía-Cerezo A(2023)A multidimensional Bayesian architecture for real-time anomaly detection and recovery in mobile robot sensory systemsEngineering Applications of Artificial Intelligence10.1016/j.engappai.2023.106673125:COnline publication date: 1-Oct-2023
https://dl.acm.org/doi/10.1016/j.engappai.2023.106673

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