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Towards flexible runtime monitoring support for ROS-based applications

Published: 02 February 2023 Publication History
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  • Abstract

    Robotic systems are becoming common in different domains and for various purposes, such as unmanned aerial vehicles performing search and rescue operations, or robots operating in manufacturing plants. Such systems are characterized by close interactions, or even collaborations, between hardware and machinery on the one hand, and humans on the other. Furthermore, as Cyber-Physical Systems (CPS) in general and robotic applications in particular typically operate in an emergent environment, unanticipated events may occur during their operation, making the need for runtime monitoring support a crucial yet often time-consuming task. Runtime monitoring typically requires establishing support for collecting data, aggregating and transporting the data to a monitoring framework for persistence and further processing, and finally, performing checks of functional and non-functional properties. In this paper, we present our initial efforts towards a flexible monitoring framework for ROS-based systems. We report on challenges for establishing runtime monitoring support and present our preliminary architecture that aims to significantly reduce the setup and maintenance effort when creating monitors and establishing constraint checks.

    References

    [1]
    Ankit Agrawal, Sophia Abraham, Benjamin Burger, Chichi Christine, and et al. Fraser. 2020. The Next Generation of Human-Drone Partnerships: Co-Designing an Emergency Response System. Proc. of the 2020 CHI Conference on Human Factors in Computing Systems (2020), 1--13.
    [2]
    Giovanni Beltrame, Ettore Merlo, Jacopo Panerati, and Carlo Pinciroli. 2018. Engineering safety in swarm robotics. In Proc. of the 1st Int'l WS on Robotics Software Engineering. ACM, 36--39.
    [3]
    Gordon Blair, Nelly Bencomo, and Robert B France. 2009. Models@run. time. Computer 42, 10 (2009), 22--27.
    [4]
    Thomas Brand and Holger Giese. 2019. Modeling Approach and Evaluation Criteria for Adaptable Architectural Runtime Model Instances. In Proc. of the 22nd Int'l Conf. on Model Driven Engineering Languages and Systems. 227--232.
    [5]
    Paulo Casanova, David Garlan, Bradley Schmerl, and Rui Abreu. 2014. Diagnosing Unobserved Components in Self-Adaptive Systems. In Proc. of the 9th Int'l Symp. on Software Engineering for Adaptive and Self-Managing Systems.
    [6]
    J. Ruby Dinakar and S. Vagdevi. 2017. A study on storage mechanism for heterogeneous sensor data on big data paradigm. In Proc. of the 2017 Int'l Conf. on Electrical, Electronics, Communication, Computer, and Opt. Techniques. 342--345.
    [7]
    Didem Gürdür, Aneta Vulgarakis Feljan, Jad El-khoury, Swarup Kumar Mohalik, Ramamurthy Badrinath, Anusha Pradeep Mujumdar, and Elena Fersman. 2018. Knowledge Representation of Cyber-physical Systems for Monitoring Purpose. Procedia CIRP 72 (2018), 468--473.
    [8]
    David B. Lindenmayer and Gene E. Likens. 2009. Adaptive monitoring: a new paradigm for long-term research and monitoring. Trends in Ecology & Evolution 24, 9 (2009), 482--486.
    [9]
    Lola Masson, Jérémie Guiochet, Hélène Waeselynck, Augustin Desfosses, and Marc Laval. 2017. Synthesis of Safety Rules for Active Monitoring: Application to an Airport Light Measurement Robot. In 2017 First IEEE International Conference on Robotic Computing (IRC). 263--270.
    [10]
    Christoph Mayr-Dorn, Mario Winterer, Christian Salomon, Doris Hohensinger, and Rudolf Ramler. 2021. Considerations for using Block-Based Languages for Industrial Robot Programming-a Case Study. In Proc. of the 2021 IEEE/ACM 3rd Int'l Workshop on Robotics Software Engineering. IEEE, 5--12.
    [11]
    Samuel Parra, Sven Schneider, and Nico Hochgeschwender. 2021. Specifying QoS Requirements and Capabilities for Component-Based Robot Software. In Proc. of the 3rd Int'l WS on Robotics Software Engineering. IEEE, 29--36.
    [12]
    Rick Rabiser, Klaus Schmid, Holger Eichelberger, Michael Vierhauser, Sam Guinea, and Paul Grünbacher. 2019. A domain analysis of resource and requirements monitoring: Towards a comprehensive model of the software monitoring domain. Information and Software Technology 111 (2019), 86--109.
    [13]
    Rick Rabiser, Jürgen Thanhofer-Pilisch, Michael Vierhauser, Paul Grünbacher, and Alexander Egyed. 2018. Developing and evolving a DSL-based approach for runtime monitoring of systems of systems. Automated Software Engineering 25, 4 (2018), 875--915.
    [14]
    Lucas Sakizloglou, Sona Ghahremani, Thomas Brand, Matthias Barkowsky, and Holger Giese. 2020. Towards Highly Scalable Runtime Models with History. In Proc. of the IEEE/ACM 15th Int'l Symp. on Software Engineering for Adaptive and Self-Managing Systems. ACM, 188--194.
    [15]
    Jürgen Thanhofer-Pilisch, Michael Vierhauser, Rick Rabiser, and Paul Grünbacher. 2016. Event capture and compare for runtime monitoring of systems of systems. In Proc. of the 1st Int'l WS on Var. and Complexity in Software Design. IEEE, 1--4.
    [16]
    Michael Vierhauser, Sean Bayley, Jane Wyngaard, Wandi Xiong, Jinghui Cheng, Joshua Huseman, Robyn Lutz, and Jane Cleland-Huang. 2019. Interlocking Safety Cases for Unmanned Autonomous Systems in Shared Airspaces. IEEE Transactions on Software Engineering 47, 5 (2019), 899--918.
    [17]
    Michael Vierhauser, Hussein Marah, Antonio Garmendia, Jane Cleland-Huang, and Manuel Wimmer. 2021. Towards a Model-Integrated Runtime Monitoring Infrastructure for Cyber-Physical Systems. In Proc. of the 2021 IEEE/ACM 43rd Int'l Conf. on Software Engineering: New Ideas and Emerging Results. IEEE, 96--100.
    [18]
    Michael Vierhauser, Rick Rabiser, and Paul Grünbacher. 2016. Requirements monitoring frameworks: A systematic review. Information and Software Technology 80 (2016), 89--109.
    [19]
    Thomas Witte and Matthias Tichy. 2021. Inferred Interactive Controls Through Provenance Tracking of ROS Message Data. In Proc. of the 3rd Int'l WS on Robotics Software Engineering. IEEE, 67--74.

    Cited By

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    • (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
    • (2023)An Empirical Study on Fault Diagnosis in Robotic Systems2023 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME58846.2023.00030(207-219)Online publication date: 1-Oct-2023

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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
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 02 February 2023

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      Author Tags

      1. ROS
      2. cyber-physical systems
      3. runtime monitoring

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      • Linz Institute of Technology

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      • (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
      • (2023)An Empirical Study on Fault Diagnosis in Robotic Systems2023 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME58846.2023.00030(207-219)Online publication date: 1-Oct-2023

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