Towards a resilience assurance model for robotic autonomous systems

Felician Campean, Sohag Kabir, Cuong Dao, Qichun Zhang, Claudia Eckert

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations

Abstract

Applications of autonomous systems are becoming increasingly common across the field of engineered systems from cars, drones, manufacturing systems and medical devices, addressing prevailing societal changes, and, increasingly, consumer demand. Autonomous systems are expected to self-manage and self-certify against risks affecting the mission, safety and asset integrity. While significant progress has been achieved in relation to the modelling of safety and safety assurance of autonomous systems, no similar approach is available for resilience that integrates coherently across the cyber and physical parts. This paper presents a comprehensive discussion of resilience in the context of robotic autonomous systems, covering both resilience by design and resilience by reaction, and proposes a conceptual model of a system of learning for resilience assurance in a continuous product development framework. The resilience assurance model is proposed as a composable digital artefact, underpinned by a rigorous model-based resilience analysis at the system design stage, and dynamically monitored and continuously updated at run time in the system operation stage, with machine learning based knowledge extraction and validation.

Original languageEnglish
Pages (from-to)3189-3198
Number of pages10
JournalProceedings of the Design Society
Volume1
DOIs
StatePublished - 2021
Externally publishedYes
Event23rd International Conference on Engineering Design, ICED 2021 - Gothenburg, Sweden
Duration: 16 Aug 202120 Aug 2021

Keywords

  • Artificial intelligence
  • Autonomous systems
  • Industry 4.0
  • Resilience
  • Systems Engineering (SE)

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