Certification of Safe and Trusted Robotic Inspection of Assets

Fateme Dinmohammadi, Vincent Page, David Flynn, Valentin Robu, Michael Fisher, Charles Patchett, Michael Jump, Wenshuo Tang, Matt Webster

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)
124 Downloads (Pure)


In future inspections of offshore assets utilizing robots, robots will not only be expected to collate new data from their payload of instruments, but they will also be expected to interact with the infrastructure being inspected, undertake remedial tasks and engage with embedded monitoring systems of the asset. This increasing level of interaction and deployment frequency of robot inspections requires an understanding of how we can embed safe and trusted operational architectures within robots. Currently, robots can undertake constrained semi-autonomous inspections, using predetermined tasks (missions) with minimum supervision. However, the challenge is that the state of the world changes with time as does the condition of the robot. Therefore, robots must be able to undertake adaptive measures to support optimal outcomes during autonomous missions. In this paper, we propose an initial architecture to the safe verification and validation of health condition and certification of robotic and autonomous inspection systems for offshore assets. Our first contribution relates to the verification and validation architecture, which takes into account risks associated with asset inspection, safety protocols, evolving ambient changes, as well as the inherent state of health of the robot. The second part of our paper looks to how prognostic analytics can be used to support robot resilience in terms of sensor drift and accurate state of health estimates of critical sub-systems. Initial results demonstrate that methods such as relevance vector machines and Bayesian networks can be used to accurately mitigate risks to autonomy.
Original languageEnglish
Title of host publication2018 Prognostics and System Health Management Conference (PHM-Chongqing)
Number of pages9
ISBN (Electronic)9781538653807
Publication statusPublished - 7 Jan 2019
Event2018 Prognostics and System Health Management Conference - Chongqing, China
Duration: 26 Oct 201828 Oct 2018

Publication series

NamePrognostics and System Health Management Conference (PHM-Chongqing)
ISSN (Electronic)2166-5656


Conference2018 Prognostics and System Health Management Conference
Abbreviated titlePHM-Chongqing


  • Asset certification
  • Prognostic and health management (PHM)
  • Robotic inspection
  • Verification and validation

ASJC Scopus subject areas

  • Computer Science Applications
  • Safety, Risk, Reliability and Quality
  • Modelling and Simulation
  • Instrumentation


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