Foundational research pillars

The research we are doing in York is focused on core technical issues arising from the use of robotics and autonomous systems in critical applications.

Our research focus in recent months has brought together the practical guidance developed for the Body of Knowledge with our foundational research on the key challenges that remain at the heart of the safety assurance of robotics and autonomous systems (RAS).

We have been advancing our research on some of the core technical issues that remain for the safety assurance of RAS and have established a new structure to focus our work. This includes five key pillars of research:

Contact us

Assuring Autonomy International Programme
assuring-autonomy@york.ac.uk
+44 (0)1904 325345
Department of Computer Science, Deramore Lane, University of York, York YO10 5GH

Overview diagram of the AMLAS methodology for assuring the safety of machine learned components

The first published methodology from our research pillars is our AMLAS process (Assurance of Machine Learning for use in Autonomous Systems). This has been peer-reviewed by our Fellows and experienced engineers from multiple industry domains.

AMLAS comprises:

  • a set of assurance activities that integrate with the development of ML components
  • defined assurance artefacts relating to those activities
  • safety case patterns to guide the development of a compelling safety case for ML components

The integration of activities, artefacts, and safety case patterns ensures AMLAS provides a practical and coherent approach. The guidance provides practical notes, examples, and links to the Body of Knowledge, creating a complete handbook for safety engineers, developers, and regulators.

Download AMLAS

This pillar will cover:

  • elicitation and validation of safety requirements for understanding (e.g. perception) in autonomous systems
  • failure analysis and propagation for understanding
  • verification of understanding (e.g. perception)
  • safety case for understanding in autonomous systems

This pillar will cover:

  • elicitation and validation of safety requirements for decision making (e.g. path planning) in autonomous systems
  • failure analysis and propagation for decision making
  • verification of decision making (e.g. path planning)
  • safety case for decision making in autonomous systems

This pillar will cover:

  • elicitation of safe autonomous systems behaviour in complex environments
  • analysing interactions between autonomous systems and outside world, including humans
  • validation of safe autonomous systems behaviour in complex environments, including use of simulation
  • maintaining safety assurance of an autonomous systems during operation
  • safety case for autonomous systems

This pillar will cover:

  • legal acceptance
  • regulatory compliance
  • accounting for ethical considerations
  • risk acceptance
  • public trust

More than the sum of its parts

As each guidance document for the five pillars is developed, it will stand alone as an essential component for assuring that aspect of an autonomous system. However, assurance of autonomous systems must consider all aspects in the broad context of development, operation, and approval. 

Used together, the guidance documents will help to ensure a credible and compelling assurance case is created for an autonomous system.

Contact us

Assuring Autonomy International Programme
assuring-autonomy@york.ac.uk
+44 (0)1904 325345
Department of Computer Science, Deramore Lane, University of York, York YO10 5GH