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Robotic and Autonomous Systems Safety (RASS)

Overview

This course aims to:

Physically embodied Autonomous Systems (RAS) are being increasingly proposed, and used, in safety-critical applications in a variety of domains. These systems employ Artificial Intelligence technologies, such as Machine Learning, to provide capability, such as object detection and avoidance. These systems, and associated technologies, provide many challenges to current system safety engineering methods and assurance techniques.
No prior knowledge of RAS is required for this module - we will provide an introduction to the technologies sufficient for understanding of the safety aspects during the module.

In this module, we will consider

  • Systems engineering of AS and safety assurance of AS challenges and solutions
  • Use of AI and safety assurance of AI challenges and solutions
  • Socio-technical issues around responsible innovation and ethics, responsibility, human factors and competency

State of the art guidance on regulation and risk acceptance will be addressed. A framework for creating an appropriate AS safety case will be explored.
The module will be taught in a blended fashion, using a combination of pre-recorded lectures and live exercises sessions in which students will be taught in small groups. After the taught part of the module, students will select a topic and conduct a short critical literature review (formative). They will use this as a basis for a short talk, in a small group session, on which they will receive feedback both from other members of the group and from the course tutor. There will also be an open assessment (summative), undertaken over 5 weeks following the taught part of the module.

By the end of this module, students will be able to:

  • Identify and describe the disruptors - technical, engineering and social - to existing system safety engineering practices generated by autonomous systems.

  • Describe and evaluate the implications for and changes required in safety assessment and assurance practices to accommodate autonomous systems and associated emerging technologies .

  • Consistently and clearly communicate concepts and issues relating to autonomous systems engineering and safety.

  • Identify the societal and regulatory impact of autonomous systems and implications for risk acceptance in a range of safety-critical domains.

  • Demonstrate how to provide a compelling safety case for autonomous systems.

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Contact us

MSc SCSE and Short Courses Team

cs-safety-courses@york.ac.uk