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Details of Grant 

EPSRC Reference: EP/V026747/1
Title: UKRI Trustworthy Autonomous Systems Node in Resilience
Principal Investigator: Calinescu, Dr R
Other Investigators:
Bennaceur, Dr A Levine, Professor M Habli, Dr I
Nuseibeh, Professor B Dogramadzi, Professor S Mihaylova, Professor LS
Stanton, Professor N Cavalcanti, Professor ALC Wilson, Professor J
Thiruvallore Thattai, Professor A Law, Dr J A Thomas, Professor A
Researcher Co-Investigators:
Project Partners:
Advanced Manufacturing Research Centre ATACC group Autonomous Drivers Alliance
Bradford Teaching Hospitals Bristol Robotics Laboratory (BRL) Chartered Inst of Ergo & Human Factors
CLAWAR Ltd ClearSy Connected Places Catapult
Consequential Robotics Ltd Croda Europe Limited Cyberselves Universal Limited
Defence Science & Tech Lab DSTL GoSouthCoast IAM RoadSmart
Kompai Robotics KUKA Robotics UK Limited Lancashire & South Cumbria NHS Fdn Trust
Lancashire Teaching Hospitals NHS Trust Lero (The Irish Software Research Ctr) Milton Keynes Uni Hospital NHS Fdn Trust
National Institute of Informatics NHS Digital (previously HSCIC) Ocado Technology
Public Health England RAC Foundation for Motoring Resilient Cyber Security Solutions
Robert Bosch GmbH Shadow Robot Company Ltd Sheffield Childrens NHS Foundation Trust
TechnipFMC (International) Thales Ltd University of Central Florida
University of Western Australia Welsh Ambulance Services NHS Trust
Department: Computer Science
Organisation: University of York
Scheme: Standard Research
Starts: 01 November 2020 Ends: 30 April 2024 Value (£): 3,033,178
EPSRC Research Topic Classifications:
Artificial Intelligence Human-Computer Interactions
Mathematical Aspects of OR Robotics & Autonomy
Sociology
EPSRC Industrial Sector Classifications:
Healthcare Aerospace, Defence and Marine
Related Grants:
Panel History:
Panel DatePanel NameOutcome
14 Sep 2020 Trustworthy Autonomous System Nodes Interview Panel A Announced
Summary on Grant Application Form
Imagine a future where autonomous systems are widely available to improve our lives. In this future, autonomous robots unobtrusively maintain the infrastructure of our cities, and support people in living fulfilled independent lives. In this future, autonomous software reliably diagnoses disease at early stages, and dependably manages our road traffic to maximise flow and minimise environmental impact.

Before this vision becomes reality, several major limitations of current autonomous systems need to be addressed. Key among these limitations is their reduced resilience: today's autonomous systems cannot avoid, withstand, recover from, adapt, and evolve to handle the uncertainty, change, faults, failure, adversity, and other disruptions present in such applications.

Recent and forthcoming technological advances will provide autonomous systems with many of the sensors, actuators and other functional building blocks required to achieve the desired resilience levels, but this is not enough. To be resilient and trustworthy in these important applications, future autonomous systems will also need to use these building blocks effectively, so that they achieve complex technical requirements without violating our social, legal, ethical, empathy and cultural (SLEEC) rules and norms. Additionally, they will need to provide us with compelling evidence that the decisions and actions supporting their resilience satisfy both technical and SLEEC-compliance goals.

To address these challenging needs, our project will develop a comprehensive toolbox of mathematically based notations and models, SLEEC-compliant resilience-enhancing methods, and systematic approaches for developing, deploying, optimising, and assuring highly resilient autonomous systems and systems of systems. To this end, we will capture the multidisciplinary nature of the social and technical aspects of the environment in which autonomous systems operate - and of the systems themselves - via mathematical models. For that, we have a team of Computer Scientists, Engineers, Psychologists, Philosophers, Lawyers, and Mathematicians, with an extensive track record of delivering research in all areas of the project. Working with such a mathematical model, autonomous systems will determine which resilience- enhancing actions are feasible, meet technical requirements, and are compliant with the relevant SLEEC rules and norms. Like humans, our autonomous systems will be able to reduce uncertainty, and to predict, detect and respond to change, faults, failures and adversity, proactively and efficiently. Like humans, if needed, our autonomous systems will share knowledge and services with humans and other autonomous agents. Like humans, if needed, our autonomous systems will cooperate with one another and with humans, and will proactively seek assistance from experts.

Our work will deliver a step change in developing resilient autonomous systems and systems of systems. Developers will have notations and guidance to specify the socio-technical norms and rules applicable to the operational context of their autonomous systems, and techniques to design resilient autonomous systems that are trustworthy and compliant with these norms and rules. Additionally, developers will have guidance to build autonomous systems that can tolerate disruption, making the system usable in a larger set of circumstances. Finally, they will have techniques to develop resilient autonomous systems that can share information and services with peer systems and humans, and methods for providing evidence of the resilience of their systems. In such a context, autonomous systems and systems of systems will be highly resilient and trustworthy.

Key Findings
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Potential use in non-academic contexts
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Impacts
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Summary
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Organisation Website: http://www.york.ac.uk