SAIR: Safe and Secure AI for Robotics – LAIV: Lab for AI Verification

Welcome to SAIR Research Theme page!

The National Robotarium and the Edinburgh Center for Robotics identified several high-priority research themes. This is the page of the Research Theme SAIR: Safe and Secure AI for Robotics. The theme has just opened, and is gradually building up.

What motivates our research:

Significant advances in Machine Learning led to its ubiquitous deployment in autonomous systems. However, Machine Learning is a black-box technology; therefore, any system that adopts it potentially jeopardises its safety, security, and interoperability. The significance of this problem has been recognised internationally, giving rise to EU AI Act and The Bletchley Park AI Declaration. For AI and autonomous systems like robots to be trusted we have ensure that they work for society in a responsible, verifiable, ethical, legal and safe manner.

SAIR Theme Co-leads:

Prof. David Aspinall (UoE),
Prof. Ekaterina Komendantskaya (HWU),
Dr Ioannis Konstas (HWU),
Dr Marta Romeo (HWU)

Participating Researchers and Research Groups:

Dependable Systems Group, HWU
Lab for AI and Verification, HWU
Security and Privacy Group, Edinburgh University
40+ multidisciplinary researchers from UoE and HWU with representatives from SoSS and Business School

Topics we Investigate:

Building safer and more secure machine-learning components
Verification of neural networks and robot behaviour
Robust use of machine learning in security applications
Formal properties of learning and autonomous systems
Legal requirements to autonomous systems
The interaction between human factors (e.g. individual differences in trust) and robotic systems
The impact of AI on the future of work
The economics of robotics: costs/benefits
Safety/Ethics in Large Language Models, Vision and Language Models
Hate Speech and Abusive Language to/from Robotic Agent
Miscommunication, Repair and Adaptation in Conversational Interaction

SAIR Seminars and Events:

All seminars advertised here are open to any interested researcher (you do not need a subscription). Below you will find information on how to join, in face-to-face mode or online. However, if you would like to join our mailing list and receive updates, please fill in this registration form.

Date	Topics
10th December 2024, 11.00 am Informatics Forum and Online	Inaugural SAIR lecture, by Professor Subramanian Ramamoorthy, School of Informatics, University of Edinburgh Title: Safety and Trustworthiness of Human-Centred Autonomous Systems Abstract: With AI systems becoming increasingly more capable, there is growing interest in questions around safety, trustworthiness and explainability. For embodied AI systems such as autonomous systems, especially robots operating in human-centred application domains, these considerations translate into desiderata for AI and systems design. In this talk, I’ll describe results from a few recent projects addressing learning and adaptive decision making in human-robot interaction contexts, ranging from surgical skills to autonomous driving. I will try to distill learnings from these in terms of a few thematic questions that define my current research agenda. Bio: Subramanian Ramamoorthy is a Professor of Robot Learning and Autonomy in the School of Informatics at the University of Edinburgh, where he is also Director of the Institute of Perception, Action and Behaviour, and Director of the UKRI AI CDT in Dependable and Deployable AI for Robotics. He holds a UKRI Turing AI World-Leading Researcher Fellowship (2024 – 29). His research focus is on robotics and machine learning, with particular emphasis on achieving safe and robust autonomy in human-centred environments. This work has attracted funding from a variety of sources including UKRI, EU, DARPA, DSTL and the Royal Academy of Engineering, and been recognised with best paper awards at international conferences including ICRA, IROS, CoRL, ICDL and EACL. In addition to his academic role, he has been involved in Five AI, a UK based technology company developing autonomous vehicles technology, as Vice President – Prediction and Planning (2017 – 2020) and Scientific Advisor (2021-23). Five AI was acquired by Bosch GmbH in 2022.

Date

Topics

10th December 2024,
11.00 am
Informatics Forum and Online

Inaugural SAIR lecture, by Professor Subramanian Ramamoorthy, School of Informatics, University of Edinburgh

Title: Safety and Trustworthiness of Human-Centred Autonomous Systems

Abstract: With AI systems becoming increasingly more capable, there is growing interest in questions around safety, trustworthiness and explainability. For embodied AI systems such as autonomous systems, especially robots operating in human-centred application domains, these considerations translate into desiderata for AI and systems design.

In this talk, I’ll describe results from a few recent projects addressing learning and adaptive decision making in human-robot interaction contexts, ranging from surgical skills to autonomous driving. I will try to distill learnings from these in terms of a few thematic questions that define my current research agenda.

Bio: Subramanian Ramamoorthy is a Professor of Robot Learning and Autonomy in the School of Informatics at the University of Edinburgh, where he is also Director of the Institute of Perception, Action and Behaviour, and Director of the UKRI AI CDT in Dependable and Deployable AI for Robotics. He holds a UKRI Turing AI World-Leading Researcher Fellowship (2024 – 29).

His research focus is on robotics and machine learning, with particular emphasis on achieving safe and robust autonomy in human-centred environments. This work has attracted funding from a variety of sources including UKRI, EU, DARPA, DSTL and the Royal Academy of Engineering, and been recognised with best paper awards at international conferences including ICRA, IROS, CoRL, ICDL and EACL.

In addition to his academic role, he has been involved in Five AI, a UK based technology company developing autonomous vehicles technology, as Vice President – Prediction and Planning (2017 – 2020) and Scientific Advisor (2021-23). Five AI was acquired by Bosch GmbH in 2022.