Vision
To create a world leading scientific programme of data driven AI research and innovation that addresses the unique challenges arising from and towards deployment of robotics and autonomous systems (RAS) technology for solving socially relevant problems across domains in a trustworthy, verifiable, and equitable manner.
Aims
The key aim of this strategic programme is to develop and support a world leading portfolio of activities that will lie at the intersection of data driven AI and machine learning, specifically targeted to the robotics and autonomous systems (RAS) domain. This will be achieved through:
- Building and funding a core research team investigating ‘fundamental’ algorithmic and computational innovations under three key strands, with a research team lead heading each strand
- Developing joint industry projects (JIPs) through deep dive engagements with industry for technologies that are at medium to high 'technology readiness levels' – with at least 50-75% of core funding coming from industry
- De-risking deployment through proof of concept implementations in several partner ‘living labs’ that integrate hardware and data processing challenges
Programme challenges
The core research agenda will be focused through three strands (that are crucial but are missing or underrepresented elements in the current RAS and machine learning roadmap).
Each of these strands of research will be closely grounded in the RAS context and will have a grand challenge counterpart that it can enable, if successful. However, we will actively look for synergies where some of the results (for example in explainable and verifiable AI) can be applied to domains beyond RAS such as Internet of Things, medical diagnostics, etc.
Scalable algorithms under constraints
Real time inference requirements, computational constraints of embedded, untethered and mobile platforms, hardware limits (torque, joint) for guaranteeing safety, representation and approximate hierarchical inference that achieve graceful performance degradation under adversarial and stochastic real world environments.
Methods for efficient multi-agent computations
Intention detection and movement prediction, scalable multi-agent adversarial and collaborative policies, multi-modal sensor aggregation for decision making.
Verifiable, robust and explainable decision-making for multi-modal RAS assets
Enabling secure systems – communication, decision making; understanding and predicting failure modes, developing robustness and multiple failure recovery modes, fault and risk inference through probabilistic modelling. Algorithmic transparency, fairness and ethical implications arising out of RAS deployment.
Impact
The programme's engagement approach will aim to create a tangible pipeline that can take strong research and innovation to tangible deployable solutions. The solutions will deliver concrete benefits to society by closely working with various stakeholders – the government, local councils and industry.
The core research programme will identify and develop fundamental AI and machine learning underpinnings that need solving in the RAS domain. This will engage current EPSRC Centres for Doctoral Training (CDT) in Robotics, Data Science and Artificial Intelligence as well as their key scientific leads. Some of the Turing PDRA fellowships in this area are intended to act as a first opportunity for our brightest CDT graduates to play a leadership role.
In addition, we will leverage several world leading sites with substantial RAS assets in terms of cutting edge hardware platforms, to enable stakeholder testing of proof of concept deployments in living labs. We already have several UK wide national robotics hardware and field testing facilities in Edinburgh, Oxford, Bristol, London, Sheffield, and others.
In conjunction with the living labs at the Bayes’ Centre in Edinburgh (the site of the Turing's robotics hub), we will work in domains ranging from oil and gas, mining, nuclear decommissioning, construction, smart mobility, high value manufacturing (e.g. aircraft), healthcare and smart assisted living space to galvanise industrial engagements through joint industry projects (JIPs) as well as proof-of-concept demonstrations for de-risking in realistic settings.
Finally, engagement with the government and funding agencies (including UKRI, BEIS and learned societies like RAEng, Royal Society, and Royal Society of Edinburgh) will help shape future research funding as well as policy making for enabling, de-risking and deploying RAS technology with the help of innovations in AI and data science.
News
Edinburgh Science Festival
The Edinburgh Centre for Robotics are involved in world leading research on robots for human assistance. They opened their laboratory to adults and children to discover cutting-edge robotic research, meet humanoid robots and learn the ways robots can assist humans.
Further information on the Edinburgh Science Festival can be found here Bayes Centre Tour: Meet the Robots | InfWeb (ed.ac.uk)
Embracing contacts
The workshop Embracing Contacts took place on the 2nd of June of 2023 at the IEEE International Conference on Robotics and Automation (ICRA), in London. The main aim of the workshop was to foster a lively and multidisciplinary discussion about the most recent theoretical, technological, and translation aspects of contact-rich manipulation approaches, to provide the younger audience the unique opportunity to gain a wide and general overview of the field from different perspectives.
The workshop counted with multiple activities such as panel discussions, invited talks, poster sessions, and even some table-top dexterity games for the participants to socialize and have fun. The workshop gathered nine exceptional invited speakers, all of them renowned researchers tackling contact-rich manipulation tasks using various different approaches—from model-based to machine learning—which made for very exciting discussions in the panel sessions.
The event reached an audience of over 200 people attending in person, with many young students and researchers but also with quite a few established researchers in the field. The interactive session counted with 22 poster presentations from young researchers, that got the opportunity to showcase their work during the poster session and other breaks and also to introduce their work in a one minute spotlight presentation to the entire workshop audience.
Organisers
Dr Stefano Albrecht
Group Leader (Multi-Agent RAS Systems)
Professor Nick Hawes
Group Leader (Human Robot Interfaces)
Dr Atoosa Kasirzadeh
Group Leader (Verifiable, Explainable RAS Interfaces)
Suzanne Perry
Projects Manager, AI (Robotics) (University of Edinburgh)
Dr João Moura
Research Associate
Dr Wenqian Du
Research Associate
Dr Namiko Saito
Research Associate
