The international offshore energy industry currently faces the triple challenges of an oil price expected to remain less than $50 a barrel, significant expensive decommissioning commitments of old infrastructure (especially North Sea) and small margins on the traded commodity price per KWh of offshore renewable energy. Further, the offshore workforce is ageing as new generations of suitable graduates prefer not to work in hazardous places offshore. Operators therefore seek more cost effective, safe methods and business models for inspection, repair and maintenance of their topside and marine offshore infrastructure. Robotics and artificial intelligence are seen as key enablers in this regard as fewer staff offshore reduces cost, increases safety and workplace appeal. The long-term industry vision is thus for a completely autonomous offshore energy field, operated, inspected and maintained from the shore. The time is now right to further develop, integrate and de-risk these into certifiable evaluation prototypes because there is a pressing need to keep UK offshore oil and renewable energy fields economic, and to develop more productive and agile products and services that UK startups, SMEs and the supply chain can export internationally. This will maintain a key economic sector currently worth £40 billion and 440,000 jobs to the UK economy, and a supply chain adding a further £6 billion in exports of goods and services. The ORCA Hub is an ambitious initiative that brings together internationally leading experts from 5 UK universities with over 30 industry partners (>£17.5M investment). Led by the Edinburgh Centre of Robotics (HWU/UoE), in collaboration with Imperial College, Oxford and Liverpool Universities, this multi-disciplinary consortium brings its unique expertise in: Subsea (HWU), Ground (UoE, Oxf) and Aerial robotics (ICL); as well as human-machine interaction (HWU, UoE), innovative sensors for Non Destructive Evaluation and low-cost sensor networks (ICL, UoE); and asset management and certification (HWU, UoE, LIV). The Hub will provide game-changing, remote solutions using robotics and AI that are readily integratable with existing and future assets and sensors, and that can operate and interact safely in autonomous or semi-autonomous modes in complex and cluttered environments. We will develop robotics solutions enabling accurate mapping of, navigation around and interaction with offshore assets that support the deployment of sensors networks for asset monitoring. Human-machine systems will be able to co-operate with remotely located human operators through an intelligent interface that manages the cognitive load of users in these complex, high-risk situations. Robots and sensors will be integrated into a broad asset integrity information and planning platform that supports self-certification of the assets and robots.

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.

Robots and autonomous systems (RAS) will revolutionise the world's economy and society for the foreseeable future, working for us, beside us and interacting with us. The UK urgently needs graduates with the technical skills and industry awareness to create an innovation pipeline from academic research to global markets. Key application areas include manufacturing, construction, transport, offshore energy, defence, and health and well-being. The recent Industrial Strategy Review set out four Grand Challenges that address the potential impact of RAS on the economy and society at large. Meeting these challenges requires the next generation of graduates to be trained in key enabling techniques and underpinning theories in RAS and AI and be able to work effectively in cross-disciplinary projects. The proposed overarching theme of the CDT-RAS can be characterised as 'safe interactions'. Firstly, robots must safely interact physically with environments, requiring compliant manipulation, active sensing, world modelling and planning. Secondly, robots must interact safely with people either in face-to-face natural dialogue or through advanced, multimodal interfaces. Thirdly, key to safe interactions is the ability for introspective condition monitoring, prognostics and health management. Finally, success in all these interactions depends on foundational interaction enablers such as techniques for vision and machine learning. The Edinburgh Centre for Robotics (ECR) combines Heriot-Watt University and the University of Edinburgh and has shown to be an effective venue for a CDT. ECR combines internationally leading science with an outstanding track record of exploitation, and world class infrastructure with approximately £100M in investment from government and industry including the National ROBOTARIUM. A critical mass of over 50 experienced supervisors cover the underpinning disciplines crucial to RAS safe interaction. With regards facilities, ECR is transformational in the range of robots and spaces that can be experimentally configured to study both the physical interaction through robot embodiment, as well as, in-field remote operations and human-robot teaming. This, combined with supportive staff and access to Project Partners, provides an integrated capability unique in the world for exploring collaborative interaction between humans, robots and their environments. The reputation of ECR is evidenced by the additional support garnered from 31 industry Project Partners, providing an additional 23 studentships and overall additional support of approximately £11M. The CDT-RAS training programme will align with and further develop the highly successful, well-established CDT-RAS four-year PhD programme, with taught courses on the underpinning theory and state of the art and research training, closely linked to career relevant skills in creativity, RI and innovation. The CDT-RAS will provide cohort-based training with three graduate hallmarks: i) advanced technical training with ii) a foundation international experience, and iii) innovation training. Students will develop an assessed learning portfolio, tailored to individual interests and needs, with access to industry and end-users as required. Recruitment efforts will focus on attracting cohorts of diverse, high calibre students, who have the hunger to learn. The single-city location of Edinburgh enables stimulating, cohort-wide activities that build commercial awareness, cross-disciplinary teamwork, public outreach, and ethical understanding, so that Centre graduates will be equipped to guide and benefit from the disruptions in technology and commerce. Our vision for the CDT-RAS is to build on the current success and ensure the CDT-RAS continues to be a major international force that can make a generational leap in the training of innovation-ready postgraduates, who will lead in the safe deployment of robotic and autonomous systems in the real world.