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.

Driven by the ever-increasing demand for performance enhancement, light weight and function integration, more and more next-generation products/components are designed to possess 3D freeform shapes (i.e. non-rotational symmetric), to integrate different shapes/structures and/or to be made of multi-materials. Examples are seen in freeform lens array photovoltaic concentrators, integrated car head-up displays for improving road safety; Lidar (light detection and range) devices for autonomous vehicle; minimal invasive surgery tools for curing aging related diseases such as cataract blindness, osteoarthritis, and saving lives, to name a few. The ratio of required product tolerance to its dimension is less than 1 part in 10e-6, i.e. in the ultra-precision manufacturing domain. The design, manufacture assembly and characterisation challenges for these products are considerable, requiring a step change in the current manufacturing system to achieve the ambitious target of securing industrial efficiency gains of up to 25% (Industrial Digitalisation Interim Report, 2017) as Britain's productivity has long lagged behind that of its competitors. The project will start from an established baseline in a unique flexible and reconfigurable hybrid micromanufacturing system developed from a recently completed EPSRC project (EP/K018345/1) and advance beyond state-of-the-art of system modelling, digital, control and automation technologies. It will research and develop the underlying science and technology for the creation of a new generation smart digital twin-driven manufacturing system that can sense consumer needs and actively self-optimise for customised next-generation high performance 3D products with enhanced productivity in a sustainable way. It will break new ground in understanding intrinsic links among product design, manufacturing and metrology with a novel product/process fingerprint approach. For the first time, a digital twin-driven automation approach which combines feedback and feed forward control algorithms with inputs from high-frequency digital twins of manufacturing process at machine level will be developed to bridge the real and virtual systems and eliminate dynamic errors and thermal errors which cannot be measured by machine encoders even the machine is running at an extremely high operational frequency to meet the required product performance through predictive control. As such, this project will make a step change in manufacturing automation which is based on linear control theory using semi-closed-looped feedback from encoders. As building blocks of the smart manufacturing system, smart multi-sense in-line surface metrology and smart assembly system will be developed to measure complex and high dynamic surface and to precision assemble large variety of parts that are difficulty to achieve before. A novel multiscale business modelling and system analysis approach will also be developed to allow integration of these smart systems and take the live data, model, predict product quality, delivery time, cost, emission, waste, and optimise the performance into the future in different scenarios. The effectiveness of the SMART will be demonstrated through manufacturing the selected demonstrators including minimal invasive surgery tools, Head-up displays, Lidar and solar cell concentrators. The consortium will transform the research outcome to industry and our society through knowledge exchange, training, industrial demonstration and deployment. A unified expertise pool in smart manufacturing established in this project will be a "one-stop-shop" for the UK industry, particularly SMEs, who are keen to exploit the benefit of the project.