
PAL Robotics
PAL Robotics
2 Projects, page 1 of 1
assignment_turned_in Project2022 - 2025Partners:Blackwood, Cyberselves Universal Limited, Skills for Care, Skills for Care, Medical Device Manufacturing Centre +30 partnersBlackwood,Cyberselves Universal Limited,Skills for Care,Skills for Care,Medical Device Manufacturing Centre,InnoScot Health,Digital Health and Care Institute,North Bristol NHS Trust,NHS Lothian,Bristol Health Partners,NTU,Johnnie Johnson Housing and Astraline,Blackwood Homes and Care,Consequential Robotics Ltd,Innovation Centre for Sensor and Imaging Systems,Johnnie Johnson Housing and Astraline,National Rehabilitation Center,University of Nottingham,Scottish Health Innovations Ltd,National Rehabilitation Center,North Bristol NHS Trust,Cyberselves Universal Limited,CENSIS,Barnsley Hospital NHS Foundation Trust,Sheffield Teaching Hospitals NHS Trust,PAL Robotics,Barnsley Hospital NHS Foundation Trust,Bristol Health Partners,Blackwood Homes and Care,UBC,The Medical Device (United Kingdom),Sheffield Teaching Hospitals NHS Foundation Trust,NHS Lothian,Digital Health and Care Institute,Consequential Robotics (to be replaced)Funder: UK Research and Innovation Project Code: EP/W000741/1Funder Contribution: 708,125 GBPThe EMERGENCE network aims to create a sustainable eco-system of researchers, businesses, end-users, health and social care commissioners and practitioners, policy makers and regulatory bodies in order to build knowledge and capability needed to enable healthcare robots to support people living with frailty in the community. By adopting a person-centred approach to developing healthcare robotics technology we seek to improve the quality of life and independence of older people at risk of, and living with frailty, whilst helping to contain spiralling care costs. Individuals with frailty have different needs but, commonly, assistance is needed in activities related to mobility, self-care and domestic life, social activities and relationships. Healthcare can be enhanced by supporting people to better self-manage the conditions resulting from frailty, and improving information and data flow between individuals and healthcare practitioners, enabling more timely interventions. Providing cost-effective and high-quality support for an aging population is a high priority issue for the government. The lack of adequate social care provisions in the community and funding cuts have added to the pressures on an already overstretched healthcare system. The gaps in ability to deliver the requisite quality of care, in the face of a shrinking care workforce, have been particularly exposed during the ongoing Covid-19 crisis. Healthcare robots are increasingly recognised as solutions in helping people improve independent living, by having the ability to offer physical assistance as well as supporting complex self-management and healthcare tasks when integrated with patient data. The EMERGENCE network will foster and facilitate innovative research and development of healthcare robotic solutions so that they can be realised as pragmatic and sustainable solutions providing personalised, affordable and inclusive health and social care in the community. We will work with our clinical partners and user groups to translate the current health and social care challenges in assessing, reducing and managing frailty into a set of clear and actionable requirements that will inspire novel research and enable engineers to develop appropriate healthcare robotics solutions. We will also establish best practice guidelines for informing the design and development of healthcare robotics solutions, addressing assessment, reduction and self-management of frailty and end-user interactions for people with age-related sensory, physical and cognitive impairments. This will help the UK develop cross-cutting research capabilities in ethical design, evaluation and production of healthcare robots. To enable the design and evaluation of healthcare robotic solutions we will utilize the consortium's living lab test beds. These include the Assisted Living Studio in the Bristol Robotics Lab covering the South West, the National Robotarium in Edinburgh together with the Health Innovation South East Scotland's Midlothian test bed, the Advanced Wellbeing Research Centre and HomeLab in Sheffield, and the Robot House at the University of Hertfordshire covering the South East. Up to 10 funded feasibility studies will drive co-designed, high quality research that will lead to technologies capable of transforming community health and care. The network will also establish safety and regulatory requirements to ensure that healthcare robotic solutions can be easily deployed and integrated as part of community-based frailty care packages. In addition, we will identify gaps in the skills set of carers and therapists that might prevent them from using robotic solutions effectively and inform the development of training content to address these gaps. This will foster the regulatory, political and commercial environments and the workforce skills needed to make the UK a global leader in the use of robotics to support the government's ageing society grand challenge.
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For further information contact us at helpdesk@openaire.euassignment_turned_in Project2019 - 2028Partners:USYD, Chitendai, SICSA, University of Bremen, Leonardo +79 partnersUSYD,Chitendai,SICSA,University of Bremen,Leonardo,EURATOM/CCFE,Chitendai,Schlumberger (United Kingdom),QUT,TechnipFMC (International),Tharsus,Offshore Renewable Energy Catapult,Mactaggart Scott & Co Ltd,Balfour Beatty (United Kingdom),Mactaggart Scott & Co Ltd,SCR,Queensland University of Technology,TechnipFMC (France),University of Maryland, College Park,Shadow Robot Company Ltd,UKAEA,Royal IHC (UK),Codeplay Software,The Data Lab,Five AI Limited,Digital Health and Care Institute,BALFOUR BEATTY RAIL,Hydrason Solutions Limited,Historic Environment Scotland,Royal IHC (UK),ABB (Switzerland),Royal Bank of Scotland (United Kingdom),SeeByte Ltd,BALFOUR BEATTY PLC,Dyson Limited,Heriot-Watt University,SICSA,RASA Technoligies GMBH,Chinese Academy of Sciences,Digital Health and Care Institute,S M C Pneumatics (U K) Ltd,General Dynamics (United Kingdom),S M C Pneumatics (U K) Ltd,Autonomous Surface Vehicles Ltd (ASV),Hydrason Solutions Limited,KUKA (United Kingdom),KUKA Robotics UK Limited,Total E&P UK PLC,Royal Bank of Scotland Plc,Babcock International Group (United Kingdom),Heriot-Watt University,UMB,BAE Systems (UK),Chinese Academy of Sciences,United Kingdom Atomic Energy Authority,Leonardo (UK),Five AI Limited,KUKA Robotics UK Limited,Historic Environment Scotland,FBM Babcock Marine Ltd,RASA Technologies GmbH,Dimensional Imaging Ltd,OFFSHORE RENEWABLE ENERGY CATAPULT,BAE Systems (United Kingdom),CAS,Italian Institute of Technology,Tharsus,Italian Institute of Technology,Fudan University,PAL Robotics,Codeplay (United Kingdom),ASV (United Kingdom),Fudan University,SBT,ABB (United Kingdom),FBM Babcock Marine Ltd,Shadow Robot (United Kingdom),Dyson Appliances Ltd,Total E&P UK PLC,Leonardo (United Kingdom),BAE Systems (Sweden),Dimensional Imaging (United Kingdom),The Data Lab,Offshore Renewable Energy CatapultFunder: UK Research and Innovation Project Code: EP/S023208/1Funder Contribution: 7,174,730 GBPRobots 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.
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