
Scisys (United Kingdom)
Scisys (United Kingdom)
4 Projects, page 1 of 1
assignment_turned_in Project2011 - 2014Partners:University of Stirling, University of Stirling, Industrial Systems and Control (United Kingdom), Scisys (United Kingdom), Industrial Systems and Control (United Kingdom) +4 partnersUniversity of Stirling,University of Stirling,Industrial Systems and Control (United Kingdom),Scisys (United Kingdom),Industrial Systems and Control (United Kingdom),SciSys,University of Stirling,Industrial Systems and Control (United Kingdom),SciSysFunder: UK Research and Innovation Project Code: EP/I009310/1Funder Contribution: 352,598 GBPThe field of autonomous vehicle control (AVC) is a rapidly growing one which promises improved performance, fuel economy, emission levels, comfort and safety.Application of conventional control methods can generate adequate results under restricted circumstances,but have high design and computational costs and are fragile under real environmental changes (winds, proximity of other vehicles etc).There is therefore a pressing need for alternative approaches to AVC.One particularly promising alternative is to break the task into a set of sub-tasks,each valid over a restricted range of conditions, and to switch between them when required.Dr Hussain's group in Stirling has been developing a novel framework for such'modular learning controllers'over the last few years.The problem of selecting from amongst a set of actions or behaviours is also a central problem for animals.There is growing evidence that a set of central brain nuclei -the basal ganglia- are used by all vertebrates to help solve this problem.Research in Prof Gurney's lab has,over the last decade,been developing computational models of how the basal ganglia support behavioural selection.Thus,we believe that the basal ganglia act as a central 'selector' or 'switch' in all vertebrate brains,in that they examine requests for behaviour and allow the most urgent or salient requests to be selected for behavioural expression Given the similarity between the two problems' domains of AVC and action selection in animals, this project aims to leverage new results from psychology and neurobiology (discovered in Prof Gurney's lab) and apply them to the AVC controllers under development in Dr Hussain's group.One aspect of action selection which appears particularly promising in this respect has to do with there being two general modes of behavioural selection.To see this,consider the following scenarios.First,imagine making tea soon after getting out of bed in the morning in your own kitchen.You probably know exactly what to do without having to consciously be aware of it--the location of the tea,milk,sugar,kettle and water-tap are all well learned, as is the motor actions required to interact with the objects in these locations.Introspection after the event leads us to use terms such as;`I did it in my sleep' or `I was on auto-pilot'.Now consider doing the same task if you are staying at a friend's house for the first time.A completely different strategy appears to be used.Thus,we have to be alert, explore, and use high level cognitive knowledge that we hope generalises well (for example,we hope the tea will be in a cupboard near the sink, not in the living room)These two modes of control are well recognised in the psychological literature as automatic and controlled or executive processing respectively.There is also growing neurobiological evidence for the existence of different control regimes, supported by different brain systems.In addition, the new AVC systems developed at Stirling have two major components:a high level 'supervisory' controller and a set of basic (but adaptable) controllers that direct the actual vehicle behaviour.We believe the similarities with the biological notions of executive and automatic control are highly indicative of a mutually fruitful interaction between neuroscientific and control theoretic domains in this regard.Thus, while our general aim is to exploit a range of similarities between systems in control engineering and the animal brain, we will focus specifically on the concepts of automatised and controlled (or executive) processing and how they might map onto modular AVC solutions of the kind described above.The outcome should be a new generation real-time AVC controller, more directly inspired by the biological ideas. We will work with our industrial partners (Industrial Systems Control and SciSys) to evaluate the benefits of these novel controllers within the context of regular road driving and planetary rover vehicles.
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For further information contact us at helpdesk@openaire.euassignment_turned_in Project2014 - 2022Partners:NHS South of England, BAE Systems (Sweden), TUM, Rolls-Royce (United Kingdom), Defence Science and Technology Laboratory +28 partnersNHS South of England,BAE Systems (Sweden),TUM,Rolls-Royce (United Kingdom),Defence Science and Technology Laboratory,National Composites Centre,Rolls-Royce (United Kingdom),Defence Science & Tech Lab DSTL,Scisys (United Kingdom),Blue Bear (United Kingdom),BAE Systems (Sweden),SSSUP,Blue Bear Systems Research Ltd,University of Bristol,Toshiba (United Kingdom),TREL,SciSys,BAE Systems (UK),BAE Systems (United Kingdom),TREL,Rolls-Royce (United Kingdom),SciSys,Rolls-Royce Plc (UK),University of Bristol,OC Robotics,Defence Science & Tech Lab DSTL,OC Robotics,Logic 35,Sant'Anna School of Advanced Studies,Defence Science & Tech Lab DSTL,Logic 35,NHS South of England,NCCFunder: UK Research and Innovation Project Code: EP/L015293/1Funder Contribution: 4,930,860 GBPThe global Robotics and Autonomous Systems (RAS) market was $25.5bn in 2001 and is growing. The market potential for future robotics and autonomous systems is of huge value to the UK. The need for expansion in this important sector is well recognised, as evidenced by the Chancellor of the Exchequer's announcement of £35m investment in the sector in 2012, the highlighting of this sector in the 2012 BIS Foresight report 'Technology and Innovation Futures' and the identification of robotics and autonomous systems by the Minister for Universities and Science in 2013 as one of the "8 great technologies" that will drive future growth. This expansion will be fuelled by a step change in RAS capability, the key to which is their increased adaptability. For example, a home care robot must adapt safely to its owner's unpredictable behaviour; micro air vehicles will be sent into damaged buildings without knowing the layout or obstructions; a high value manufacturing robot will need to manufacture small batches of different components. The key to achieving increased adaptability is that the innovators who develop them must, themselves, be very adaptable people. FARSCOPE, the Future Autonomous and Robotic Systems Centre for PhD Education, aims to meet the need for a new generation of innovators who will drive the robotics and autonomous systems sector in the coming decade and beyond. The Centre will train over 50 students in the essential RAS technical underpinning skills, the ability to integrate RAS knowledge and technologies to address real-world problems, and the understanding of wider implications and applications of RAS and the ability to innovate within, and beyond, this sector. FARSCOPE will be delivered by a partnership between the University of Bristol (UoB) and the University of the West of England (UWE). It will bring together the dedicated 3000 square metre Bristol Robotics Laboratory (BRL), one of the largest robotics laboratories in Europe, with a training and supervising team drawn from UoB and UWE offering a wide breadth of experience and depth of expertise in autonomous systems and related topics. The FARSCOPE centre will exploit the strengths of BRL, including medical and healthcare robotics, energy autonomous robotics, safe human-robot interactions, soft robotics, unconventional computing, experimental psychology, biomimicry, machine vision including vision-based navigation and medical imaging and an extensive aerial robotics portfolio including unmanned air vehicles and autonomous flight control. Throughout the four-year training programme industry and stakeholder partners will actively engage with the CDT, helping to deliver the programme and sharing both their domain expertise and their commercial experience with FARSCOPE students. This includes regular seminar series, industrial placements, group 'grand challenge' project, enterprise training and the three-year individual research project. Engaged partners include BAE Systems, DSTL, Blue Bear Systems, SciSys, National Composites Centre, Rolls Royce, Toshiba, NHS SouthWest and OC Robotics. FARSCOPE also has commitment from a range of international partners from across Europe, the Americas and Asia who are offering student exchange placements and who will enhance the global perspective of the programme.
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For further information contact us at helpdesk@openaire.euassignment_turned_in Project2015 - 2021Partners:CHESS Center,UC Berkeley, NAVTECH RADAR LIMITED, Gompels HealthCare Ltd, MIRA Ltd, ARC Centre of Excellence for Robotic Vis +55 partnersCHESS Center,UC Berkeley,NAVTECH RADAR LIMITED,Gompels HealthCare Ltd,MIRA Ltd,ARC Centre of Excellence for Robotic Vis,Fraunhofer Society,Department for Transport,EURATOM/CCFE,Guidance Navigation Ltd.,ETHZ,Navtech Radar (United Kingdom),Automotive Council UK,Amey Plc,McGill University,Nissan (Japan),Network Rail,PRECISE Center, University of Pennsylvan,United Kingdom Space Agency,SciSys,GGG (France),EURATOM/CCFE,Scisys (United Kingdom),University of California, Berkeley,Eidgenossiche Technical College,Automotive Council UK,UKSA,DfT,MIRA (United Kingdom),HMG,Guidance (United Kingdom),Ferrovial (United Kingdom),Network Rail,Tracetronic,FHG,United Kingdom Atomic Energy Authority,UK ATOMIC ENERGY AUTHORITY,BEIS,Amey Plc,MIRA (United Kingdom),Tracetronic,Nissan Motor Company,Guidance Navigation Ltd.,DfT,SciSys,BP Global,University of Oxford,Network Rail,NAVTECH RADAR LIMITED,MIRA LTD,McGill University,Australian Centre for Robotic Vision,OC Robotics,University of Pennsylvania,OC Robotics,BP Global,UKSA,CGG Services SA,Gompels HealthCare Ltd,GCS,CHESS Center,UC BerkeleyFunder: UK Research and Innovation Project Code: EP/M019918/1Funder Contribution: 4,991,610 GBPVISION: To create, run and exploit the world's leading research programme in mobile autonomy addressing fundamental technical issues which impede large scale commercial and societal adoption of mobile robotics. AMBITION: We need to build better robots - we need them to be cheap, work synergistically with people in large, complex and time-changing environments and do so for long periods of time. Moreover, it is essential that they are safe and trusted. We are compelled as researchers to produce the foundational technologies that will see robots work in economically and socially important domains. These motivations drive the science in this proposal. STRATEGY: Robotics is fast advancing to a point where autonomous systems can add real value to the public domain. The potential reach of mobile robotics in particular is vast, covering sectors as diverse as transport, logistics, space, defence, agriculture and infrastructure management. In order to realise this potential we need our robots to be cheap, work synergistically with people in large, complex and time-changing environments and do so robustly for long periods of time. Our aim, therefore, is to create a lasting, catalysing impact on UKPLC by growing a sustainable centre of excellence in mobile autonomy. A central tenet to this research is that the capability gap between the state of the art and what is needed is addressed by designing algorithms that leverage experiences gained through real and continued world use. Our machines will operate in support of humans and seamlessly integrate into complex cyber-physical systems with a variety of physical and computational elements. We must, therefore, be able to guarantee, and even certify, that the software that controls the robots is safe and trustworthy by design. We will engage in this via a range of flagship technology demonstrators in different domains (transport, logistics, space, etc.), which will mesh the research together, giving at once context, grounding, validation and impact.
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For further information contact us at helpdesk@openaire.euassignment_turned_in Project2014 - 2022Partners:Baker Hughes (United Kingdom), SBT, Thales (United Kingdom), Thales Optronics Ltd, Balfour Beatty (United Kingdom) +85 partnersBaker Hughes (United Kingdom),SBT,Thales (United Kingdom),Thales Optronics Ltd,Balfour Beatty (United Kingdom),Subsea 7 Limited,KUKA Robotics UK Limited,BAE Systems (UK),Edinburgh International Science Festival,KUKA (United Kingdom),BAE Systems (Sweden),Selex-ES Ltd,BAE Systems (Sweden),RENISHAW,HRI-EU,Mactaggart Scott & Co Ltd,Industrial Systems and Control (United Kingdom),Heriot-Watt University,General Dynamics (United Kingdom),RENISHAW,Renishaw plc (UK),Selex ES Ltd,Baker Hughes Ltd,Touch Bionics,Pelamis Wave Power (United Kingdom),Schlumberger (United Kingdom),DI4D,CRRC (United Kingdom),BALFOUR BEATTY RAIL LIMITED,Pelamis Wave Power (United Kingdom),SICSA,Aquamarine Power Ltd,National Institute of Informatics,Industrial Systems and Control (United Kingdom),Pelamis Wave Power (United Kingdom),Kinova (Canada),BALFOUR BEATTY RAIL,Industrial Systems and Control (United Kingdom),AMP,Edinburgh Science Foundation Limited,SBT,Rail Safety and Standards Board (United Kingdom),TRL,SciSys,Mactaggart Scott & Co Ltd,Hydrason Solutions Ltd,Scisys (United Kingdom),KUKA Robotics UK Limited,Leonardo (United Kingdom),YDreams (Portugal),MARZA Animation Planet USA,TRL,Transport Research Laboratory (United Kingdom),Thales Optronics Ltd,YDreams,Soil Machine Dynamics UK,Shadow Robot (United Kingdom),MARZA Animation Planet USA,OC Robotics,SICSA,SCR,Dimensional Imaging (United Kingdom),BP EXPLORATION OPERATING COMPANY LTD,SeeByte Ltd,OC Robotics,SciSys,RSSB,Dyson Appliances Ltd,Renishaw (United Kingdom),BAE Systems (United Kingdom),Subsea 7 Limited,Heriot-Watt University,RSSB,NII,AMP,Shadow Robot Company Ltd,Dyson Appliances Ltd,BALFOUR BEATTY RAIL,Honda (Germany),Dyson Limited,BP (United Kingdom),Mactaggart Scott & Co Ltd,Kinova,Thales Optronics Ltd,HRI-EU,Heriot-Watt University,SCR,Touch Bionics,Hydrason Solutions Ltd,BP EXPLORATION OPERATING COMPANY LTDFunder: UK Research and Innovation Project Code: EP/L016834/1Funder Contribution: 5,784,700 GBPRobots will revolutionise the world's economy and society over the next twenty years, 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, assistive and medical robots, offshore energy, environmental monitoring, search and rescue, defence, and support for the aging population. The robotics and autonomous systems area has been highlighted by the UK Government in 2013 as one the 8 Great Technologies that underpin the UK's Industrial Strategy for jobs and growth. The essential challenge can be characterised as how to obtain successful INTERACTIONS. Robots must interact physically with environments, requiring compliant manipulation, active sensing, world modelling and planning. Robots must interact with each other, making collaborative decisions between multiple, decentralised, heterogeneous robotic systems to achieve complex tasks. Robots must interact with people in smart spaces, taking into account human perception mechanisms, shared control, affective computing and natural multi-modal interfaces.Robots must introspect for condition monitoring, prognostics and health management, and long term persistent autonomy including validation and verification. Finally, success in all these interactions depend on engineering enablers, including architectural system design, novel embodiment, micro and nano-sensors, and embedded multi-core computing. The Edinburgh alliance in Robotics and Autonomous Systems (EDU-RAS) provides an ideal environment for a Centre for Doctoral Training (CDT) to meet these needs. Heriot Watt University and the University of Edinburgh combine internationally leading science with an outstanding track record of exploitation, and world class infrastructure enhanced by a recent £7.2M EPSRC plus industry capital equipment award (ROBOTARIUM). A critical mass of experienced supervisors cover the underpinning disciplines crucial to autonomous interaction, including robot learning, field robotics, anthropomorphic & bio-inspired designs, human robot interaction, embedded control and sensing systems, multi-agent decision making and planning, and multimodal interaction. The CDT will enable student-centred collaboration across topic boundaries, seeking new research synergies as well as developing and fielding complete robotic or autonomous systems. A CDT will create cohort of students able to support each other in making novel connections between problems and methods; with sufficient shared understanding to communicate easily, but able to draw on each other's different, developing, areas of cutting-edge expertise. The CDT will draw on a well-established program in postgraduate training to create an innovative four year PhD, with taught courses on the underpinning theory and state of the art and research training closely linked to career relevant skills in creativity, ethics and innovation. The proposed centre will have a strong participative industrial presence; thirty two user partners have committed to £9M (£2.4M direct, £6.6M in kind) support; and to involvement including Membership of External Advisory Board to direct and govern the program, scoping particular projects around specific interests, co-funding of PhD studentships, access to equipment and software, co-supervision of students, student placements, contribution to MSc taught programs, support for student robot competition entries including prize money, and industry lead training on business skills. Our vision for the Centre is as a major international force that can make a generational leap in the training of innovation-ready postgraduates who are experienced in deployment of robotic and autonomous systems in the real world.
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