
NAVTECH RADAR LIMITED
NAVTECH RADAR LIMITED
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4 Projects, page 1 of 1
Open Access Mandate for Publications and Research data assignment_turned_in Project2021 - 2024Partners:DEMATIC, APPLIED AUTONOMY AS, FORESIGHT AUTOMOTIVE LTD, DFDS AS, SCHENKER & CO AG +26 partnersDEMATIC,APPLIED AUTONOMY AS,FORESIGHT AUTOMOTIVE LTD,DFDS AS,SCHENKER & CO AG,Enide Solutions (Spain),EASYMILE,TEKNOLOGIAN TUTKIMUSKESKUS VTT OY,FH OO,AVINOR AS,CONTINENTAL AUTONOMOUS MOBILITY GERMANY GMBH,LCM,Cerema,ASSOCIATION CARA,NAVTECH RADAR LIMITED,Business Upper Austria,KAMAG TRANSPORTTECHNIK GMBH & CO.KG,INTERNATIONAL ROAD TRANSPORT UNION (IRU),AIT,TERBERG BENSCHOP,SMART AIRPORT SYSTEMS,CERTX AG,OTTOPIA TECHNOLOGIES LTD,FRANCE AVIATION CIVILE SERVICES,Adasky,BRP-POWERTRAIN GMBH & CO KG,IRU PROJECTS ASBL,ITS NORWAY,CONTINENTAL TEVES,AUSTRIATECH,DIGITRANS GMBHFunder: European Commission Project Code: 101006817Overall Budget: 26,014,700 EURFunder Contribution: 19,892,900 EURConnected and automated vehicles can be seen as a revolution in the global automotive industry, bringing a new mobility paradigm and having a huge impact on several economic sectors such as logistics industry. Significant progress has been made in the field of autonomous truck driving with numerous prototypes. However, challenges need to be addressed in order to ensure the uptake of this breakthrough technology and the future advent of an overall autonomous logistic chain. The deployment of autonomous heavy-duty vehicles is hindered by the current inabilities of these vehicles to work with the right safety and functional level for 24/7 availability (e.g. harsh weather conditions) and by the lack of harmonized regulatory framework. This project aims at developing and enabling to deploy a safe autonomous transportation systems in a wide range of real-life use cases in a variety of different scenarios. This encompasses the development of autonomous driving system (ADS) capable of handling adverse environmental conditions such as heavy rain, snowfall, fog. The ADS solution will be based on multiple sensor modalities to address 24/7 availability. The ADS will then be integrated into multiple vehicle types used in low-speed areas. Finally, these vehicles will be deployed, integrated and operated in a variety of real-life use cases to validate their value in the application and identify any limitations: forklift (un)loading in warehouses and industrial plants, hub-to-hub shuttle service on open road, automated baggage dispatching in airports, container transfer operations and vessel loading in ports. Logistics operations will be optimized thanks to a new fleet management system that will act as a control tower, gathering all information from subsystems (vehicles, road sensors, etc.) to coordinate the operations and protect vulnerable road users. This work should then enable commercial exploitation of the technology and policy recommendations for certifications processes.
more_vert assignment_turned_in Project2010 - 2016Partners:Bae Systems Defence Ltd, BAE Systems, Guidance (United Kingdom), BAE Systems (Sweden), Massachusetts Institute of Technology +12 partnersBae Systems Defence Ltd,BAE Systems,Guidance (United Kingdom),BAE Systems (Sweden),Massachusetts Institute of Technology,Massachusetts Institute of Technology,Nissan (Japan),Department for Transport,Navtech Radar Limited,NAVTECH RADAR LIMITED,DfT,University of Oxford,Guidance Navigation Ltd.,Nissan Motor Company,GCS,BAE Systems (United Kingdom),MITFunder: UK Research and Innovation Project Code: EP/I005021/1Funder Contribution: 1,655,490 GBPIn the future, autonomous vehicles will play an important part in our lives. They will come in a variety of shapes and sizes and undertake a diverse set of tasks on our behalf. We want smart vehicles to carry, transport, labour for and defend us. We want them to be flexible, reliable and safe. Already robots carry goods around factories and manage our ports, but these are constrained, controlled and highly managed workspaces. Here the navigation task is made simple by installing reflective beacons or guide wires. This project is about extending the reach of robot navigation to truly vast scales without the need for such expensive, awkward and inconvenient modification of the environment. It is about enabling machines to operate for, with and beside us in the multitude of spaces we inhabit, live and work. Even when GPS is available, it does not offer the accuracy required for robots to make decisions about how and when to move safely. Even if it did, it would say nothing about what is around the robot and that has a massive impact on autonomous decision-making.Perhaps the ultimate application is civilian transport systems. We are not condemned to a future of congestion and accidents. We will eventually have cars that can drive themselves, interacting safely with other road users and using roads efficiently, thus freeing up our precious time. But to do this the machines need life-long infrastructure-free navigation, and that is the focus of this work.We will use the mathematics of probability and estimation to allow computers in robots to interpret data from sensors like cameras, radars and lasers, aerial photos and on-the-fly internet queries. We will use machine learning techniques to build and calibrate mathematical models which can explain the robot's view of the world in terms of prior experience (training), prior knowledge (aerial images, road plans and semantics) and automatically generated Web queries. The goal is to produce technology which allows robots always to know precisely where they are and what is around them. Robots have a big role to play in our future economy, but underpinning this role will be life-long infrastructure-free navigation.
more_vert assignment_turned_in Project2015 - 2021Partners:OC Robotics, Gompels HealthCare Ltd, McGill University, EURATOM/CCFE, United Kingdom Atomic Energy Authority +45 partnersOC Robotics,Gompels HealthCare Ltd,McGill University,EURATOM/CCFE,United Kingdom Atomic Energy Authority,Automotive Council UK,Gompels HealthCare Ltd,DfT,BEIS,SciSys,NAVTECH RADAR LIMITED,University of Oxford,Guidance Navigation Ltd.,PRECISE Center, University of Pennsylvan,BP Global,Tracetronic,CGG Services SA,Guidance (United Kingdom),MIRA Ltd,Eidgenossiche Technical College,Network Rail,Amey Plc,Fraunhofer,CGG Services SA (Global),CHESS Center,UC Berkeley,Nissan Motor Company,Nissan (Japan),EPFZ,UK ATOMIC ENERGY AUTHORITY,Automotive Council UK,GCS,ARC Centre of Excellence for Robotic Vis,SciSys Ltd,UK Space Agency,Department for Transport,FHG,Network Rail Ltd,Tracetronic,McGill University,OC Robotics,University of Pennsylvania,Motor Industry Research Assoc. (MIRA),ARC Centre of Excellence for Robotic Vis,University of California Berkeley,MIRA LTD,UKSA,Amey Plc,Navtech Radar Limited,CHESS Center,UC Berkeley,BP GlobalFunder: 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.
more_vert assignment_turned_in Project2013 - 2015Partners:ITAINNOVA, INNORA S.A., NAVTECH RADAR LIMITED, NSOLVER, Aer Lingus (Ireland) +4 partnersITAINNOVA,INNORA S.A.,NAVTECH RADAR LIMITED,NSOLVER,Aer Lingus (Ireland),UK-ISRI,iKH,MEL,WLB Limited (Cyprus)Funder: European Commission Project Code: 314838more_vert