3mE Faculty well represented in NWO’s Perspective programme

News - 21 November 2017 - Webredactie 3ME

The Netherlands Organisation for Scientific Research (NWO) has given six new research programmes the green light within the ‘Perspective for the top sectors’ programme. Professor Ian Richardson (MSE Department) is coordinating the ‘3D printing of large metal components’ programme and professor Frans van der Helm (BME Department) is coordinating the Injury-free exercise’ programme. Researcher Herman van der Kooij is coordinator of the ‘Wearable robotics for people with weak muscles’ programme. He works at the University of Twente and at 3mE’s BME Department. Professor Dariu Gavrila, expert in the field of Intelligent vehicles at the department Cognitive Robotics, leads the Perspectief-Programme ‘Efficient Deep Learning’ from TU Delft.  Professor Corporaal from Eindhoven University of Technology is programme leader. 
The board of NWO Domain Applied and Engineering Sciences (AES) is providing 21 million euros for six large-scale research programmes within the Perspectief funding programme. The companies, civil society organisations and knowledge institutes involved in the programmes will supplement NWO’s funding with another 11 million euros. The overall budget will support 74 PhD candidates and 25 postdocs in their work for the coming five or six years.

With Perspectief, NWO is challenging scientists to establish a close partnership with industry and social organisations. It concerns multidisciplinary research with a special emphasis on application. Together the parties will develop new research lines linked to the top sectors.

32 miljoen euro voor technologisch toponderzoek | NWO-programma Perspectief

Additive Manufacturing for Extra Large Metal Components (AiM2XL)

Programme manager: Professor I.M. Richardson (Delft University of Technology)

Metal-based additive manufacturing (AM), commonly known as '3D printing', is a method in which a metal object is designed with the computer and then built up layer by layer by a machine. This can be done in various ways, and the choice of a particular method influences the speed with which an object can be made, as well as its quality. AM is considered revolutionary, and is already widely used to make relatively small metal objects.

Ian Richardson

Larger scale
The AM technology has the potential to have an enormous impact on a larger scale (objects from 1 to 10 metres), but so far little attention has been paid to this. The intended benefits of AM on a large scale include the ability to construct components where and when necessary, and the design of components combining radically different properties (e. g.: strength, wear resistance, corrosion resistance, mass, and electrical properties). 

One sector for which this programme is expected to be highly relevant is the maritime sector, where major components are needed for the construction and maintenance of ships, and for offshore activities.

Participants: Air Liquide B.V., Allseas, Autodesk, Damen, DEMCON, Element Materials Technology, Fokker Technologies Holding B.V., Heerema Fabrication Group, Huisman, Jungle, Lincoln Electric B.V., Lloyd’s Register EMEA, M2i, MX3D, OCAS NV, RAMLAB, University of Groningen, Shell, Delft University of Technology, Eindhoven University of Technology, Trumpf Nederland B.V., University of Twente, Valk Welding B.V., VandeGrijp International Gear Suppliers B.V.

Also read Ian Richardson leader of major new public-private research programme on additive manufacturing

Injury-free excercise

Citius Altius Sanius – Injury-free exercise for everyone Programme manager: Professor F.C.T. van der Helm (Delft University of Technology)

How do you get people to exercise (and keep exercising), and prevent them from becoming injured in the process? The Citius Altius Sanius (faster, higher, healthier) programme develops and uses innovative wearable sensors to measure the physical and physiological burden, data science to calculate the risk of injury for individual athletes, and proven effective personalised feedback methods to influence the behaviour of athletes at all performance levels. The researchers are not only developing the necessary theory and technology. They are also testing whether common sports injuries can be prevented in sports such as fitness training, soccer, tennis, long-distance running and cycling. Sports clubs, sports physicians and physiotherapists, among others, have joined the programme. They will use the results during sports training and rehabilitation.

Frans van der Helm

Participants: Achmea, Adidas, AMC, Borre, Bosch, Cinoptics, Dopple, Fit!Vak, Fontys Hogescholen, Municipality of Amsterdam, Municipality of Eindhoven, Golazo Sports SX, The Hague University of Applied Sciences, Hanze University of Applied Sciences Groningen, Amsterdam University of Applied Sciences, HAN University of Applied Sciences, Inmotio Object Tracking, InnosportLab Sport & Movement, International Tennis Federation, IZI BodyCooling, Knowledge Centre for Sport Netherlands, ManualFysion, 2M Engineering, Motekforce Link, MYLAPS, MyTemp, NedCard, NHTV Breda, Nijmeegse Vierdaagse Foundation, NOC*NSF, Noldus, NovioSense, Plux, Qualogy, Radboudumc, Reade Rehabilitation, University of Groningen, National Sports Federations (KNBSB, KNHB, KNLTB, KNVB, KNWV), Koninklijke Gazelle, Sailing Innovation Center, SWOV, Team Sunweb, Delft University of Technology, Eindhoven University of Technology, Leiden University, VirtuaGym, VU Amsterdam, VUmc, Zevenheuvelenloop Foundation

Wearable robotics for weak muscles

Wearable robotics
Programme manager: Professor H. van der Kooij (University of Twente)

People who are confined to a wheelchair as a result of a muscular disorder should be able to stand independently again without needing to use crutches. This would allow them to cook at a counter in an upright position, for example. This is not a divine miracle but a feasible goal set by the Wearable Robotics research consortium. This programme develops so-called Exo-Aids: soft, lightweight technology that wears comfortably, is easy to operate and affordable, and makes smooth and versatile movements possible. The aim is to increase the mobility and independence of people with damage to their spinal cord or loss of muscle strength. In addition, the researchers are developing a technology to prevent work-related complaints such as lower back pain. These complaints are common among people who have to lift heavy objects or stand in a hunched position for long periods of time.

Herman van der Kooij

Participants: Baat Medical, Bond 3D, By-wire, DEMCON, Duchenne Parent Project, Dwarslaesie Organisatie Nederland, Festo, FSHD Patient Foundation, Hankamp Gears, Hocoma, IMSystems, Laevo, Landelijke Vereniging van Operatieassistenten, Motek, Oceanz, Opteq, Ottobock, Radboudumc, Roessingh Research and Development, Roessingh Revalidatie Techniek, Delft University of Technology, Sint Maartenskliniek, Spieren voor Spieren, Eindhoven University of Technology, TNO, Twente Medical Systems International, Ultimaker, University of Twente, VU Amsterdam, Xsens, Yumen Bionics


Read more in : TU Delft to lead three new, large-scale public-private research programmes

Efficiënte zelflerende systemen
Efficient Deep Learning
Programmaleider: Prof.dr. H. Corporaal (Technische Universiteit Eindhoven)

The Intelligent Vehicles group at TU Delft leads sub-project “Mobile Robotics” and will receive funding for two PhD positions related to automated driving. One PhD position involves research on deep learning for efficient mapping and localization, in collaboration with TomTom. The second PhD position addresses research on deep learning for 3D semantic traffic scene analysis, in collaboration with 2getthere. Read more about their research on the website of Intelligent Vehicles. 

Dariu Gavrila

A computer that recognises dangerous situations on security footage: this is possible with deep-learning automated systems. But before this kind of system can operate independently, you have to design it and then train it with a huge number of examples. In addition, you need considerable computing power to let the system make decisions. At the Efficient Deep Learning programme, researchers are going to make deep learning much more efficient by using examples from daily life. They want to make it possible to use the technique (Of: They want to make the technique applicable) for other automatic visual inspections, tissue analysis, smart maintenance of equipment and intelligent hearing aids that can handle noisy environments.

Participants: AIIR Innovations, ASTRON, CWI, Cyclomedia, Cygnify, Donders Institute, FEI, 2getthere, GN Hearing, Holst Centre, ING, Intel, Irdeto, Lely, Mobiquity, NLeSC, NXP, NVIDIA, Océ, Radboudumc, Schiphol, Scyfer, Sectra, Semiotic Labs, Siemens, Sightcorp, Sorama, SURFsara, TASS International, Tata Steel, TU Dresden, Delft University of Technology, Eindhoven University of Technology, Thales, TNO, TomTom, University of Twente, University of Amsterdam, 3DUniversum, VicarVision, ViNotion, VU Amsterdam, Wageningen University & Research