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23 November 2017

Major funding for wearable robotics

Wearable robotics, 3D printing of large metal objects, deep learning, extreme microscopy without lenses. In four out of six ‘Perspectief’ funding programmes, the University of Twente is involved.

'Perspectief' programmes stimulate close collaboration of scientists with companies and other organisations. The programmes concern multidisciplinary research with a special emphasis on application. The Netherlands Organisation for Scientific Research (NWO), domain Applied and Engineering Sciences, provides 21 million euros for six programmes, the partners together supplement this with another 11 million.

Wearable robotics: light and comfortable

The programme ‘wearable robotics’ is led by UT Professor Herman van der Kooij. It is aiming at the development of so-called Exo-Aids: soft, comfortable robot technology supporting smooth and versatile movements. Patients with a damaged spinal cord or loss of muscle power, can come out of their wheelchair and stand up without needing crutches. Another application of wearable robots is preventing job-related injuries, like the lower back pain people are suffering from when doing heavy work.

Many of the partners in this programme come from the Twente region: apart from the University of Twente, Baat Medical, BOND 3D, Hankamp Gears, DEMCON, Roessingh Research and Development, Roessingh Revalidatietechniek, Twente Medical Systems and XSens participate.

Printing large metal objects

What will be the properties of large metal objects, like ship propellors, when you 3D print them? As the object is composed of layers, how can we prevent deformation, cracks or rust? The partners in ‘AiM2XL – Additive Manufacturing for Extra Large Metal Components’ will focus on printed metal objects between 1 and 10 metres in size. The project is led by the TU Delft, and it has industrial partners like RAMLAB and VandeGrijp International Gear Suppliers. UT partners are the groups of Nonlinear Solid Mechanics and Design, Production & Management.

EFficient deep learning

Self-learning computers recognize dangerous situations, for example. They have to be trained intensively and demand a lot of computing power. Often, the learning process is a black box, you can’t really see how the systems makes its choices. Is it possible to make this efficient and more transparent, is the central question of the ‘Efficient Deep Learning’ project partners led by the TU Eindhoven. They want to use deep learning in tissue analysis, for example, for intelligent hearing aids and machine maintenance.Apart from the TU Eindhoven and UT, several other knowledge institutions are partner as well as companies like TomTom, Océ, NVIDIA and Schiphol.

Extreme microscopy without lenses

The consortium LINX (Lensless Imaging of 3D Nanostructures with Soft X-Rays) will work on techniqus for imaging of structures as small as 1 nanometer. The partners will not use lenses for this: their method will be based on smart calculation and soft X-Rays (with wavelengths between 10 and 30 nanometres). This smart microscopy technique can be used for finding errors on chips or for visualizing details of solar cells, for example. The project is led by TU Delft, one of the industrial partners is ASML.

The press release of NWO is here.