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Details of Grant 

EPSRC Reference: EP/M002527/1
Title: Engineering Fellowships for Growth: Printable Tactile Skin
Principal Investigator: Dahiya, Professor R
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Shadow Robot Company Ltd Touch Bionics
Department: School of Engineering
Organisation: University of Glasgow
Scheme: EPSRC Fellowship
Starts: 01 September 2014 Ends: 31 August 2018 Value (£): 1,085,910
EPSRC Research Topic Classifications:
Control Engineering Instrumentation Eng. & Dev.
Materials testing & eng. Med.Instrument.Device& Equip.
Robotics & Autonomy
EPSRC Industrial Sector Classifications:
Manufacturing Electronics
Related Grants:
Panel History:
Panel DatePanel NameOutcome
12 Mar 2014 Engineering Fellowships for Growth - Robotics Announced
Summary on Grant Application Form
The societal needs such as helping elderly and rapid technological advances have transformed robotics in recent years. Making robots autonomous and at the same time able to interact safely with real world objects is desired in order to extend their range of applications to highly interactive tasks such as caring for the elderly. However, attaining robots capable of doing such tasks is challenging as the environmental model they often use is incomplete, which underlines the importance of sensors to obtain information at a sufficient rate to deal with external change. In robotics, the sensing modality par excellence so far has been vision in its multiple forms, for example lasers, or simply stereoscopic arrangements of conventional cameras. On other hand the animal world uses a wider variety of sensory modalities. The tactile/touch sensing is particularly important as many of the interactive tasks involve physical contact which carry precious information that is exploited by biological brains and ought to be exploited by robots to ensure adaptive behaviour. However, the absence of suitable tactile skin technology makes this task difficult.

PRINTSKIN will develop a robust ultra-flexible tactile skin and endow state-of-the-art robotic hand with the tactile skin and validate the skin by using tactile information from large areas of robot hands to handle daily object with different curvatures. The tactile skin will be benchmarked against available semi-rigid skins such as iCub skin from EU project ROBOSKIN and Hex-O-Skin. The skin will be validated on at least two different industrial robotic hands (Shadow Hand and i-Limb) that are used in dexterous manipulation and prosthetics.

The robust ultra-thin tactile skin will be developed using an innovative methodology involving printing of high-mobility materials such as silicon on ultra-flexible substrates such as polyimide. The tactile skin will have solid-state sensors (touch, temperature) and electronics printed on ultra-flexible substrates such as polyimide. The silicon-nanowires based ultra-thin active-matrix electronics in the backplane will be covered with a replaceable soft transducer layer. Integration of electronic and sensing modules on a foil or as stack of foils will be explored. 'Truly bottom-up approach' is the distinguishing feature of PRINTSKIN methodology as the development of tactile skin will begin with atom by atom synthesis of nanowires and finish with the development of tactile skin system - much like the way nature uses proteins and macromolecules to construct complex biological systems. This new technological platform to print tactile skin will enable an entirely new generation of high-performance and cost-effective systems on flexible substrates. Fabrication by printing will have important implications for cost-effective integration over large areas and on nonconventional substrates, such as plastic or paper. Printing of high-performance electronics is also appealing for mask-less approach, reduced material wastage, and scalability to large area. The proposed programme thus has the potential to emulate yet another revolution in the electronics industry and trigger transformation in various sectors including, robotics, healthcare, and wearable electronics.

Key Findings
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