Deliverbles from The INTUITIVE Project

These Deliverables have a public dissemination level and are shown as soon as they’ve been approved.

D1.4 Supervisory board

Supervisory board appointed

D1.6 Data Management Plan

Guidlines for Open Data Management within the project

D1.8 Third year progress report

Report on the progress for the first three years

D2.1 First representation of haptic input features across a population of cortical neurons

Learning the multiple, parallel in vivo whole cell patch clamp recording technique in the neocortex of the rat. Exploring the representation of haptic input features in neocortical neurons. Tuning properties of neocortical neurons with respect to the haptic input features representation of haptic input features across a population of cortical neurons.

D2.2 Principles of brain state influence on neural representation of haptic input features

Controlled manipulation of brain states via basal ganglia or corticocortical manipulation. Investigation of neural representation of haptic events across brain states

Analyse closed-form electro/thermal scaling laws for miniaturization. Realise computer aided-design based on the analysis and perform multi-physics simulation. Implement physical miniaturized system.

D2.4 Report on molecular scale mechanism of mechanoreceptors in skin 

Develop molecular scale model of mechanoreceptors of the skin. Incorporate biomimetic mechanoreceptor models in synthetic material to be used for artificial skin.

D2.6 Multi-scale model of synthetic materials mimicking tactile sensing in skin

Validate in-silico model with experimental data. Use the in silico model for design and development of realistic tactile sensing skin

D3.1 Learning classifier system for high-dimensional sensorimotor data

Characterization of neuromimetic sensorimotor processing. Identification of tactile interaction invariants. Implement learning classifier system for high-dimensional data

D3.2 Next generation sensory augmentation device

Integration of tactile stimulators in a sensory augmentation device. Design and test mapping of sensory information (orientation, distance to obstacles, dynamics of approach and recess) to degrees of freedom of sensory augmentation device (frequency domain, AM-modulation, selection of simultaneously active tactors (UOS). Usability study and validation of behavioural benefits

D3.3 Predictive coding model of haptic sensing

Abstract model of haptic sensing integrating tactile and proprioceptive information. Predictive coding modelling of tactile sensing in rodents. Human-like computational model of haptic sensing for robots.

D4.2 Graphene based touch sensor and benchmarking

Fabrication of graphene based touch sensors

D4.4 Sensors with memory

Demonstrator of the properties of the sensors based on memristive device

D4.5 softMEMS based stress and slip sensors

Design and fabrication cantilever based sensors on ultra-thin chips. Characterization of sensors for stress and slip. Embedding sensors in soft materials and connecting to electronics with transparent electrodes

D4.6 Low-power sensory readout and electronic interface

Architectural study of time-based sensor readout in CMOS. Circuit design and layout of a low-power time-based sensor interface in CMOS.

D4.7 Ultra thin chips based sensory interface

Thinning of the chip and testing with various sensors.

D4.8 Integration on flexible substrates – survey and limitation of existing methods

Literature survey analysing the suitability of some of planar electronics integration methods for soft electronics. Stretchable interconnections and stiff sensor/electronics integration configuration.

D4.9 Embedded integration of sensors/electronics at various depths in soft substrates

Integration of sensors at various depths in soft substrates – towards 3D integration of sensor distribution.

D5.1 Taxonomy of image processing algorithms in the context of categorizing tactile graphics

Systematic analysis of ‘translating and simplifying visual to tactile graphics’ by a literature review

D5.2 Design guidelines for representing audio-tactile graphics on a two-dimensional display 

Employ deep learning to categorise certain types of graphics. Development of a prototype to translate visual to tactile information. Evaluate the system with blind users on a two-dimensional tactile display. Investigate the combination of audio-output with tactile output.

D5.3 Haptic integration of proprioception and tactile information for robots

Implementation of predictive coding based haptic exploration with a robot hand. Complex haptic exploration (using Markov chain formalism) and manipulation.

D5.4 Human-like haptic exploration and manipulation

Comparison of robotic and human manipulation and haptic exploration

D5.5 Classification of 2D refreshable tactile user interfaces

Literature review of the user interfaces and interaction

D5.6 Design principles and basic version of the intuitive tactile user interface

Software prototype for the new user interface allowing interaction between the Tactonom and computer

D5.7 Audio-Tactile Design Pattern Repository

Repository of designed patterns for combination of audio-output with tactile output

D6.1 Submission/Award of PhD thesis

Submission of PhD thesis for Award competition

D6.2 First year research schools, workshops, & tutorials

Report on the research schools, workshops and tutorials organized the first year of the project

D6.3 Second year research schools, workshops, & tutorials

Report on the research schools, workshops, and tutorials organized the second year of the project.

D6.4 Third year research schools, workshops, & tutorials

Report on the research schools, workshops, and tutorials organized the third year of the project