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Smart E-skins for Life-like Soft Robot Perception

Project description

Smart e-skins for soft robotics

As robotics becomes more integrated into human society, a key challenge emerges: replicating the sensory intelligence found in living organisms. Developing this capability in robots is crucial for enhancing safety and adaptability in human-robot interactions. Soft robotics, inspired by the pliability of living beings, is a rapidly advancing field. The ERC-funded SELECT project aims to develop smart electronic skins (e-skins) for soft robots to mimic the sensory abilities of organisms. The project will create multimodal e-skins, develop integration models, explore adaptive designs, and apply advanced learning algorithms to decode e-skin data. By combining e-skin sensory attributes with machine learning, the project will redefine soft robot perception, ultimately envisioning human-machine symbiosis.

Objective

Nature, through millennia of evolution, has endowed living organisms with unmatched sensory adaptability. As robotics weave more deeply into the fabric of human society, a compelling challenge emerges: mimicking the sensory intelligence intrinsic to these life forms. The intricate synergy between the organism’s skin and brain, delivering unrivalled sensory insight and data interpretation, epitomises a domain in robotics still uncharted. Cultivating such perceptive sense in robots is crucial; it heralds a future with enhanced safety and adaptability in human-robot interactions, revealing new horizons for innovative applications.

SELECT aims to bridge this perception gap in soft robotics – a rapidly evolving robotic field inspired by the softness of living beings. At the heart of SELECT lies the ambition to pioneer smart electronic skins (e-skins) that resonate with the sensory capability of organisms. SELECT's objectives include:

1. Develop multi-modal e-skins for holistic perception.
2. Build models to simulate the integration of e-skins and robots.
3. Explore automated, adaptive e-skin designs.
4. Advance learning algorithms to decode e-skin data.
5. Streamline e-skin deployment and training.

SELECT's outcomes promise to redefine soft robot perception, synergising e-skin sensory attributes with state-of-the-art machine learning. Beyond advancing robotics, SELECT envisions reshaping our interaction dynamics with intelligent systems, championing a new epoch of human-machine symbiosis.

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2024-STG

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Host institution

THE UNIVERSITY OF EDINBURGH
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 486 463,00
Address
OLD COLLEGE, SOUTH BRIDGE
EH8 9YL Edinburgh
United Kingdom

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Region
Scotland Eastern Scotland Edinburgh
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 486 463,00

Beneficiaries (1)

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