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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.

Fields of science (EuroSciVoc)

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Host institution

THE UNIVERSITY OF EDINBURGH
Net EU contribution
€ 1 486 463,00
Address
OLD COLLEGE, SOUTH BRIDGE
EH8 9YL Edinburgh
United Kingdom

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Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 1 486 463,00

Beneficiaries (1)