Summary
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.
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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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101165927 |
| Start date: | 01-09-2024 |
| End date: | 31-08-2029 |
| Total budget - Public funding: | 1 486 463,00 Euro - 1 486 463,00 Euro |
Cordis data
Original description
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.
Status
SIGNEDCall topic
ERC-2024-STGUpdate Date
24-11-2024
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