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Scalable Electronic-skins for Autonomous Intelligence in Soft Robotics

Objective

In the emerging era of physical intelligence, soft robotics offers a transformative pathway to safe, adaptive, and intelligent human–machine interactions. Yet this vision remains constrained by a fundamental limitation: today’s soft robots largely operate “blind” due to the lack of scalable, high-resolution sensing systems that can capture both distributed tactile interactions and body deformations. This absence critically undermines their ability to perceive, adapt, and act autonomously in real-world environments.

FLEX-AI aims to address this bottleneck by translating a breakthrough stretchable electronic skin (e-skin), developed under the ERC SELECT project, into scalable, application-ready solutions that enable autonomous soft robotic behaviours. This e-skin uniquely integrates simultaneous, high-resolution sensing of both touch and deformation within a single, conformal, stretchable platform, capabilities never achieved before. This project will pioneer robust, scalable fabrication methods for mass-producible e-skins and validate their generalisation and usability across diverse robotic platforms. Another central ambition is to enable real-time perception–action loops by embedding the e-skin into soft machines and developing lightweight, on-device control frameworks. This will demonstrate soft robots that can perceive, decide, and adapt autonomously to environments.

By addressing critical technological, fabrication, and integration challenges, FLEX-AI will de-risk the pathway from lab-scale prototypes to commercially viable products. Target applications include healthcare robotics and assistive devices, where safe, intelligent physical interaction is essential. By uniting scalable fabrication, multimodal perception, and autonomy-driven control, FLEX-AI will redefine the capabilities of soft robots. The project has the potential to unlock new markets, deliver broad societal impact, and establish Europe as a global leader in next-generation robotics innovation.

Fields of science (EuroSciVoc)

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2025-POC

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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.

€ 150 000,00
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.

No data

Beneficiaries (1)

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