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Call key data

Robust and trustworthy GenerativeAI for Robotics and industrial automation (AI/Data/Robotics & Made in Europe Partnerships)

Funding Program

Horizon Europe: Cluster 4 - Digital, Industry and Space

Call number

HORIZON-CL4-2025-03-DIGITAL-EMERGING-07

deadlines

Opening
10.06.2025

Deadline
02.10.2025 17:00

Funding rate

100%

Call budget

€ 85,000,000.00

Estimated EU contribution per project

between € 40,000,000.00 and € 45,000,000.00

Link to the call

ec.europa.eu

Link to the submission

ec.europa.eu

Call content

short description

Proposals integrating Generative AI in robotics and industrial automation are expected to substantially contribute to productivity gains, including for instance in engineering industries, the automotive sector, food production or other sectors related to manufacturing industries. All proposals will have to demonstrate their expected impact on the competitiveness of the selected application sector.

Call objectives

The budget will be split in a balanced way between area Type A and Type B defined below. Proposals should clearly identify the area they are addressing.

Proposals aiming for Type A outcomes should adhere to the Type A scope, while proposals aiming for Type B outcomes should follow the Type B scope.

Type A Scope: 

While it is widely acknowledged that current use of generative AI has the potential to impact certain tasks in robotics such as improving user interaction or providing explanations about why a robot system made a particular decision, these are, in general, not within the critical operating flow of a robot. To reach next level of autonomy, generative AI must also enable robots to learn from their experiences, simulate realistic environments for training in challenging conditions, and enhance planning, decision making and control while considering the physical constraints imposed both by the environment and by the physical construction of the robot. This includes integrating 'Human-in-the-loop' mechanisms, where AI systems collaborate with human operators to enhance decision-making processes and adaptability, particularly in dynamic environments.

This represents a significant advancement in robotics, requiring the development of AI models that can effectively navigate the complexities of the physical world while ensuring safety. Generative AI is expecting to bring such a step-change in robots precision, adaptability, versatility and robustness, enabling them to efficiently achieve real world tasks such as complex moves (navigation, manipulations, etc.) with higher level of autonomy and precision.

In the context of advancing robotics capabilities, the use of generative AI stands as a transformative force, amplifying robots’ learning, interaction, and operational abilities. By enabling robots to learn from experiences, simulate diverse environments for training, and enhance human-robot interaction, it drives adaptability and efficiency. Additionally, generative AI facilitates the augmentation of robot situational awareness and planning capabilities, empowering them to predict outcomes of various actions, thereby elevating their autonomy and decision-making prowess.

Training current generative AI models, in particular Large AI models, requires high volumes of data to achieve effective levels of performance. The vast amount of data required present a significant challenge when it comes to robotics. Further research is necessary to find the appropriate balance between the quality, adequacy, and volume of data with regards to the performance of the AI model. Moreover, model distillation techniques may play a key role for the portability of the generative AI solution at the edge, in power-limited devices. The training data should come from the real world or from physical aware simulations of the real world. Where relevant, in particular in the context of human interaction, training data should encompass diverse individual characteristics, such as gender, age, racial and ethnical background, to mitigate potential bias and discriminations.

Proposals should detail strategies to leverage cutting-edge generative AI techniques to enhance the adaptability and reliability of these models across complex and dynamic scenarios, as well as how to ensure human-centricity and environmental considerations. The goal is to train and fine-tune generative AI models that meet the necessary standards for ensuring the safe operation of robotics hardware. These models should empower robots to autonomously plan and execute actions while maintaining high levels of performance and generalization capabilities.

Research activities should explore the training methodologies for these foundation models, emphasizing their ability to process multimodal data and derive actionable insights to inform robotic decision-making processes.

The proposals are also expected to include the validation of the trained models through applications. Proposals should detail methodologies for conducting rigorous testing procedures, incorporating both simulation-based evaluations and physical experiments. These tests aim to evaluate the performance and scalability of developed foundation models.

The research will be driven by impactful scenarios defined by major manufacturing industry players who should be well integrated in the consortium. They should be deeply involved in the proposed work in order to provide the use-case, the corresponding data and they will play an important role to accompany the validation process. They will define a number of representative real-world use-cases with gradually increased level of complexity to drive the technology development. They will provide existing relevant data and collect further data necessary to train and fine-tune the models, but also to validate the solutions. Given the sensitivity of sharing industrial data, manufacturers present in the consortium have to define upfront mechanisms to collectively provide and pool a sufficiently large dataset for training the models (this might involve a trusted third party as intermediary), ensuring sufficient quality and quantity of data needed to train the models. If necessary, they will have to put in place mechanisms to acquire data from sources outside the consortium.

Proposals should address both the safety of robotic operations, ensuring protection against physical risks, and cybersecurity measures to safeguard against digital threats and ensure system integrity.

The emphasis lies in creating and disseminating general-purpose models and tools rather than being limited to narrowly focused solutions. Projects should also build on or seek collaboration with existing and upcoming projects and develop synergies and ensure complementarities with other relevant European (e.g. projects funded under HORIZON-CL4-2024-HUMAN-03-01: Advancing Large AI Models: Integration of New Data Modalities and Expansion of Capabilities), national or regional initiatives, funding programmes and platforms.

Type B Scope:

The objective is to enhance productivity and provide a competitive advantage to EU industry in the transition towards more sustainable, zero-carbon production, addressing the uncertainties and tensions on supply chains and the lack of highly-skilled workers. A new generation of digital technologies will integrate generative Artificial Intelligence, robotics, and advanced human interfaces in industry-grade applications with a high degree of autonomy. This will enable the development, production, and operation of complex and advanced high-tech products at lower cost while improving sustainability and flexibility, ultimately becoming a powerful tool for accelerating innovation in both processes and products.

The manufacturing sector should strongly benefit from increased levels of automation made possible by breakthroughs provided by AI, in particular by the family of technologies know as generative AI, including (e.g.) AI foundation models, large language models, transformers, multimodal generative AI. The main objective of this Type B is the development of Generative AI solutions dedicated to the manufacturing sector and making use of manufacturing data available in production lines.

Proposals should address at least one of the following use-cases:

  1. Robustness and trustworthiness of digital technologies and data management at industry-grade quality, to raise the automation levels on production sites and across industry and supply chains;
  2. Enhanced product and process qualification/certification and compliance assessment through higher levels of automation, digitalisation and data management, taking into account related requirements;
  3. Automation of manufacturing processes to achieve higher reliability, efficiency and sustainability;
  4. Automated tools for fast and large-scale deployment and reconfiguration of production assets and for rapid innovation cycles.

Proposals should accomplish these objectives exploiting the most suitable approach(es) among the ones described below:

  • The integration of applications exhibiting advanced developments of generative AI model(s) specifically designed for manufacturing, providing measurable advantages in one of more of these key areas: manufacturing cost, increased productivity, quality, flexibility, resilience, sustainability, circularity, time to market and usability. Applications can target factory-floor operations and/or management of data, knowledge and documentation associated to products and production (for use-case 1 or 2);
  • Development and integration of digital production systems capable of significantly increasing productivity and managing high-mix production with close to zero time needed for re-purposing and capability to manage different mixes of materials and components (for use-case 3);
  • Development of deployment tools to automate the management of production lines, namely through automatic configuration, integration with legacy systems, placement of data translators and connectors, and deployment of machines and sensors on the shop floor (for use-case 4).

Proposals should indicate which approach they are targeting. Proposals may combine several approaches above, indicating which is the main approach, provided there is added value in such a combined approach; arbitrary combinations without integration are excluded.

The use of generative AI techniques is encouraged for all the approaches. The applicants will specifically describe how they will secure the acquisition of quality manufacturing data from real-world industrial use cases of industry partners or companies outside the consortium in the context of the data volume necessary to train and finetune the models used in the proposal.

Type A and Type B

For both Type A and Type B projects, proposal should allocate up to EUR 30 million towards the development of the foundation model. Each project is anticipated to focus on up to six use cases.

A minimum of EUR 10 million of the proposal budget must be allocated via FSTP for the fine-tuning phase. This phase aims to create Generative AI applications tailored to impactful industry-driven use cases.

  • FSTP may be foreseen for up to EUR 2 million per use case, either for a single company (including SME/Start-up), user industry providing their data and use-case, or to a small consortium complementing such user industry company with one or two additional partners, such as AI developer/integrator. Such FSTP initiatives will develop mini-projects, working in close collaboration with the consortium partners, that will dedicate sufficient resources to support such FSTP projects, in order to develop advanced applications and demonstrate with quantitative KPIs the power of Generative AI solutions. These mini-projects will include data preparation, fine-tuning, validation of the Generative AI solution in the selected impactful use-cases.

Where relevant, interoperability for data sharing should be addressed, focusing on open specifications and standards, enabling effective cross-domain data communities, and new data-driven markets.

If high computing resources are necessary, for both Type A and Type B proposals the primary source of computing resources for pretraining should be sought from external high-performance computing facilities such as EuroHPC or National centres. The proposal should describe convincingly the strategy to access these computing resources.

When possible, proposals should build on and reuse public results from relevant previous funded actions. Additionally, proposals should leverage the tools available for the AI and robotics community on the AI on demand platform. Communicable results should be shared with the European R&D community through the AI-on-demand platform, and if necessary, other relevant digital resource platforms to bolster the European AI, Data, and Robotics ecosystem by disseminating results and best practices.

This topic implements the co-programmed European Partnerships on AI, Data, and Robotic (ADRA) and Made in Europe and all proposals are expected to allocate tasks for cohesion activities with ADRA and the CSA HORIZON-CL4-2025-03-HUMAN-18: GenAI4EU central Hub.

Proposals should also build on or seek collaboration with existing projects and develop synergies with other relevant International, European, national or regional initiatives.

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Expected effects and impacts

Type A: Proposals are expected to enhance the accuracy and robustness of generative AI systems in robotics, ensuring that the solutions developed are trustworthy and reliable in their applications, hence in line with the AI Act requirements.

Type B: Proposed projects should aim to develop models that align with European values and principles and regulation, including the AI Act. Research should build on existing standards or contribute to standardisation, particularly addressing the needs and requirements of the industry.

Expected results

Proposals are expected to address one area of the expected outcomes, either Type A or Type B. The type should be clearly identified within the proposal.

Type A GenAI4EU: Generative AI for Robotics for industrial automation. Project results are expected to contribute to all the following expected outcomes:

  • Development of advanced foundation models for robotics, fostering increased autonomy and generalization capabilities, thus enabling robots to dynamically learn and comprehend their physical surroundings in real-time, ensuring adaptability and reliability across diverse and complex scenarios.
  • Validation of the model through fine-tuning and downstream application to address industrial automation use-cases

Type B Trustworthy and robust generative AI for improved manufacturing. Project results are expected to further advance foundation models and reliable industrial solutions and to contribute to some of the following expected outcomes, depending on the use-cases addressed in the proposals:

  • Increased productivity by high quality, flexible and resource-efficient industrial automation, both on the shop floor and in engineering/business processes;
  • Significantly improved facilitation of product and process certification and compliance assessment, as well as reliability, efficiency and sustainability of manufacturing processes, supporting easier high-mix production and manufacturing of products based on sustainable and advanced technologies; and
  • Significantly facilitated installation, commissioning and decommissioning of production facilities, through tools that enable faster industrialisation of factory automation well beyond the pilot phase, while reducing the need for manual on-site interventions.
  • Applicants will justify their selection by the expected business dimension of their use cases, while ensuring a critical mass of resources in the project to ensure significant outcomes in these.

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Eligibility Criteria

Regions / countries for funding

EU Member States, Overseas Countries and Territories (OCT)
Canada, Iceland (Ísland), Israel (ישראל / إِسْرَائِيل), New Zealand (Aotearoa), Norway (Norge), Switzerland (Schweiz/Suisse/Svizzera), United Kingdom

eligible entities

EU Body, Education and training institution, Non-Profit Organisation (NPO) / Non-Governmental Organisation (NGO), Other, Private institution, incl. private company (private for profit), Public Body (national, regional and local; incl. EGTCs), Research Institution incl. University, Small and medium-sized enterprise (SME)

Mandatory partnership

Yes

Project Partnership

To be eligible for funding, applicants must be established in one of the following countries:

  • the Member States of the European Union, including their outermost regions
  • the Overseas Countries and Territories (OCTs) linked to the Member States
  • countries associated to Horizon Europe - see list of particpating countries

Only legal entities forming a consortium are eligible to participate in actions provided that the consortium includes, as beneficiaries, three legal entities independent from each other and each established in a different country as follows:

  • at least one independent legal entity established in a Member State; and
  • at least two other independent legal entities, each established in different Member States or Associated Countries.

Any legal entity, regardless of its place of establishment, including legal entities from non-associated third countries or international organisations (including international European research organisations) is eligible to participate (whether it is eligible for funding or not), provided that the conditions laid down in the Horizon Europe Regulation have been met, along with any other conditions laid down in the specific call topic.

A ‘legal entity’ means any natural or legal person created and recognised as such under national law, EU law or international law, which has legal personality and which may, acting in its own name, exercise rights and be subject to obligations, or an entity without legal personality.

Specific cases:

  • Affiliated entities (i.e. entities with a legal or capital link to a beneficiary which participate in the action with similar rights and obligations to the beneficiaries, but which do not sign the grant agreement and therefore do not become beneficiaries themselves) are allowed, if they are eligible for participation and funding.
  • Associated partners (i.e. entities which participate in the action without signing the grant agreement, and without the right to charge costs or claim contributions) are allowed, subject to any conditions regarding associated partners set out in the specific call conditions.
  • Entities which do not have legal personality under their national law may exceptionally participate, provided that their representatives have the capacity to undertake legal obligations on their behalf, and offer guarantees to protect the EU’s financial interests equivalent to those offered by legal persons.
  • Legal entities created under EU law (EU bodies) including decentralised agencies may be part of the consortium, unless provided for otherwise in their basic act.
  • International European research organisations are eligible to receive funding. International organisations with headquarters in a Member State or Associated Country are eligible to receive funding for ‘Training and mobility’ actions or when provided for in the specific call/topic conditions. Other international organisations are not eligible to receive funding, unless provided for in the specific call/topic conditions, or if their participation is considered essential for implementing the action by the granting authority.
  • Joint Research Centre (JRC)— Where provided for in the specific call conditions, applicants may include in their proposals the possible contribution of the JRC but the JRC will not participate in the preparation and submission of the proposal. Applicants will indicate the contribution that the JRC could bring to the project based on the scope of the topic text. After the evaluation process, the JRC and the consortium selected for funding may come to an agreement on the specific terms of the participation of the JRC. If an agreement is found, the JRC may accede to the grant agreement as beneficiary requesting zero funding or participate as an associated partner, and would accede to the consortium as a member.
  • Associations and interest groupings — Entities composed of members (e.g. European research infrastructure consortia (ERICs)) may participate as ‘sole beneficiaries’ or ‘beneficiaries without legal personality’. However, if the action is in practice implemented by the individual members, those members should also participate (either as beneficiaries or as affiliated entities, otherwise their costs will NOT be eligible.
  • EU restrictive measures — Entities subject to EU restrictive measures under Article 29 of the Treaty on the European Union (TEU) and Article 215 of the Treaty on the Functioning of the EU (TFEU) as well as Article 75 TFEU, are not eligible to participate in any capacity, including as beneficiaries, affiliated entities, associated partners, third parties giving in-kind contributions, subcontractors or recipients of financial support to third parties (if any).
  • Legal entities established in Russia, Belarus, or in non-government controlled territories of Ukraine — Given the illegal invasion of Ukraine by Russia and the involvement of Belarus, there is currently no appropriate context allowing the implementation of the actions foreseen in this programme with legal entities established in Russia, Belarus, or in non-government controlled territories of Ukraine. Therefore, even where such entities are not subject to EU restrictive measures, such legal entities are not eligible to participate in any capacity. This includes participation as beneficiaries, affiliated entities, associated partners, third parties giving in-kind contributions, subcontractors or recipients of financial support to third parties (if any). Exceptions may be granted on a case-by-case basis for justified reasons.
    With specific regard to measures addressed to Russia, following the adoption of the Council Regulation (EU) 2024/1745 of 24 June 2024 (amending Council Regulation (EU) No 833/2014 of 31 July 2014) concerning restrictive measures in view of Russia’s actions destabilising the situation in Ukraine, legal entities established outside Russia but whose proprietary rights are directly or indirectly owned for more than 50% by a legal person, entity or body established in Russia are also not eligible to participate in any capacity.
  • Measures for the protection of the Union budget against breaches of the principles of the rule of law in Hungary — Following the Council Implementing Decision (EU) 2022/2506, as of 16 December 2022, no legal commitments can be entered into with Hungarian public interest trusts established under the Hungarian Act IX of 2021 or any entity they maintain. Affected entities may continue to apply to calls for proposals and can participate without receiving EU funding, as associated partners, if allowed by the call conditions. However, as long as the Council measures are not lifted, such entities are not eligible to participate in any funded role (beneficiaries, affiliated entities, subcontractors, recipients of financial support to third parties, etc.).In case of multi-beneficiary grant calls, applicants will be invited to remove or replace that entity in any funded role and/or to change its status into associated partner. Tasks and budget may be redistributed accordingly.

other eligibility criteria

In order to achieve the expected outcomes, and safeguard the Union’s strategic assets, interests, autonomy, and security, it is important to avoid a situation of technological dependency on a non-EU source, in a global context that requires the EU to take action to build on its strengths, and to carefully assess and address any strategic weaknesses, vulnerabilities and high-risk dependencies which put at risk the attainment of its ambitions. For this reason, participation is limited to legal entities established in Member States, Iceland and Norway and the following additional associated countries: Canada, Israel, the Republic of Korea, New Zealand, Switzerland, and the United Kingdom.

For the duly justified and exceptional reasons listed in the paragraph above, in order to guarantee the protection of the strategic interests of the Union and its Member States, entities established in an eligible country listed above, but which are directly or indirectly controlled by a non-eligible country or by a non-eligible country entity, may not participate in the action unless it can be demonstrated, by means of guarantees positively assessed by their eligible country of establishment, that their participation to the action would not negatively impact the Union’s strategic assets, interests, autonomy, or security. Entities assessed as high-risk suppliers of mobile network communication equipment within the meaning of ‘restrictions for the protection of European communication networks’ (or entities fully or partially owned or controlled by a high-risk supplier) cannot submit guarantees.

A minimum of EUR 10 million of the EU funding requested by the proposal must be allocated to financial support to third parties.

Additional information

Topics

Digitalisation, Digital Society, ICT

Relevance for EU Macro-Region

EUSDR - EU Strategy for the Danube Region, EUSBSR - EU Strategy for the Baltic Sea Region, EUSALP - EU Strategy for the Alpine Space, EUSAIR - EU Strategy for the Adriatic and Ionian Region

UN Sustainable Development Goals (UN-SDGs)

Additional Information

Applications must be submitted electronically via the Funders & Tenders Portal electronic submission system (accessible via the topic page in the Search Funding & Tenders section). Paper submissions are NOT possible.

Applications must be submitted using the forms provided inside the electronic submission system (not the templates available on the topic page, which are only for information). The structure and presentation must correspond to the instructions given in the forms.

Applications must be complete and contain all parts and mandatory annexes and supporting documents.

The application form will have two parts:

  • Part A (to be filled in directly online) contains administrative information about the applicant organisations (future coordinator and beneficiaries and affiliated entities), the summarised budget for the proposal and call-specific questions;
  • Part B (to be downloaded from the Portal submission system, completed and then assembled and re-uploaded as a PDF in the system) contains the technical description of the project.

Annexes and supporting documents will be directly available in the submission system and must be uploaded as PDF files (or other formats allowed by the system).

The limit for a full application (Part B) is 48 pages.

In order to include a business case and exploitation strategy, the page limit in Part B of the General Annexes is exceptionally extended by 3 pages.

Activities are expected to start at TRL 2 and achieve TRL 6 by the end of the project.

To ensure a balanced portfolio grants will be awarded to applications not only in order of ranking but at least also to one proposal that is the highest ranked within Type A and Type B, provided that the applications attain all thresholds.

Beneficiaries must provide financial support to third parties (FSTP). The support to third parties can only be provided in the form of grants. In derogation to article 208 EU Financial Regulation, the maximum amount to be granted to each third party can exceed EUR 60,000 and reach up to EUR 500 000. This derogation is justified by the high cost intensity of the substantial human resources, equipment or data acquisition required to successfully carry out the research and innovation activities planned in the FTSP actions. 

A given action supported by such FSTP scheme can be implemented by one third party or a by consortium of entities. The maximum amount to be granted to each action implemented by a third party or by a consortium is up to EUR 2 million.

Call documents

Horizon Europe Work Programme 2025 Cluster 4 - Digital, Industry and SpaceHorizon Europe Work Programme 2025 Cluster 4 - Digital, Industry and Space(kB)

Contact

National Contact Points for Horizon Europe
Website

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