JARVIS continues developing synergies with Sister Projects

16/09/2025

JARVIS continues to build synergies with sister projects! Last week, we participated in the launch of the FORTIS project’s webinar series and presented our vision for the future in human robot collaboration in industrial environments.

Representing the JARVIS project, our coordinator Zoi Arkouli delivered a presentation on the project’s vision, goals and solutions that will be validated across four large scale pilots coming from the nuclear and offshore energy sectors, as well as the automotive and aeronautics production.

During the webinar, it was discussed that, while there is intensive research in Human-Robot Interaction (HRI) across Europe, the industrial deployment of collaborative robotic processes remains limited. The JARVIS project addresses this challenge in two ways:

1) JARVIS consortium is co-developing a set of reusable tools for HRI with direct input and iterative feedback from the JARVIS end users, ensuring that once validated in the four pilots, these tools are both relevant and sustainable in for real production settings, and

2) by funding external pilots through Open Calls, allowing new application domains and technologies to be explored while extending the validation of the JARVIS tools to additional contexts.

In addition to technical advancements, the importance of investing in operator training and upskilling to help future-proof the workforce and make new technologies more accessible was underscored. The need for supporting all ages in adopting augmentation solutions for manufacturing was emphasized highlighting the value of XR-based tools and user centric design in facilitating faster learning and smoother adoption. While technology providers aim to deliver user-friendly tools, human operators still need guidance and support in forming clear expectations to feel confident working with them. In this context, enablers of natural HRI were outlined, focusing on easy programming, accommodating micro-adjustments in production, ensuring minimal disruptions and providing intuitive interfaces which were also identified as critical for real-world adoption.

Furthermore, innovative AI approaches for faster and more reliable robotic processes were discussed in conjunction with reducing dependence on costly datasets and data annotation, for instance by employing synthetic generation and self-trained AI models.

We look forward to continuing our engagement with FORTIS and ARISE, and to welcoming stakeholders, researchers, and industry players to join us in upcoming sessions.

Stay tuned for more insights from the JARVIS project and the broader ecosystem!