Hub Data Science & AI

Manufacturing, construction, and agriculture are major driving forces for the European economy and prosperity. Maintaining its competitiveness in these sectors demands highly efficient and flexible processes, and this can be achieved through digitization. Novel intelligent robotic capabilities that can be deployed side-by-side with humans and can operate and adapt to dynamic environments can accelerate this process. However, existing robotic systems cannot fit well into such settings as they are not versatile and flexible enough to automate certain tasks, cannot collaborate safely with humans in open and dynamic environments, nor are they easily and economically adaptable to process changes.

The SOPRANO project coalesces multidisciplinary research and innovation in human-robot collaboration and intelligent multi-agent systems, aspiring to design the next generation of manufacturing floors, construction sites, and agri-food production, where humans and intelligent machines will seamlessly work together. It proposes to scale collaboration from the single human-agent dyad to a peer-based synergy between multiple interconnected robotic systems featuring different physical and cognitive properties, supporting various tasks in collaboration with human workers, robotics and other agents.

SOPRANO will validate the technological offering in three novel and open-access use cases addressing both large-scale industries and small to medium enterprises, adding value to EU key sectors and instrumenting community building surrounding the open-source technologies in the EU industrial ecosystem. During the project, we will also enable external SMEs and start-ups to benefit from the project technologies via an open call, which will enable the building of demonstrators using SOPRANO technologies that will open new market opportunities for their products and services.

DEADLINE : 14 mai 2025

HUB : Advanced Engineering & Computing

To strengthen the competitiveness of the EU industry, there is an increasing need for flexible production, exploiting the capabilities of both the machinery and human workforce. The growing market of robots has reacted, adapting to the changing situation by providing collaborative robotic solutions with a variety of characteristics in terms of payload, type and mobility. A number of technological solutions for perception and safety allow their coexistence with humans. While several research activities have been conducted over the past 5 years on this topic, wider industrial adoption is lagging due to the following restrictions:
• Limited cognition and intelligence
• Low performance of collaborative operations
• Collaboration fluidity is rather low as the operators have to adapt to the particularities of the robots.
• Complexity in robot programming which requires the involvement of skilled engineers, does not provide flexibility in the execution phase, and does not benefit from the tacit knowledge of experienced operators.

Thus, despite the fact the mechatronics are quite advanced, a perfect matching of mechanics and control is required to create robots that advance from repetitive and precision-oriented tasks to becoming intelligent and helpful co-workers. Proper human robot interaction is the most important ground to be covered.

Thus, JARVIS aims to develop a reusable set of tools that enable AI driven multimodal means of interaction: a) involving interfaces for physical and remote information exchange, robot control and programming, b) providing social skills to a variety of robots to achieve seamless user-centric interaction that extends human ability for complex tasks and c) demonstrating scalability of application and ability to achieve economies at scale.

DEADLINE : 5 mai 2025

HUB : Cyber & Security

A common trait of many important markets is the increasing attention of consumers to the aesthetic quality of the products. Even products like mid-segment cars are required to be defect-free in all the areas falling under the direct sight of the customer. These expectations translate into high-quality standards in the production process, which are currently met by requiring an important physical effort to the workers in unsafe environments. The MAGICIAN project will take on the challenge producing a modular automation solution in which robots are used to detect and rework production defects before the last production phases commence and the aesthetics of the product is finalised. The project will produce two robotic solutions, one for defect analysis (the SR) and one for the defects’ rework (the CR). The SR and the CR can be used separately, with the humans remaining in charge of some of the activities, or in combination, with the CR operating on the defects identified by the SR. The SR can also be used in connection with the welding robotic station in order to adapt the process parameters. The robots will use Artificial Intelligence modules to detect and discriminate the defects from multi-modal data (the SR) or to decide the best policy to use for defect rework (the CR). In both cases, the decision logic of the modules will be trained using machine learning algorithms. The training data set will be acquired with the help of workers, who will operate on semi-worked products within a controlled environment. The SR and the CR will rely on the software services of a common robotic platform. The solution will be developed adopting a human-centered approach, which will allow us to evaluate the impact of the innovation on the production processes and remove the most important asperities along this path. The effectiveness of the solution will be tested on a use-case, and its generality proven by recruiting additional contributors and use-cases through a FSTP scheme.

DEADLINE : 2 mai 2025

HUB : Advanced Engineering & Computing