Socially-Acceptable and Trustworthy Human-Robot Teaming for Agile Industries

Project Information

SOPRANO

Grant agreement ID: 101120990

DOI

10.3030/101120990

EC signature date 28 June 2023

Start date 1 October 2023

End date 31 January 2027

Funded under

• Digital, Industry and Space

Total cost

€ 8 793 462,75

EU contribution

€ 8 039 523,77

Coordinated by

INSTITUT FÜR ANGEWANDTE SYSTEMTECHNIK BREMEN GMBH
Germany

Periodic Reporting for period 1 - SOPRANO (Socially-Acceptable and Trustworthy Human-Robot Teaming for Agile Industries)

Reporting period: 2023-10-01 to 2024-09-30

Summary of the context and overall objectives of the project

Maintaining Europe’s competitiveness demands highly efficient and flexible industrial processes. Novel intelligent robotic capabilities deployed side-by-side with humans and able to adapt to dynamic situations can address these demands. 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, and are not easily and economically adaptable to process changes.

SOPRANO aims to enable a next generation of multi-human multi-robot (MH-MR) systems to support more flexible, resilient and reconfigurable agile processes built on the following innovative technology pillars:
• Advanced collaborative human-centric robotic capabilities by improving context awareness in highly uncertain indoor and outdoor environments, via ubiquitous, visual and non-visual sensing, exploiting the notion of time and models from industrial and cognitive psychology.
• Trustworthy and Dependable AI-based MH-MR teaming that ensures safe and robust operation in industrial environments encompassing safety monitoring, diagnostics, AI planning and reasoning, model-driven simulation-based approaches to assess quality aspects, human-digital twin integrating the human resource in the system design, and dynamic operation monitoring.
• Modular, reconfigurable and flexible engineering tools to support adaptability and ease of use in various operating environments through the exploitation of robot programming, easy configuration of AI-supported tools to dynamically adapt to product changes, model-based development of reconfigurable control systems supporting adaptive control policies at run time, and open standards-based cloud and federated cloud-edge service orchestration with automatic organisation of tasks and resources.

The SOPRANO technology pillars will enable truly agile production processes across multiple European industries able to autonomously adapt to changes in product requirements and components, human collaborative tasks and real-time changes in resources and supplies.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

In the early months of the project, the partners have focused on the definition of the industrial Use Cases and prioritisation of the associated requirements for the new tools, technologies and methodologies targeted for MH-MR systems development and deployment. The Use Case requirements have then been used to establish the detailed and prioritised technical requirements that are driving the technology development and innovation tasks within each of the research and development workpackages of the project.

The evaluation plans were established for eventually determining the extent to which the project technologies and innovations address the Use Case requirements and achieve the target industrial benefits for MH-MR development and deployments, along with the data management plans for handling of the data sets being utilised by each industrial Use Case partner and those that will be used for laboratory technology development and validation.

The project has completed the initial SOPRANO systems architecture represented using multiple viewpoints: Logical View, Development View, Process View, Physical View; including an analysis of a typical industrial deployment of the SOPRANO components. All of the tool designs have been completed and development has substantially progressed for each component towards the planned completion of early prototypes at the end of December 2024 for first industrial evaluations and to support the Open Call that will be launched in the second quarter of 2025.

The partners have been active in dissemination actions including multiple technical papers presented and published targeting the robotics research and development community, as well as industrial communities that rely on robotics technologies, all of which have created awareness of the MH-MR systems development and deployment technologies being developed in the project.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

SOPRANO will deliver the following key technologies supporting the design, testing, deployment and monitoring of MH-MR applications:
• Pervasive scene perception with real-time environment monitoring of multiple sensors
• Detection/localization of challenging objects exploiting visual and tactile cues during robot actions
• Human digital twins supporting virtual simulation for complex scenarios integrating human resources
• Time-aware MH-MR orchestration for collaboration at global team and local human-robot level
• Human-robot interaction model encompassing socio-cognitive prerequisites for effective interactions
• Suite of advanced development and deployment tools for MH-MR applications
• Suite of ML quality assessment tools for testing ML models for MH-MR applications
• Simulation-based testing tools for MH-MR applications able to interface with different robotic simulators

Expected Impact
• Scientific: Advanced robotics technologies that enable safe, highly flexible, reconfigurable and modular production solutions through use of multi-robot systems supporting AI driven human collaboration.
• Economic: Increased production efficiency in multiple key European industrial sectors including 30% cost reduction in reconfiguring production processes, 50% time savings in adapting to changes in production, 20% increase in human robot collaborations, and many other targeted improvements.
• Societal: Paves the way for less fossil-based production by adopting less carbon-intensive alternatives while investing in new human skills for a climate-neutral continent, a resource-efficient society, a circular economy, and a thriving labour market.

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