Projects
RoboSAPIENS: Robotic Safe Adaptation In unprecedented Situations

RoboSAPIENS: Robotic Safe Adaptation In unprecedented Situations

Duration
01.01.2024-31.12.2026

The robots of tomorrow will be endowed with the ability to adapt to drastic and unpredicted changes in their environment, including humans. Such adaptations can, however, not be boundless: the robot must stay trustworthy, i.e., the adaptations should not be just a recovery into degraded functionality. Instead, it must be a true adaptation, meaning that the robot will change its behaviour while maintaining or even increasing its expected performance and staying at least as safe and robust as before.
Robotic Safe Adaptation In Unprecedented Situations (RoboSAPIENS) will focus on autonomous robotic software adaptations and will lay the foundations for ensuring that such software adaptations are carried out in an intrinsically safe, trustworthy, and efficient manner, thereby reconciling open-ended self-adaptation with safety by design. RoboSAPIENS will also transform these foundations into 'first-time right' design tools and robotic platforms and will validate and demonstrate them up to TRL4.

To achieve this overall goal, RoboSAPIENS will extend the state of the art in four main objectives.

  1. It will enable robotic open-ended self-adaptation in response to unprecedented system structural and environmental changes.
  2. It will advance safety engineering techniques to assure robotic safety not only before, during and after adaptation.
  3. It will advance deep learning techniques to actively reduce uncertainty in robotic self-adaptation.
  4. It will assure trustworthiness of systems that use both deep-learning and computational architectures for robotic self-adaptation.

To realise these objectives, RoboSAPIENS will extend techniques such as MAPE-K (Monitor, Analyze, Plan, Execute, Knowledge) and Deep Learning to set up generic adaptation procedures and also use an SSH dimension. RoboSAPIENS will demonstrate this trustworthy robotic self-adaptation on four industry-scale use cases centered around an industrial disassembly robot, a warehouse robotic swarm, a prolonged hull of an autonomous vessel, and human-robotic interaction.

Funding

This project is funded by the Horizon Europe programme under Call HORIZON-CL4-2023-DIGITAL-EMERGING-01-01— Novel paradigms and approaches, towards AI-driven autonomous robots (external link to the call).

Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or CINEA. Neither the European Union nor the Granting authority can be held responsible for them.

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