RoboSAPIENS
Financiado
Robotic Safe Adaptation In unprecedented Situations
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 ada...
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 recoveryinto a degraded functionality. Instead, it must be a true adaptation, meaning that the robot will change its behavior while maintainingor even increasing its expected performance, and stays at least as safe and robust as before.RoboSAPIENS will focus on autonomous robotic software adaptations and will lay the foundations for ensuring that such softwareadaptations are carried out in an intrinsically safe, trustworthy and efficient manner, thereby reconciling open-ended self-adaptationwith 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 over-all 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) andDeep 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 industrialdisassembly robot, a warehouse robotic swarm, a prolonged hull of an autonomous vessel, and human-robotic interaction.
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Duración del proyecto: 35 meses
Fecha Inicio: 2024-01-01
Fecha Fin: 2026-12-31
Fecha Fin: 2026-12-31
Línea de financiación: concedida
El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-01-01
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
Presupuesto
El presupuesto total del proyecto asciende a
7M€
Líder del proyecto
AARHUS UNIVERSITET
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5