Summary
Autonomous systems able to comprehensively assess and model risks would be a scientific breakthrough leading to highly intelligent system behaviors, safe interactions in unstructured environments, and public trust. Currently, risk perception is an important part of human cognition not adequately implemented in the situation awareness, control and decision-making of autonomous systems. Therefore, this project addresses fundamental research challenges related to risk-based autonomy and safe and efficient shared control with human supervisors. The aim is to develop powerful risk modelling and built-in risk control solutions, closely connected to risk-based decision support for human supervisors in-the-loop. The outcomes of the project will allow for new, safe, and advanced types of transport, mapping and monitoring of oceans and land, and inspections of structures difficult to access. Although there are a few preliminary concepts coupling risk models with control algorithms and artificial intelligence (AI), a fundamental framework providing risk-based control and decision support – for both the autonomous system and human supervisors – does not exist. In BREACH, I will establish such a framework constituted by quantitative risk models merged with data-driven approaches, simulation and model-based approaches, integrating hardware, software, human, and environmental risk elements. The complexity of the framework will gradually evolve in two parallel tracks along with demonstrations for mission planning and execution for autonomous marine “organizations”. The focus on marine systems is due to the demanding challenges in that domain, and my knowledge and experience as a researcher in the Centre of Excellence on Autonomous Marine Operations and Systems (NTNU AMOS). For several years, I have contributed to fundamental research related to risk management of autonomous marine systems, which has convinced me that this project will be a major leap forward with great impact.
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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101142277 |
Start date: | 01-01-2025 |
End date: | 31-12-2029 |
Total budget - Public funding: | 2 499 773,00 Euro - 2 499 773,00 Euro |
Cordis data
Original description
Autonomous systems able to comprehensively assess and model risks would be a scientific breakthrough leading to highly intelligent system behaviors, safe interactions in unstructured environments, and public trust. Currently, risk perception is an important part of human cognition not adequately implemented in the situation awareness, control and decision-making of autonomous systems. Therefore, this project addresses fundamental research challenges related to risk-based autonomy and safe and efficient shared control with human supervisors. The aim is to develop powerful risk modelling and built-in risk control solutions, closely connected to risk-based decision support for human supervisors in-the-loop. The outcomes of the project will allow for new, safe, and advanced types of transport, mapping and monitoring of oceans and land, and inspections of structures difficult to access. Although there are a few preliminary concepts coupling risk models with control algorithms and artificial intelligence (AI), a fundamental framework providing risk-based control and decision support – for both the autonomous system and human supervisors – does not exist. In BREACH, I will establish such a framework constituted by quantitative risk models merged with data-driven approaches, simulation and model-based approaches, integrating hardware, software, human, and environmental risk elements. The complexity of the framework will gradually evolve in two parallel tracks along with demonstrations for mission planning and execution for autonomous marine “organizations”. The focus on marine systems is due to the demanding challenges in that domain, and my knowledge and experience as a researcher in the Centre of Excellence on Autonomous Marine Operations and Systems (NTNU AMOS). For several years, I have contributed to fundamental research related to risk management of autonomous marine systems, which has convinced me that this project will be a major leap forward with great impact.Status
SIGNEDCall topic
ERC-2023-ADGUpdate Date
21-11-2024
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