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IKTPLUSS-IKT og digital innovasjon

Resilient Robotic Autonomy for Underwater Operations in Fish Farms

Alternative title: Robust autonom robotikk for undervannsoperasjoner i oppdrettsanlegg

Awarded: NOK 12.0 mill.

This project envisions to reshape the underwater operations in dynamic, complex and perceptually-degraded environments by developing new knowledge and novel technology to enable resilient autonomy for Unmanned Underwater Vehicles (UUVs). ResiFarm challenges the resilience in one of the most demanding industrial environments such as fish farms. Motivated by the core hypothesis that there exists a broadly defined and unified science for resilient autonomy of UUVs operating in complex, high risk, perceptually-degraded and dynamic environments, the envisioned research will be holistically organized around three cross-cutting objectives that are addressing the current knowledge gaps on: a) resilient multi-modal perception for UUVs operating in dynamic perceptually-degraded environments, b) methods for novel motion planning concepts that enable safe, fish- and structure-aware operations and c) validation of the fully integrated system in field studies. By utilising the competence of the interdisciplinary team (SINTEF, NTNU), industry partners' (Eelume, Skarv Technologies) expertise in the underwater robotic and automation domain, and involving international experts in topics relevant to the project (MIT, LSTS, TUM, ETH), our team aims to provide the foundation for the new generation of permanent resident UUVs that co-exist with fish without causing negative impact and autonomously navigate and interact with flexible structures. The result of this project will be the new science and systems to facilitate long-term autonomous underwater operation of UUVs and promote sustainable expansion in fish farms and other maritime industries such as fisheries, subsea oil and gas and offshore wind farms. Overall, ResiFarm will impact research communities, businesses, the public sector and society at large through collaboration between these and with the outmost dedication to developments and demonstrations of novel methods within artificial intelligence, automation and robotics.

This project envisions to reshape the underwater operations in dynamic, complex and perceptually-degraded environments by developing new knowledge and novel technology to enable resilient autonomy for Unmanned Underwater Vehicles (UUVs). ResiFarm challenges the resilience in one of the most demanding industrial environments such as fish farms. Motivated by the core hypothesis that there exists a broadly defined and unified science for resilient autonomy of UUVs operating in complex, high risk, perceptually-degraded and dynamic environments, the envisioned research will be holistically organized around three cross-cutting objectives that are addressing the current knowledge gaps on: a) resilient multi-modal perception for UUVs operating in dynamic perceptually-degraded environments, b) methods for novel motion planning concepts that enable safe, fish- and structure-aware operations and c) validation of the fully integrated system in field studies. By utilising the competence of the interdisciplinary team (SINTEF, NTNU), industry partners' (Eelume, Skrav Technologies) expertise in the underwater robotic and automation domain, and involving international experts in topics relevant to the project (MIT, LSTS, TUM, ETH), our team aims to provide the foundation for the new generation of permanent resident UUVs that co-exist with fish without causing negative impact and autonomously navigate and interact with flexible structures. The result of this project will be the new science and systems to facilitate long-term autonomous underwater operation of UUVs and promote sustainable expansion in fish farms and other maritime industries such as fisheries, subsea oil and gas and offshore wind farms. Overall, ResiFarm will impact research communities, businesses, the public sector and society at large through collaboration between these and with the outmost dedication to developments and demonstrations of novel methods within artificial intelligence, automation and robotics.

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IKTPLUSS-IKT og digital innovasjon