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Collision-free motion planning for operations in dynamically changing environments such as fish farms
Unmanned underwater vehicles (UUVs) have become indispensable tools for inspection, maintenance, and repair (IMR) operations in the underwater domain. Path planning and collision avoidance are fundamental concepts for enabling autonomy for mobile robots. This remains a challenge, particularly for underwater vehicles operating in complex and dynamically changing environments such as fish farms [1].
The operations in fish farms feature deformable structures and they are conducted in the presence of up to 200.000 fish. In such environments, there is a need both for optimality and quickly being able to alter the plan based on changes in the surroundings [2]. This thesis will investigate and develop for collision-free motion planning methods for UUVs operating in fish farms. In addition to the simulated case studies, there will be potential for field validation of the developed method/methods in collaboration with SINTEF ACE RoboticLab [3].
References:
[1] Kelasidi, E. and Svendsen, E. (2022). Robotics for Sea-Based Fish Farming, 1–20. Springer International Publishing, Cham. doi:10.1007/978-3-030-89123-7 202-1.
[2] H.B. Amundsen, M. Føre, E. Kelasidi, S.J. Ohrem and B. Haugaløkken, “Three-dimensional collision avoidance and path planning for unmanned underwater vehicles using elastic bands”, Field Robotics, 2024
[3] SINTEF ACE RoboticLab. https://www.sintef.no/en/expertise/ocean/sintef-ace-roboticlab/
The operations in fish farms feature deformable structures and they are conducted in the presence of up to 200.000 fish. In such environments, there is a need both for optimality and quickly being able to alter the plan based on changes in the surroundings [2]. This thesis will investigate and develop for collision-free motion planning methods for UUVs operating in fish farms. In addition to the simulated case studies, there will be potential for field validation of the developed method/methods in collaboration with SINTEF ACE RoboticLab [3].
References: [1] Kelasidi, E. and Svendsen, E. (2022). Robotics for Sea-Based Fish Farming, 1–20. Springer International Publishing, Cham. doi:10.1007/978-3-030-89123-7 202-1. [2] H.B. Amundsen, M. Føre, E. Kelasidi, S.J. Ohrem and B. Haugaløkken, “Three-dimensional collision avoidance and path planning for unmanned underwater vehicles using elastic bands”, Field Robotics, 2024 [3] SINTEF ACE RoboticLab. https://www.sintef.no/en/expertise/ocean/sintef-ace-roboticlab/
Literature review of motion planning methods for underwater operations in dynamic environments
Develop safe and cognizant motion planning concepts for collision-free navigation considering the dynamic structure-aware features of fish farms for UUVs operating in fish farms
Develop safe and cognizant motion planning concepts for collision-free navigation considering fish-aware features of fish farms for UUVs operating in fish farms
Implemented and combined with the developed motion planning methods in simulation environment (e.g., FhSim-comprehensive simulation environment featuring net cages, fish behaviour, ROVs, DAVE, HoloOcean etc)
Potential for Field validation in collaboration with SINTEF ACE RoboticLab
Literature review of motion planning methods for underwater operations in dynamic environments Develop safe and cognizant motion planning concepts for collision-free navigation considering the dynamic structure-aware features of fish farms for UUVs operating in fish farms Develop safe and cognizant motion planning concepts for collision-free navigation considering fish-aware features of fish farms for UUVs operating in fish farms Implemented and combined with the developed motion planning methods in simulation environment (e.g., FhSim-comprehensive simulation environment featuring net cages, fish behaviour, ROVs, DAVE, HoloOcean etc) Potential for Field validation in collaboration with SINTEF ACE RoboticLab
Highly motivated student
Experience with C/C++ and/or Python programming is desired
Highly motivated student Experience with C/C++ and/or Python programming is desired