Automation and autonomous unmanned underwater vehicles (UUVs) are furthermore key elements in meeting the desire for increased precision in finfish farming that will enable aquaculture to advance operational efficiency, safety and thus sustainability. While current models and control strategies for UUVs allow navigation among rigid structures in static environments, they are not sufficient for UUV operations in a dynamic fish farm environment where the UUV needs to react to the presence of animals and deformable structures influenced by external forces such as waves and currents.
In the young researcher talents CHANGE project, fundamental knowledge on modelling of UUVs interacting with complex environments will be developed together with advanced control strategies. The developed models will include fish behaviour and deformation of flexible structures, combined with influences from the surrounding environment (e.g. currents, waves), thus providing data for feedback control loops. Integrating these with the novel control strategies, will enable real-time control of the UUV during autonomous navigation in aquaculture fish cages without colliding with fish or flexible structures despite variable currents or waves. The functionality of the resulting new control paradigm will be tested in laboratory experiments that mimic the dynamic environments of aquaculture sites. Final field tests at active salmon farms will be employed to validate the developed models and strategies during demanding operations. By enabling UUVs to adapt their actions to the dynamically changing environment, CHANGE will promote the sustainable expansion of Norwegian salmon farming while simultaneously offering opportunities also for application outside the aquaculture context.
The primary objective of the CHANGE project is to develop new control systems for UUVs that enable autonomous operations in highly complex and dynamically changing environments containing live fish and flexible structures.
Secondary research objectives are:
- Develop realistic models of fish behaviour, dynamic structures, and the environmental conditions suitable for the navigation of UUVs that balance computational complexity vs. precision.
- Develop computationally affordable models of underwater vehicles that incorporate hydrodynamic effects caused by the dynamic cage environment.
- Develop intelligent control strategies for online operations that enable verifiable collision-free navigation in dynamically changing environments while compensating for unmodelled effects and minimising the impact on fish behaviour.
- Validation of the new control strategies in laboratory and field studies and comparison to current control strategies for UUVs.