# Towards a Digital Twin for Open-Frame Underwater Vehicles Using Evolutionary Algorithms
## 1 Introduction  
Most of the tasks performed by autonomous underwater vehicles (AUVs) have focused on long-range exploration, mostly large torpedo-type AUVs designed for visually exploring and mapping large areas that require very long ranges [1, 2]. Inspection and maintenance tasks for parts of the installation that are above water are similar to those performed in onshore installations and are reasonably standardized. Underwater inspections, however, are in a different state, as there are still no procedures or systems in place to carry out these operations in a systematic and cost-effective way. The applications of AUVs in these tasks, such as undersea structure inspection, are relatively new; although, some developments have been made in the oil and gas sector, especially following oil or gas lines [3] and some basic ideas proposed for windfarms [4].  
To address these tasks, an approach based on the coordination of swarms of small and medium-sized underwater vehicles could be useful. This approach involves deploying a group of AUVs with autonomous navigation and behavior capabilities, equipped with the appropriate sensor set and sensing strategies, to carry out the analysis of the state of offshore structures. These tasks involve the AUVs not operating in open waters, but in more confined spaces, and have hardly been addressed except for some work on cave exploration [5, 6]. Each AUV in the team needs to accurately determine its position with respect to the structure and the rest of the team.  
A digital twin of the AUV that allows integrating the measurements made in real time with the simulations of the dynamic behavior of the assembly is proposed in this work. This makes it possible to determine the current situation of the vehicle while simulating and evaluating the future outcome of the decisions to be made by the system. Although parts of the developments in other sectors are applicable to AUVs, the complexity of the environment in which it is located, the high nonlinearity of the environmental responses, and the high degree of interactions make this a very incipient area in the field of AUVs [7], especially when operating closely or in contact with large structures.  
Understanding system behavior before real-world deployment is crucial for modern robotics. Digital twins (DTs) are especially valuable in marine robotics [8] where they support risk assessment, strategy optimization, and emergency planning [9] without exposing the physical system to danger. However, building high-fidelity virtual models and ensuring rapid data updates remain key challenges.  
DT technology is expanding into cyber physical operation systems, allowing real-time interaction between physical robots and virtual environments. This integration is enhanced by virtual reality visualization and advanced physics engines, which simulate dynamic interactions--such as track-ground contact--with high accuracy. These innovations are validated through experimental comparisons and are paving the way for more stable, efficient, and intuitive underwater operations [8; 10].  
While DTs are widely applied in manufacturing and other sectors, their use in underwater environments is still maturing due to the complexity of marine modeling [11]. Nevertheless, ongoing research and technological integration are rapidly advancing the capabilities and impact of digital twins in marine robotics [12]. All these factors make the digital twin of AUVs an open problem today that requires not only a base platform but also specific models that allow representing the physical phenomena that take place during the activity of AUVs [7; 13].