A Turning Radius Prediction Scheme for Sailing Robots under Complex Marine Environment

This paper presents a strategy for predicting the turning radius of a sailing robot with consideration of aerodynamic and hydrodynamic interferences from the marine environment. The turning radius is initially obtained based on three consecutive designated points during the turning process, which is regarded as the baseline method. Subsequently, on the basis of our constructed turning datasets, a model is trained using Gaussian process regression (GPR) to achieve radius prediction. The feasibility and effectiveness of the proposed scheme have been validated in both simulation and experi- ments (conducted with OceanVoy as shown in Fig.1). Under experimental circumstances, the Mean Absolute Error (MAE) of the turning radius produced by the trained prediction model is 0.58m. Furthermore, it has been observed that during long- term sailing covering a distance of 1200km, apart from wind speed and robot velocity, the tidal range also has a significant impact on the navigation of sailing robots.