MoWe: Motion Observation for Wind Estimation of Sailing Robots

Toward sustained mobility in complex marine environment, there is an urgent need for sailing robots to operate robustly when wind measurements are unavailable (e.g., wind sensors are damaged). This study proposes an effective motion observation-based wind estimation (MoWe) scheme, which enables the robotic sailboat to consistently acquire wind information from its own maneuvers. MoWe incorporates motion analysis (MA) and data-driven (DD) methods. In the MA method, dead zone constraints of the robotic sailboat are identified as crucial references in deriving wind direction. For the DD approach, the sailing robot as shown in Figure 1 is employed to collect a data set, which serves as the basis for regressing an estimator. We conducted extensive validation tests in both simulation and experiments. Results indicate favorable performance for both methods in simulated scenarios. Notably, the DD method exhibited higher estimation accuracy in all experiments. The mean absolute error (MAE) of estimated wind direction was 4.25°, with the range of confidence interval spanning from 25.13° to 33.56°, demonstrating the robustness of the DD method. Furthermore, the estimation of wind direction has been successfully applied in straight-line sailing tests, and the wind magnitude has been estimated. The MAE of wind magnitude estimation was 1.13m/s.