Sensor Fusion – Based Localization for ASV with Linear Regression Optimization

ASV (Autonomous Surface Vehicle) is one of popular innovations in the maritime field that is widely used for various missions on the water surface. The ASV itself has the ability to operate automatically without human intervention. Therefore, ASV requires an accurate and reliable localization system. This research focuses on developing an ASV localization system using waterflow sensors optimized through linear regression and integrated with orientation data from an IMU sensor through sensor fusion to obtain global coordinate position estimation. The experiments conducted showed a significant improvement in accuracy after optimization, with the Root Mean Square Error (RMSE) of the waterflow sensor data decreasing from 161.65 meters to 0.28 meters. Moreover, the yaw data reading by IMU achieved accuracy with RMSE 1.54 degrees. The localization system in the final test achieved RMSE values of 0.07 meters for the X-axis, 0.14 meters for the Y-axis, and 1.9 degrees for yaw during the ASV global positioning experiment. In addition, a GUI (Graphical User Interface) was developed for visualization with average communication latency of 113.6 milliseconds. This localization system is a promising solution in stable water condition.