Modified Adaptive Line-of-Sight for Path Tracking and Obstacle Avoidance

This research presents a modified Adaptive Line-ofSight (ALOS) guidance method with a dynamically tuned projection parameter for Autonomous Underwater Vehicle (AUV). The proposed method was examined for tracking tasks in a straight-line path with underwater disturbances. The projection parameter is adaptively computed based on cross-track error and vertical-track error, as well as their derivatives. The simulation results indicate that the proposed method has a lower root mean square error (RMSE) than fixed-parameter techniques. Furthermore, the obstacle avoidance task is considered a more realistic scenario to assess the strategy. In this case, the Whale Optimization Algorithm (WOA) generates an alternative waypoint, while the modified ALOS guides the AUV along the new path. The proposed method provides precise path tracking and efficiently avoids obstacles, exhibiting excellent robustness and reliable performance in uncertain underwater conditions.