V3I6P108

Adaptive Navigation Strategies for Autonomous Underwater Vehicles in Time-Varying Marine Environments 

Nguyen Trung Dung*¹

Abstract

Autonomous Underwater Vehicles (AUVs) are increasingly employed in oceanographic exploration, environmental monitoring, offshore inspection, and military operations. However, reliable navigation in time-varying marine environments remains a significant challenge due to ocean currents, dynamic obstacles, sensor uncertainties, and communication constraints. This study presents an adaptive navigation framework designed to enhance the autonomy, robustness, and operational efficiency of AUVs operating in complex underwater environments.

The proposed approach integrates environmental perception, adaptive path planning, and real-time trajectory optimization to continuously adjust the vehicle’s navigation strategy according to changing environmental conditions. A dynamic decision-making module combines onboard sensor information with predictive environmental models to generate collision-free and energy-efficient trajectories while maintaining mission objectives. The navigation strategy is designed to compensate for external disturbances, reduce positioning errors, and improve vehicle stability under uncertain ocean conditions.

Simulation experiments were conducted in various dynamic marine scenarios involving time-varying currents, moving obstacles, and uncertain environmental disturbances. The performance of the proposed navigation strategy was evaluated in terms of navigation accuracy, path efficiency, energy consumption, obstacle avoidance capability, and mission completion rate. Comparative analyses demonstrate that the proposed adaptive strategy achieves higher navigation reliability and robustness than conventional navigation methods, particularly in highly dynamic environments.

The proposed framework provides a flexible foundation for intelligent underwater navigation and can be extended to cooperative multi-AUV operations, reinforcement learning-based autonomous decision making, and long-duration underwater missions in complex marine environments.

Keywords:

Autonomous Underwater Vehicle (AUV), adaptive navigation, path planning, dynamic marine environment, obstacle avoidance, trajectory optimization, autonomous decision making, underwater robotics.