Hierarchical Thermocline-Aware Navigation for Underwater Gliders via Multi-Objective Path Planning and Reinforcement Learning

Navigation planning and execution for underwater gliders operating in thermocline-affected environments is challenging due to the coupled influence of energy constraints, spatially distributed environmental disturbances, and limited control authority. Spatially varying thermocline structures act as structured environmental disturbances that degrade motion efficiency and tracking accuracy, and therefore must be explicitly considered in both path planning and control design. This paper proposes a hierarchical control-oriented decision framework for underwater glider navigation in thermocline regions. At the planning layer, a thermocline-aware multi-objective optimization problem is formulated to regulate the trade-off between navigation efficiency and cumulative environmental disturbance, characterized by total path length and cumulative thermocline exposure, respectively. A multi-objective artificial bee colony (MOABC) algorithm is employed to generate a set of Pareto-optimal reference trajectories that explicitly reveal this trade-off. At the execution layer, pitch angle regulation is formulated as a stochastic tracking control problem under environmental uncertainty. A Markov Decision Process (MDP) is constructed to model the coupled effects of pitch control on energy consumption and trajectory deviation, and a deep deterministic policy gradient (DDPG) algorithm is adopted to synthesize a feedback control policy for adaptive pitch regulation during path execution. Simulation results demonstrate that the proposed framework effectively reduces cumulative thermocline exposure and overall energy consumption while maintaining improved trajectory consistency compared with representative benchmark methods. These results indicate that integrating multi-objective planning with learning-based control provides an effective control-oriented solution for constrained underwater glider navigation in thermally stratified environments.