Autonomous Underwater Vehicles (AUVs) are a highly promising technology for ocean exploration and diverse offshore operations, yet their practical deployment is constrained by energy efficiency and endurance. To address this, we propose Current-Harnessing Stage-Gated MPC, which exploits ocean currents via a per-stage scalar which indicates the "helpfulness" of ocean currents. This scalar is computed along the prediction horizon to gate lightweight cost terms only where the ocean currents truly aids the control goal. The proposed cost terms, that are merged in the objective function, are (i) a Monotone Cost Shaping (MCS) term, a help-gated, non-worsening modification that relaxes along-track position error and provides a bounded translational energy rebate, guaranteeing the shaped objective is never larger than a set baseline, and (ii) a speed-to-fly (STF) cost component that increases the price of thrust and softly matches ground velocity to the ocean current, enabling near zero water-relative "gliding". All terms are C1 and integrate as a plug-and-play in MPC designs. Extensive simulations with the BlueROV2 model under realistic ocean current fields show that the proposed approach achieves substantially lower energy consumption than conventional predictive control while maintaining comparable arrival times and constraint satisfaction.

翻译：自主水下航行器（AUV）是海洋勘探与多样化离岸作业中极具前景的技术，但其实际部署受限于能源效率与续航能力。为此，我们提出洋流利用型阶段门控模型预测控制方法，该方法通过逐阶段标量来利用洋流，该标量指示洋流对控制目标的“助益程度”。该标量沿预测时域计算，仅在洋流真正有助于控制目标时启用轻量化成本项。所提出的成本项（整合于目标函数中）包括：（一）单调成本塑形项，这是一种助益门控的非劣化修正，可放宽沿航迹位置误差并提供有界的平移能量回馈，保证塑形后的目标函数值永不高于设定基线；（二）飞航速度成本项，通过提高推力代价并柔和地使对地速度匹配洋流速度，实现近乎零水相对速度的“滑翔”。所有成本项均为C1连续函数，可作为即插即用模块集成于MPC设计中。基于BlueROV2模型在真实洋流场中的大量仿真表明，所提方法在保持相近抵达时间与约束满足度的同时，能实现比传统预测控制显著更低的能耗。