Autonomous object recovery in the hadal zone is challenging due to extreme hydrostatic pressure, limited visibility and currents, and the need for precise manipulation at full ocean depth. Field experimentation in such environments is costly, high-risk, and constrained by limited vehicle availability, making early validation of autonomous behaviors difficult. This paper presents a simulation-based study of a complete autonomous subsea object recovery mission using a Hadal Small Vehicle (HSV) equipped with a three-degree-of-freedom robotic arm and a suction-actuated end effector. The Stonefish simulator is used to model realistic vehicle dynamics, hydrodynamic disturbances, sensing, and interaction with a target object under hadal-like conditions. The control framework combines a world-frame PID controller for vehicle navigation and stabilization with an inverse-kinematics-based manipulator controller augmented by acceleration feed-forward, enabling coordinated vehicle - manipulator operation. In simulation, the HSV autonomously descends from the sea surface to 6,000 m, performs structured seafloor coverage, detects a target object, and executes a suction-based recovery. The results demonstrate that high-fidelity simulation provides an effective and low-risk means of evaluating autonomous deep-sea intervention behaviors prior to field deployment.

翻译：在深渊带进行自主目标回收极具挑战性，原因在于极高的静水压力、有限的能见度与海流，以及需要在全海深条件下进行精确操控。在此类环境中进行现场实验成本高昂、风险巨大，且受限于可用航行器数量稀少，使得自主行为的早期验证困难重重。本文提出了一项基于仿真的完整自主海底目标回收任务研究，该任务使用配备三自由度机械臂与吸力驱动末端执行器的深渊小型航行器（HSV）。研究利用Stonefish仿真器，在类深渊条件下对航行器动力学、流体动力扰动、传感以及与目标物体的交互进行了真实建模。控制框架结合了用于航行器导航与稳定的世界坐标系PID控制器，以及通过加速度前馈增强的基于逆运动学的机械臂控制器，从而实现了航行器与机械臂的协调操作。在仿真中，HSV自主从海面下潜至6000米，执行结构化的海底覆盖搜索，检测到目标物体，并执行了基于吸力的回收操作。结果表明，高保真仿真为现场部署前评估自主深海干预行为提供了一种有效且低风险的手段。