Towards reliable subsea object recovery: a simulation study of an auv with a suction-actuated end effector

2026-01-03

arXiv.org

AI Summary

This study addresses the challenges of autonomous object recovery in extreme deep-sea environments—such as hadal trenches—where high pressure, low visibility, ocean current disturbances, and the need for high-precision manipulation complicate operations, while field trials remain costly and risky. Leveraging the high-fidelity simulation platform Stonefish, the authors develop a Hadal Small Vehicle (HSV) equipped with a three-degree-of-freedom manipulator and a suction-based end-effector. For the first time in simulation, they integrate full-system dynamics, hydrodynamic disturbances, perception models, and suction-target interaction physics to enable coordinated vehicle-manipulator control. Using a world-frame PID navigation controller and an inverse kinematics manipulator controller with acceleration feedforward, the system successfully executes a complete mission sequence at 6000 m depth, including descent, seabed coverage search, target identification, and autonomous suction-based retrieval, thereby demonstrating the efficacy and low-risk validation potential of high-fidelity simulation for deep-sea autonomous intervention tasks.

Technology Category

• Intelligent Robots: Manipulation
• Search and Optimization: Sampling/Simulation-based Search
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

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.

Problem

• autonomous object recovery
• hadal zone
• subsea manipulation
• extreme hydrostatic pressure
• deep-sea intervention

Innovation

• suction-actuated end effector
• autonomous subsea recovery
• hadal zone simulation
• vehicle-manipulator coordination
• high-fidelity underwater simulation