A unified shared control architecture for underwater vehicle–manipulator systems using task priority

Abstract

It is challenging for underwater vehicle–manipulator systems (UVMSs) to operate autonomously in unstructured underwater environments. Relying solely on teleoperation for both underwater vehicle (UV) and underwater manipulator (UM) imposes a considerable cognitive and physical load on the operator. In this paper, we propose a unified shared control (USC) architecture for the UVMS, integrating divisible shared control (DSC) and interactive shared control (ISC) to alleviate the operator’s workload. By applying task priority based on DSC, we divide the whole-body task into constraints, operation, and posture optimization subtasks. The robot autonomously avoids self-collisions and adjusts its posture according to the user’s visual preferences. ISC incorporates haptic feedback to enhance human–robot collaboration, seamlessly integrating it into the operation task via a whole-body controller for the UVMS. Simulations and pool experiments are conducted to verify the feasibility of the method. Compared to manual control (MC), the proposed method reduces completion time by 17.50%, operator input length by 25.00%, and cognitive load by 35.53% in the simulations, with corresponding reductions of 22.73%, 40.00%, and 29.91% in the pool experiments. Subjective measurements demonstrate the reduction in operator workload with the proposed method.

1. Introduction

The proliferation of ocean exploration by humans has led to an increasing demand for underwater missions, including persistent underwater observation (Lin and Yang, 2020) and underwater manipulation (Petillot et al., 2019). Underwater tasks encompass a wide range of missions, such as scientific expeditions, marine rescue, and offshore industries (Ridao et al., 2015). Skilled divers are capable of undertaking some underwater interventions but face limitations in deep or prolonged underwater missions. Consequently, underwater vehicle–manipulator systems (UVMSs) have become essential for underwater operations (Sahoo et al., 2019).

In the early stages of UVMS development, operators remotely control the vehicle and manipulator independently. However, full teleoperation requires operators to maintain sustained focus and patience for precise movements (Shim et al., 2010). This process places significant physical and cognitive load on operators, rendering it difficult to maintain during prolonged periods (Capocci et al., 2018). In addressing this challenge, numerous UVMSs have been developed. Some are fully autonomous, such as GIRONA 500 (Ribas et al., 2015) and Aquanaut (Manley et al., 2018). Others, like Ocean One (Khatib et al., 2016) and DexROV (Di Lillo et al., 2021) operate in semi-autonomous mode. Notably, task priority control (Simetti et al., 2018) is widely used in UVMSs, and offers a hierarchical motion resolution framework for redundant robotic systems through the prioritization of control objectives.

For instance, using task priority control, GIRONA 500 completed underwater tasks such as object recovery, valve turning (Maurelli et al., 2016), and pipeline inspection tasks (Cieślak and Ridao, 2018). This approach enables a UVMS to adapt to various operational scenarios featuring diverse control objectives and activation functions. Although underwater manipulation autonomy has been improved significantly (Zhang et al., 2017), fully automated control is still inadequate for complex and delicate operations in open and unstructured underwater environments. Underwater operations continue to require human intervention (Sivčev et al., 2018). Human–machine hybrid augmented intelligence (HMAI) has the potential to significantly enhance the capabilities of complex systems (Wang et al., 2022). Human–robot shared control (SC) technology has garnered significant attention over the past decade. SC leverages human high-level cognition and decision-making while integrating robotic capabilities for low-level task execution (Yang et al., 2022b). SC methods are typically classified into divisible shared control (DSC) and interactive shared control (ISC).