Human-Machine Interfaces for Subsea Telerobotics: From Soda-straw to Natural Language Interactions

This review explores the evolution of human-machine interfaces (HMIs) for subsea telerobotics, tracing back the transition from traditional first-person "soda-straw" consoles (narrow field-of-view camera feed) to advanced interfaces powered by gesture recognition, virtual reality, and natural language models. First, we discuss various forms of subsea telerobotics applications, current state-of-the-art (SOTA) interface systems, and the challenges they face in robust underwater sensing, real-time estimation, and low-latency communication. Through this analysis, we highlight how advanced HMIs facilitate intuitive interactions between human operators and robots to overcome these challenges. A detailed review then categorizes and evaluates the cutting-edge HMI systems based on their offered features from both human perspectives (e.g., enhancing operator control and situational awareness) and machine perspectives (e.g., improving safety, mission accuracy, and task efficiency). Moreover, we examine the literature on bidirectional interaction and intelligent collaboration in terms of sensory feedback and intuitive control mechanisms for both physical and virtual interfaces. The paper concludes by identifying critical challenges, open research questions, and future directions, emphasizing the need for multidisciplinary collaboration in subsea telerobotics.

Word2Wave: Language Driven Mission Programming for Efficient Subsea Deployments of Marine Robots

This paper explores the design and development of a language-based interface for dynamic mission programming of autonomous underwater vehicles (AUVs). The proposed 'Word2Wave' (W2W) framework enables interactive programming and parameter configuration of AUVs for remote subsea missions. The W2W framework includes: (i) a set of novel language rules and command structures for efficient language-to-mission mapping; (ii) a GPT-based prompt engineering module for training data generation; (iii) a small language model (SLM)-based sequence-to-sequence learning pipeline for mission command generation from human speech or text; and (iv) a novel user interface for 2D mission map visualization and human-machine interfacing. The proposed learning pipeline adapts an SLM named T5-Small that can learn language-to-mission mapping from processed language data effectively, providing robust and efficient performance. In addition to a benchmark evaluation with state-of-the-art, we conduct a user interaction study to demonstrate the effectiveness of W2W over commercial AUV programming interfaces. Across participants, W2W-based programming required less than 10% time for mission programming compared to traditional interfaces; it is deemed to be a simpler and more natural paradigm for subsea mission programming with a usability score of 76.25. W2W opens up promising future research opportunities on hands-free AUV mission programming for efficient subsea deployments.

Ego-to-Exo: Interfacing Third Person Visuals from Egocentric Views in Real-time for Improved ROV Teleoperation

Underwater ROVs (Remotely Operated Vehicles) are unmanned submersible vehicles designed for exploring and operating in the depths of the ocean. Despite using high-end cameras, typical teleoperation engines based on first-person (egocentric) views limit a surface operator's ability to maneuver and navigate the ROV in complex deep-water missions. In this paper, we present an interactive teleoperation interface that (i) offers on-demand "third"-person (exocentric) visuals from past egocentric views, and (ii) facilitates enhanced peripheral information with augmented ROV pose in real-time. We achieve this by integrating a 3D geometry-based Ego-to-Exo view synthesis algorithm into a monocular SLAM system for accurate trajectory estimation. The proposed closed-form solution only uses past egocentric views from the ROV and a SLAM backbone for pose estimation, which makes it portable to existing ROV platforms. Unlike data-driven solutions, it is invariant to applications and waterbody-specific scenes. We validate the geometric accuracy of the proposed framework through extensive experiments of 2-DOF indoor navigation and 6-DOF underwater cave exploration in challenging low-light conditions. We demonstrate the benefits of dynamic Ego-to-Exo view generation and real-time pose rendering for remote ROV teleoperation by following navigation guides such as cavelines inside underwater caves. This new way of interactive ROV teleoperation opens up promising opportunities for future research in underwater telerobotics.