As marine exploration becomes increasingly important, marine robots have been extensively studied in recent years. Despite some well-designed robots have already achieved to various successful missions, most existing robots struggle to adapt to diverse demands or tasks due to their fixed structure and complexity of the marine environment. To address these challenges, we present a novel reconfigurable marine robot named Sea-U-Whale. This system can dynamically adjust its actuator configuration in the marine environment, providing superior environmental adaptability, maneuverability, and ver-satile mobility. Considering the demands of unmanned ocean exploration, an active reconfiguration mechanism and three distinct vehicle modes are designed for optimal actuation in various marine scenarios. The multi-modal mobility of our system and its robust performance have been validated through extensive field tests and water tank experiments, demonstrating its potential in handling a wide range of mission profiles.

Despite the evident superiority of event cameras in practical vision applications (e.g., action recognition), owing to their distinctive sensing mechanism, existing event-based action recognition methods rely heavily on large-scale training data. However, the expensive cost of camera deployment and the requirement of data privacy protection make it challenging to collect substantial data in real-world scenarios. To address this limitation, we explore a novel yet practical task, Few-Shot Event-Based Action Recognition (FSEAR), which aims at leveraging a minimal number of intractable event action data for model training and accurately classifying unlabeled data into a specific category. Accordingly, we design a new framework for FSEAR, including a Noise-Aware Event Encoder (NAE) and a Distilled Prototypical Distance Fusion (DPDF). The former efficiently filters noise within the spatiotemporal domain while retaining vital information related to action timing. The latter conducts multi-scale measurements across geometric, directional, and distributional dimensions. These two modules benefit mutually and thus effectively exploit the potential characteristics of event data. Extensive experiments on four distinct event action recognition datasets have demonstrated the significant advantages of our model over other few-shot learning methods. Our code and models will be publicly released.

Autonomous Marine Vehicles (AMVs) have been widely used in many critical tasks such as surveillance, patrolling, marine environment monitoring, and hydrographic surveying. However, most typical AMVs cannot meet the diverse demands of different marine tasks. In this article, we design a new type of remote-controlled hydrofoil marine vehicle, named Sea-U-Foil, which is suitable for different marine scenarios. Sea-U-Foil features three distinct locomotion modes, displacement mode, foilborne mode, and submarine mode, which enable the platform flexible mobility, high-speed and high-load capacities, and superior concealment. Specifically, the submarine mode makes Sea-U-Foil unique among previous studies. In addition, the performance of Sea-U-Foil in foilborne mode outperforms those of most current unmanned surface vehicles (USVs) in terms of speed and payload. To the best of our knowledge, we are the first to introduce a new type of AMV that can work in displacement mode, foilborne mode, and submarine mode. We elaborate on the design principles and methodologies of Sea-U-Foil first, then validate the effectiveness of its tri-modal locomotion through extensive experiments.

Aerial-aquatic vehicles are capable to move in the two most dominant fluids, making them more promising for a wide range of applications. We propose a prototype with special designs for propulsion and thruster configuration to cope with the vast differences in the fluid properties of water and air. For propulsion, the operating range is switched for the different mediums by the dual-speed propulsion unit, providing sufficient thrust and also ensuring output efficiency. For thruster configuration, thrust vectoring is realized by the rotation of the propulsion unit around the mount arm, thus enhancing the underwater maneuverability. This paper presents a quadrotor prototype of this concept and the design details and realization in practice.