Multimodal Underwater Research Articles

Swift: Transition Characterization and Motion Analysis of a Multimodal Underwater Vehicle

Swift: Transition Characterization and Motion Analysis of a Multimodal Underwater Vehicle

A multimodal magnetoelastic artificial skin for underwater haptic sensing.

Future exploitation of marine resources in a sustainable and eco-friendly way requires autonomous underwater robotics with human-like perception. However, the development of such intelligent robots is now impeded by the lack of adequate underwater haptic sensing technology. Inspired by the populational coding strategy of the human tactile system, we harness the giant magnetoelasticity in soft polymer systems as an innovative platform technology to construct a multimodal underwater robotic skin for marine object recognition with intrinsic waterproofness and a simple configuration. The bioinspired magnetoelastic artificial skin enables multiplexed tactile modality in each single taxel and obtains an impressive classification rate of 95% in identifying seven types of marine creatures and marine litter. By introducing another degree of freedom in underwater haptic sensing, this work represents a milestone toward sustainable marine resource exploitation.

Development of Bioinspired Multimodal Underwater Robot “HERO-BLUE” for Walking, Swimming, and Crawling

Development of Bioinspired Multimodal Underwater Robot “HERO-BLUE” for Walking, Swimming, and Crawling

Energy optimal depth control for multimodal underwater vehicles with a high accuracy buoyancy actuated system

Efficient depth control and energy consumption are significant factors that must be considered for underwater vehicles operating in deep-sea environments and for long-term deployments. This paper proposes a high-accuracy buoyancy-actuated system (HA-BAs) based on the energy optimization principle for multimodal underwater vehicles (MUVs), which can precisely regulate displacement to realize the efficient depth control. The proposed mathematical model in the vertical plane and the energy consumption model of the MUV with the HA-BAs were established, revealing all the regularities of motion control to improve the depth control precision and navigation efficiency. The depth control characteristics of the MUV with HA-BAs were analyzed by considering the operating in a practical environment, which showed that the HA-BAs facilitated a more precise depth control for the MUV. In addition, energy consumption per diving meter was used as an indicator of sailing efficiency. Energy efficiency and depth control analysis were carried out by motion simulation and sea trails, and the results indicate that the MUV employed HA-BAs is beneficial for energy saving and depth control, particularly in the Argo mode.

Dynamic modeling and switching analysis of all-attitude multimode underwater vehicle for multidimensional data acquisition

This study proposes a unique multimodal underwater observation platform, called all-attitude multimode underwater vehicle (AMUV). AMUV integrates the movement capabilities of Argo buoy, Glider motion modes, and autonomous underwater vehicles (AUVs), enabling comprehensive underwater navigation. To explore the operational rules of individual modes and the changes in actuator and attitude during mode transitions, firstly, a dynamics model of AMUV is established, conforming the operating principles of the Argo buoy, Glider, and AUVs. Secondly, through open-loop simulations of different modes, the feasibility of the dynamic model is verified. Thirdly, through simulation experiments involving three typical mode switching processes, the mechanism of AMUV multi-mode switching is demonstrated. Finally, to examine the ability of the AMUV for multidimensional data acquisition, a simulation task focused on gathering multidimensional data of marine elements is designed. The simulation results indicate that the proposed AMUV has considerable potential for application in monitoring activities requiring the acquisition of multidimensional oceanographic data.

MLRS-RL: An Energy-Efficient Multilevel Routing Strategy Based on Reinforcement Learning in Multimodal UWSNs

In recent years, Multimodal Underwater Wireless Sensor Networks (M-UWSNs) have attracted widespread concern in academia. Due to the complex underwater communication environment and the increasing marine applications, it is a crucial issue for M-UWSNs to design an energy efficient routing strategy that can satisfy multiple transmission latency requirements of different marine applications. Reinforcement learning (RL) approaches with distributed dynamic optimization ability provide a prospective way to solve the aforementioned problem. Therefore, we propose an improved RL framework and then design an energy efficient multi-level routing strategy (MLRS-RL) based on this framework for multiple transmission latency requirements. In MLRS-RL, a method of model knowledge collection based on the time backoff principle is proposed to preliminarily learn the network environment information before network operates. The convergence speed of the RL framework can be accelerated by utilizing the model knowledge. Then, underwater nodes use the improved RL model to calculate the transmission rewards that data packets with different transmission latency requirements are sent to different candidate relay nodes. Finally, a cooperative transmission strategy using multiple relay nodes is designed to further improve the reliability of data transmission. We verify the effectiveness of the MLRS-RL strategy in terms of packet delivery ratio, transmission latency, energy efficiency, network lifetime, and delivery quantity.

Anti-Swelling Zwitterionic Hydrogels as Multi-Modal Underwater Sensors and All-in-One Supercapacitors

Anti-Swelling Zwitterionic Hydrogels as Multi-Modal Underwater Sensors and All-in-One Supercapacitors

An External Ocean Thermal Energy Power Generation Modular Device for Powering Smart Float

Smart Float is a new multi-modal underwater vehicle, a tool for ocean observation and detection, whose performance is limited by its underwater voyage distance and endurance like most underwater vehicles. The utilization of marine energy provides an ideal way to overcome these limitations. In this paper, an external ocean thermal energy power generation module is developed for Smart Float, which can be used for multiple times of energy storage and power generation and is expected to be further applied to small and medium-sized underwater vehicles. The integration of the proposed device will cause changes in the counterweight characteristic, hydrodynamic characteristic, and heat transfer characteristic of the vehicle, which are deeply analyzed in this study, and adaptive modification solutions are proposed according to the analysis results. Finally, a prototype of Smart Float integrating the proposed device was deployed in the South China Sea to perform a sea trial, to test its performance in thermal energy utilization. According to the results, the device generates 1.341 Wh in a profile diving to 700 m, with the maximum single-profile generation of 1.487 Wh, the average electrical energy of 1.368 Wh, and the hydraulic-to-electric efficiency of about 60% in the power generation stage, which verifies its excellent performance in thermal energy utilization. This study realizes the integration of thermal energy power generation modules into an underwater vehicle for the first time, exploring a new way to improve the endurance and self-sustainability of commercial underwater vehicles.

Opportunistic Routing for Opto-Acoustic Internet of Underwater Things

Internet of Underwater Things (IoUT) is a technological revolution that could mark a new era for scientific, industrial, and military underwater applications. To mitigate the hostile underwater channel characteristics, this article considers a multimodal underwater network that hybridizes acoustic and optical wireless communications to achieve an ubiquitous control and high-speed low-latency networking performance, respectively. Since underwater optical wireless communications (UOWCs) suffer from limited range, it requires effective multihop routing solutions. In this regard, we propose a sector-based opportunistic routing (SectOR) protocol. Unlike the traditional unicast routing (TUR) techniques, which send packets to a unique relay, opportunistic routing (OR) targets a set of candidate relays by leveraging the broadcast nature of the UOWC channel. OR improves the packet delivery ratio as the likelihood of having at least one successful packet reception is much higher than that in TUR. Contingent upon the performance characterization of a single-hop link, we obtain a variety of local and global metrics to evaluate the fitness of a candidate set (CS) and develop candidate prioritization techniques for various OR metrics. Since rate <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\leftrightarrow $ </tex-math></inline-formula> error and range <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\leftrightarrow $ </tex-math></inline-formula> beamwidth tradeoffs yield different CS diversities, we develop a candidate filtering and searching algorithm to find the optimal sector shaped coverage region by scanning the feasible search space. Moreover, a hybrid acoustic/optic coordination mechanism is considered to avoid duplicate transmission of the relays. Numerical results show that the SectOR protocol can perform even better than optimal unicast routing protocols in well-connected underwater networks.

Dynamic modeling and motion control of a novel conceptual multimodal underwater vehicle for autonomous sampling

This paper presents a conceptual design of a novel multimodal underwater vehicle that integrates the merits of the Argo profiling float, the buoyancy-driven underwater glider and the propeller/rudder-driven underwater vehicle, which serves as a long-endurance and highly maneuverable platform for multiple-water-column ocean sampling with high spatiotemporal resolution. Key design principles of this multimodal underwater vehicle are firstly formulated to enable mode switching. The mathematical model of this proposed vehicle is derived based on unit quaternions for the three modes of locomotion, namely, Argo mode, zigzag gliding mode and propeller/rudder-driven mode (PR mode). Heading deviation arises during transition between Argo mode and zigzag gliding mode is fully revealed. To tackle this key challenge, a multi-level motion controller is developed for this hybrid vehicle, which not only guarantees rapid mode switching, but also allows the vehicle to be capable of traveling between adjacent columns in zigzag gliding mode, vertical sampling in Argo mode as well as heading correction and position compensation in PR mode. The feasibility of the mode transition, the property of the heading deviation and the performance of the devised control scheme are validated and analyzed via a series of numerical simulations and experiments.

Optimal Transmission Scheduling in Small Multimodal Underwater Networks

We describe a scheduling protocol for multimodal networks of relatively limited size, whose nodes encompass various underwater communication technologies. For such a case, we show that significant improvement in the network operations is possible when the transmission schedule is set to jointly utilize all communication technologies. Our solution is based on per-technology time-division multiple access frames, whose time slots are determined optimally to maximize the overall channel utilization while preserving flow limitations and maintaining fairness in resource allocation. Our numerical simulations and experimental results for multimodal networks with several acoustic technologies show that, while maintaining a fair resource allocation, our scheduling solution provides both high throughput and low packet delivery delay.

Fair and Throughput-Optimal Routing in Multimodal Underwater Networks

While acoustic communications are still considered the most prominent technology to communicate under water, other technologies are being developed based, e.g., on optical and radio-frequency electromagnetic waves. Each technology has its own advantages and drawbacks: for example, acoustic signals achieve long communication ranges at order-of-kbit/s rates, whereas optical signals offer order-of-Mbit/s transmission rates, but only over short ranges. Such diversity can be leveraged by multimodal systems, which integrate different technologies and provide the intelligence required to decide which one should be used at any given time. In this paper, we address a fundamental part of this intelligence by proposing optimal multimodal routing (OMR), a novel routing protocol for underwater networks of multimodal nodes. OMR makes distributed decisions about the flow in each link and over each technology, at any given time, in order to advance a packet toward its destination; in doing so, it prevents bottlenecks and allocates resources fairly to different nodes. We analyze the performance of OMR via simulations and in a field experiment. The results show that OMR successfully leverages all technologies to deliver data, even in the presence of imperfect topology information. To permit the reproduction of our results, we share our simulation code.

Multimodal Underwater Adhesion Using Self-assembled Dopa-bearing ABA Triblock Copolymer Networks.

Self-assembled mechanically robust Dopa-bearing triblock copolymer networks improve underwater adhesion through both energy dissipation and interfacial bonding. Polymer networks that incorporate energy dissipating motifs could improve the performance of high-performance wet adhesives rather than only by interfacial bonds.

Multimodal underwater adsorption of oxide nanoparticles on catechol-based polymer nanosheets.

Multimodal underwater adsorption behaviour of catechol units was demonstrated by examining the adsorption of different oxide nanoparticles on nanoscale-integrated polymer nanosheets. Catechol-based polymer nanosheets were fabricated using the Langmuir-Blodgett (LB) technique with random copolymers (p(DDA/DMA)s) of N-dodecylacrylamide (DDA) and dopamine methacrylamide (DMA). The p(DDA/DMA) nanosheets were immersed into water dispersions of SiO2, Al2O3, and WO3 nanoparticles (NPs) respectively. The results show that the adsorption properties can be altered by varying the NP type: SiO2 NP adsorption was observed only below pH = 6, at which the o-quinone form in p(DDA/DMA) nanosheets transforms into the catechol form or vice versa. However, their transition point for Al2O3 NP adsorption was found at approximately pH 10, at which the surface potential of Al2O3 NPs changes the charge polarity, indicating that the electrostatic interaction is predominant. For WO3 NPs, adsorption was observed when citric acid, which modifies the surface of WO3 NPs by complex formation, was used as a pH-controlling agent, but no adsorption was found for hydrochloric acid used as a pH controlling agent. FT-IR measurements proved that miniscule amounts of water molecules were trapped in p(DDA/DMA) nanosheets and that they acquired hydrogen bonding network formations, which might assist nanoparticle adsorption underwater and make the catechol units adjustable. The results indicate that the nanoscale spatial arrangements of catechol units in films are crucially important for the application of multimodal adsorption of oxide nanoparticles on catechol-based polymer materials.