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Review

Review of Hybrid Aerial Underwater Vehicle: Potential Applications in the Field of Underwater Marine Optics

MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University, Shenzhen 518060, China
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Author to whom correspondence should be addressed.
Drones 2025, 9(10), 667; https://doi.org/10.3390/drones9100667
Submission received: 16 July 2025 / Revised: 15 September 2025 / Accepted: 16 September 2025 / Published: 23 September 2025
(This article belongs to the Special Issue Drones in Hydrological Research and Management)

Abstract

Hybrid Aerial Underwater Vehicle (HAUV) is a new type of unmanned system that can operate both in air and water, and complete underwater and air operations tasks by carrying corresponding sensors. Owing to this dual-medium operational capability, HAUVs hold significant promise for coordinated air–sea surveillance and monitoring efforts. Optical methods enable high-resolution sampling across both spatial and temporal scales, offering enhanced contextual information for the interpretation of discrete observational data. In order to evaluate the feasibility of ocean optical profiling systems based on HAUVs, this paper reviews the design features of current HAUV models and summarizes advanced techniques that support their cross-medium mobility. Subsequently, we summarized the types of commercial optical instruments commonly used for underwater observation and compared the field deployment methods. By analyzing the underwater motion performance of HAUVs and the requirements for optical observation platforms, we believe that multi-rotor HAUVs can provide new observation methods for future underwater optical acquisition due to their smooth entry and exit characteristics and the ability to maintain a controlled orientation during underwater operation. Finally, the paper explores prospective applications and outlines key obstacles to be overcome in the advancement of amphibious platforms for ocean optical profiling.

1. Introduction

Currently, unmanned vehicles, including Unmanned Aerial Vehicles (UAVs), Unmanned Surface Vehicles (USVs), and Unmanned Underwater Vehicles (UUVs), are essential tools for human exploration, understanding, and exploitation of the ocean [1]. These conventional vehicles can carry various exploration equipment or operational tools for ocean monitoring in different spatial dimensions. In addition, new and more complex application scenarios have emerged with the development of marine science and the increasing need for rapid ocean monitoring [2,3]. These missions include the monitoring of marine emergencies such as red tides and oil spills from the air, the detection of these events under water, and the sampling of the water in the area [4]. To meet the needs of air–sea cross-domain missions, researchers have made progress in the design and operation of a distributed heterogeneous autonomous sensor network that combines unmanned vehicles in coastal environments [5]. However, the harmonious integration of different devices into a single system is not an easy or cost-effective task, and the organization and control of such a system is therefore a major challenge.
An emerging concept, Hybrid Aerial Underwater Vehicles (HAUVs), has expanded significantly in recent years to provide a more convenient and efficient solution for air–sea cross-domain missions [4,6]. The capability of HAUVs to operate across both aerial and aquatic domains simplifies the execution of multi-environment monitoring tasks. A single platform can acquire data from various mediums, reducing the need for separate systems. Current HAUV design strategies typically involve adapting fixed-wing and rotary-wing UAVs to perform underwater functions. Nevertheless, HAUVs, as an emerging technology, encounter numerous technical and operational challenges in practical deployment and remain insufficiently developed to fully support the aforementioned applications [7,8]. Therefore, identifying and developing suitable design strategies for amphibious vehicles that can meet the demands of specific operational scenarios has become a key priority in current research.
The development of satellite remote sensing technology for ocean color in the 1980s led to widespread interest in the optical properties of the ocean [9,10,11]. The change and distribution of the color of seawater is determined by substances in the upper surface water, such as phytoplankton, non-pigmented particulate matter, and soluble organic matter. In order to determine the concentration of these substances from water color data, it is necessary to have an understanding of their optical properties and their effect on the light transmission process. This need has led to the development of a large number of new high-performance optical instruments. These have been designed to provide previously unmeasurable data on the optical properties of the ocean. These optical data can provide some basic information about the ocean, such as the concentration and type of particulate matter, the particle size distribution, the primary productivity, the turbidity of the water, etc. In addition, data on optical properties are correlated with data on physical, biological, chemical, and geological properties [12,13,14,15,16]. The current research focus of ocean optics is the use of optical property measurement technology as an important tool for the study of physical oceanography, chemical oceanography, biological oceanography, and geological oceanography, which inevitably requires different observation platforms to meet the needs. Compared to traditional marine optical measurement methods such as remote sensing, buoys, and ship surveys, more and more underwater mobile intelligent platforms can help to obtain fast and stereo optical data sets (e.g., Bio-Argo, AUV, ROV, and UG) [17,18,19,20,21,22,23,24,25]. It is necessary to further integrate new observing platforms and to extend the methods they use to observe.
The main purpose of this paper is to review the progress of existing cross-domain HAUVs, then analyze the requirements of ocean optical observation methods for platforms, evaluate the feasibility of amphibious profiling optical systems, and finally look at future application scenarios. The paper is structured as follows: a review of the current status of HAUVs is given in Section 2. Ocean optical instruments and deployment methods are presented in Section 3. The feasibility of a hybrid airborne underwater optical observation system is discussed in Section 4. Finally, the potential applications and future work for amphibious optical observation systems are described in Section 5.

2. Hybrid Underwater Vehicle Progress

The Hybrid Underwater Aerial Vehicle is an unmanned aerial vehicle that can move simultaneously in water and air, rely on its own energy to cross water and air media repeatedly, and perform underwater and air operations by carrying appropriate sensors [4,26,27]. This aircraft combines the advantages of stealth, the flexibility of underwater robots, and the speed of air vehicles. It has attracted great interest in various countries. The entire development process of HAUVs can be roughly divided into the conceptual design phase, the theoretical development phase, and the research phase of prototype testing. As early as the 1930s, before World War II, the former Soviet Union proposed the manned “flying submarine” plan [6]. It developed a design scheme that combined aircraft and submarines, and established a specialized technical research team. Their design scheme can search and determine the target from the air, then land and infiltrate the enemy ship’s route to set up ambushes and achieve the effect of surprise operations. However, due to technical limitations at the time, the plan did not enter the engineering research and development stage and was finally abandoned in 1938. Following the concept of the flying submarine, four notable prototypes have exemplified the manned concept: the LPL (Letayushchaya Podvodnaya Lodka), RFS-1(Reid Flying Submarine 1), and Convair models, along with DARPA’s (DARPA, the Defense Advanced Research Projects Agency) submersible aircraft. These four conceptual prototypes advanced related technological developments and demonstrated the theoretical viability of the design. However, none were ultimately implemented to function across both aerial and underwater environments. Since the beginning of the 21st century, with the rapid development of technologies such as autonomous control, structural compatibility design, computer simulation, new lightweight materials, and advanced power systems, especially the gradual maturity of unmanned aerial vehicles, underwater autonomous robots and biomimetic theory, research institutions have been continuously demonstrating and designing amphibious unmanned aerial vehicles in the sea and the air, and some institutions have conducted principle prototypes and preliminary tests. As an emerging field, HAUV technology remains in the early stages of exploration, with numerous innovative design concepts under active development and testing. These vehicles can be categorized in multiple ways depending on the classification criteria applied. In this paper, existing forms of HAUVs are grouped into two dominant designs on the basis of water entry strategies. One is the splash entry HAUV, which is characterized by the unique way of plunge-dive water entry. The other form is the Vertical Take-Off and Landing (VTOL) HAUV, which has a stable low-speed flight and a smooth water entry capability.

2.1. The Splash Entry/Exit Way HAUVs

HAUVs with a splash entry and exit path can usually be divided into two categories (as shown in Figure 1 and Figure 2): (1) Bio-inspired HAUVs designs are inspired by natural organisms capable of locomotion in both aerial and aquatic environments, such as cliff puffins, boobies, flying fish, frilled squids, dragonflies, and similar species. (2) Fixed-wing HAUVs are capable of high-speed transit across different media. For instance, they can rapidly transition between air and water or perform takeoff and landing maneuvers in a gliding fashion, similar to traditional seaplanes.
Bio-inspired HAUVs, drawing inspiration from natural amphibians like flying fish, seabirds, and remoras, offer several advantages: they enable efficient cross-domain transitions by mimicking natural behaviors, adapt to diverse environments with multi-functional capabilities, can be energy-efficient in specific modes (like flapping wings for slow underwater movement), and have miniaturization potential [28,29,30,31,32,33,34]. However, they also have notable disadvantages: limited underwater maneuverability, high mechanical demands for water-to-air transitions, design trade-offs where features optimized for one domain hinder performance in another, limited payload capacity restricting complex tasks, and technical complexity in control systems.
Fixed-wing HAUVs, which use wing-generated lift for airborne flight, offer advantages such as efficient aerial performance (high-speed flight with low power consumption, suitable for covering large distances), versatile cross-domain functionality, innovative design adaptations, and rapid deployment [32,35,36,37,38,39]. However, they are also plagued by several drawbacks: take-off processes are problematic—surface glide take-offs demand lengthy distances and are easily disrupted by surface disturbances, while tilt-takeoffs require meticulous coordination of attitude and speed, with mismatches leading to insufficient lift and crashes; underwater efficiency is low—airborne propellers perform poorly underwater, necessitating retrofits such as water plungers, and wide wings generate significant drag during cross-domain movement, posing a risk of structural damage upon high-speed water entry.
Figure 1. Representative bio-inspired HAUVs. (a) Harvard University RoboBee [33] (b) Biomimetic flying squid [40] (c) MIT biomimetic bonito [41] (d) Beihang University hitchhiking robot [26] (e) AquaMAV [34] (f) HAUV with folding wings [42] (g) MIT biomimetic birds [28] (h) Chemical combustion HAUV [43].
Figure 1. Representative bio-inspired HAUVs. (a) Harvard University RoboBee [33] (b) Biomimetic flying squid [40] (c) MIT biomimetic bonito [41] (d) Beihang University hitchhiking robot [26] (e) AquaMAV [34] (f) HAUV with folding wings [42] (g) MIT biomimetic birds [28] (h) Chemical combustion HAUV [43].
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Figure 2. Representative fixed-wing HAUVs. (a) Flying Fish [32] (b) Test Sub II [35] (c) Dipper (d) Triangular plate-like HAUV [36] (e) HAUV with foldable wings [38] (f) EagleRay [37].
Figure 2. Representative fixed-wing HAUVs. (a) Flying Fish [32] (b) Test Sub II [35] (c) Dipper (d) Triangular plate-like HAUV [36] (e) HAUV with foldable wings [38] (f) EagleRay [37].
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2.2. The VTOL Way HAUVs

The VTOL way HAUVs usually fall into two categories: (1) Multi-rotor HAUVs, which retain the superior agility of their UAV counterparts, offering stable low-speed operation, vertical takeoff and landing (VTOL), and precise hovering at fixed positions. Such vehicles are particularly well-suited for operations in environments that are spatially limited or structurally complex. (2) Multi-modal HAUVs, integrate the hovering capability of multi-rotor systems with the extended air and underwater endurance typically seen in fixed-wing HAUVs or underwater gliders.
Multi-rotor Hybrid Aerial Underwater Vehicles (HAUVs) build on the structural framework of multi-rotor UAVs, with their propulsion systems directly providing the lift and torque needed for flight. Over the past five years, they have gained growing favor among researchers due to their significant advantages in flexibility and stability, particularly their unique hovering and Vertical Take-Off and Landing (VTOL) capabilities, which facilitate flight, diving, and cross-domain testing. Their structural layouts are categorized into single-layered and double-layered designs.
Double-layer multi-rotor HAUVs adopt a two-layer propulsion system to enable seamless movement in and out of water (Figure 3). For example, Brazil’s Federal University of Minas Gerais developed the HyDrone, a two-layer quadrotor with specialized lower-layer propellers to enhance underwater propulsion efficiency [44,45]. Rutgers University’s Naviator series, also a dual-layer quadrotor, uses its propulsion system for locomotion in air, underwater, and across the water surface, with pool tests validating its amphibious capabilities; the team has also conducted quantitative analyses to optimize its structures [46,47]. China’s Air Force Engineering University has developed a similar double-layer quadrotor prototype, primarily for control algorithm testing [48].
Single-layer multi-rotor HAUVs, meanwhile, feature varied designs (Figure 4). The University of California, Berkeley, built a miniature quadrotor that can accelerate from underwater, break the surface smoothly, and take off, though additional maneuvering tests are pending [49]. The National University of Singapore developed a tilt-quadrotor with propellers that adjust direction via a tilting mechanism—vertical for aerial flight and horizontal/downward for underwater vector propulsion, enhancing underwater maneuverability; it has undergone iterations and pool tests [50,51]. Tongji University and collaborators presented the TJ-FlyingFish, a quadrotor with tiltable dual-speed propulsion units, which has undergone thorough practicality, functionality, and maneuverability testing, functionality, and maneuverability testing [52].
Single-layer systems face greater challenges in continuous water exit, as rotors must handle sudden thrust changes at the surface. Thus, buoyancy control systems are often used when coherent surface movement is unnecessary. Oakland University’s Loon Copter uses a pump-and-drain mechanism to adjust weight: draining ballast tanks to float vertically for take-off, and filling them to submerge, with a 90° tilt positioning propellers horizontally for improved underwater maneuverability, validated in pool tests [54,62]. Georgia Tech’s GTQ-Cormorant uses buoyancy adjustment for vertical snorkeling, with pool tests confirming underwater and surface VTOL capabilities [55]. China’s Shanghai Maritime University developed a quadrotor prototype for cross-domain motion control testing (full amphibious capability unreported), while Shanghai Jiao Tong University’s Nezha-F, a small HAUV with a piston variable buoyancy system, balances aerial and underwater performance compactly without excessive actuators [53,57]. Recently, a series of new prototypes have continued to emerge, advancing the field [58,59,60,61,63,64].
Inspired by traditional Underwater Gliders (UG) and existing HAUV designs, Shanghai Jiao Tong University (SJTU) proposed a multi-modal HAUV (based on multi-rotor) concept capable of vertical flight, horizontal flight, underwater gliding, and stable water-air interface crossing. This multi-modal HAUV uses the UG motion mode underwater, adjusting net buoyancy and attitude via an internal mechanism to achieve low-energy, long-duration underwater gliding [65,66]. In the air, it can switch between multi-rotor UAV vertical flight and fixed-wing UAV horizontal flight, with the rotor propulsion system and fixed wing coordinating to provide appropriate power and lift for hovering, VTOL, or high-speed flight. SJTU made progressive developments: in 2017, it successfully developed the Nezha I, a principal prototype of a multi-rotor HAUV with vertical underwater locomotion; in 2018, it launched Nezha II, the first multi-modal HAUV prototype integrating horizontal flight, vertical flight, and underwater gliding. To date, the “Nezha” series has completed the third iteration, including the “Nezha III (tail-sitting)” and “Nezha III (VTOL)” prototypes (Figure 5). It is foreseeable that more multi-modal HAUVs will be developed to meet growing demands for rapid surveillance, expanding the application range and capabilities of amphibious vehicles [67,68].

2.3. Comparative Analysis of HAUV Types

While the previous subsections described splash-entry (bio-inspired and fixed-wing) and VTOL (multi-rotor and multi-modal) HAUVs separately, a direct parameter-based comparison provides clearer insights into their relative strengths and limitations. Table 1 summarizes representative HAUV categories across critical parameters, including transition mechanisms, payload capacity, underwater maneuverability, aerial endurance, stability, and potential application scenarios.
This comparison highlights that bio-inspired systems are most promising for miniaturized applications but remain limited in payload; fixed-wing splash-entry designs excel in long-range aerial coverage but face challenges in underwater propulsion; VTOL multi-rotors offer superior stability for optical profiling at localized scales; and multi-modal HAUVs provide the most balanced solution for adaptive missions, albeit with added system complexity.
To provide a comprehensive overview of the global research landscape, the distribution of HAUV-related studies by country/region is summarized in Table 2. This table highlights the geographical diversity of the field and emphasizes the dominant contributions from China and the United States.
In summary, HAUV research has developed along multiple directions, ranging from biomimetic design and propulsion mechanisms to cross-domain control strategies and prototype demonstrations. While these studies vary in technical approach and application focus, they collectively reflect the growing attention to versatile aerial–aquatic platforms. To provide a clearer picture of the global research landscape, we summarize in Table 2 the distribution of HAUV-related studies by country and region. The table highlights the leading contributions from China and the United States, along with representative studies from the United Kingdom, and other countries. This international distribution underlines the increasing worldwide interest in HAUVs and indicates significant potential for future cross-disciplinary and cross-border collaborations.
Table 2. Distribution of HAUV-related studies by country/region.
Table 2. Distribution of HAUV-related studies by country/region.
Country/RegionRepresentative StudiesNumber of Studies
ChinaNezha series (Nezha-F [57], Nezha-IV [58], Nezha-SeaDart [59], Nezha-H [64], Nezha-X [61]); WuKong [60]; TJ-FlyingFish [52]; Wu et al. flying boat [32]; Plunge-diving gannet [29,30,31,42]; Buoyancy system [68]; Control and stability works [26,27,48,53,66,67]; Early Soviet “flying submarine” concept [6]; Morphable quadrotors [50];~20
USALoon Copter [54]; MIT hybrid fish [28,41]; aquatic microrobots [33]; Naviator [46,47]; DARPA submersible aircraft [6]; GTQ-Cormorant [55]; Miniature quadrotor [49]; Dynamic modeling and fixed-wing concepts [35,37,39]; Squid-like soft-morphing vehicle [40]; Morphable quadrotors [51]; Fixed-wing aquatic UAV [36]~14
UKAquaMAV and morphing aquatic MAV (Imperial College London, Kovac Lab) [33,43]; Wing model [2]; IROS aquatic-aerial works [44]4
Others (Europe collaboration)Hitchhiking robots (Science Robotics, ETH/Kovac collaboration) [26]; HyDrone project and propeller configuration [44,45]2–3
Total ~40

3. Ocean Optical Instruments and Deployment Methods

Optical techniques allow sampling at much higher spatial and temporal resolution, providing a more informed context for interpreting the results from discrete samples [69]. In marine optics, there are two main types of physical quantities used to describe the characteristics of light transmission in water media, namely Inherent Optical Properties (IOPs) and Apparent Optical Properties (AOPs) [70]. IOPs are those that depend only on the water medium and are independent of the ambient light field in the water medium, such as beam absorption coefficient, volume scattering function, beam attenuation coefficient, single scatter probability, and backscatter coefficient. AOPs are those that depend not only on the water medium but also on the geometric structure of the surrounding light field. Commonly used apparent optical properties include irradiance reflectance, remote sensing reflectance, diffuse attenuation coefficient, and mean cosine. The measurement of apparent optical properties is obtained indirectly by measuring spectral radiance and spectral irradiance and is a passive measurement method. Measurement of inherent optical properties is an active method, and the types of instruments used to measure IOPs include: spectral absorption meters, spectral attenuation meters, volume scattering function meters, and spectral backscatter meters.

3.1. Inherent Optical Instruments and Observation Methods

The IOPs of seawater and its components are unaffected by sunlight and can be directly measured in situ. Absorption and angular scattering describe the mechanisms through which monochromatic (i.e., narrowband) and collimated (i.e., highly directional) light is removed from a beam through energy conversion and directional deflection, respectively. The attenuation coefficient (c(λ)) is the sum of the absorption coefficient (a(λ)) and the scattering coefficient (b(λ)) [71]. In situ optical instruments available on the market can provide estimates of beam attenuation, backscattering, side scattering, and absorption coefficients, which serve as indirect indicators of particle concentration. The parameters of some commonly used IOP instruments are given in Table 3, together with an evaluation of their compatibility with HAUV platforms.
As this type of instrument is usually part of an active observing system with its own light source, which has a high degree of modularity and automation in the observation, it can be flexibly deployed on different platforms. These instruments have been routinely deployed on slow-drop packages (packages that fall under their own weight [18]), towed systems, AUVs and profiling floats, submarines, seafloor tripods, and moorings [19,20,21,22,23,24,25]. Consideration of the deployment platform should include the potential for the platform to interfere with particles (e.g., by inducing turbulence that breaks up aggregates) and the ability of the platform to cope with the weight, size, power, and data streaming requirements of a particular sensor.

3.2. Apparent Optical Sensors and Observation Methods

AOPs are strongly associated with the biological, chemical, and lithogenic components within the water column, making them valuable bio-optical indicators for profiling water column characteristics [72]. In recent decades, considerable scientific attention has focused on ocean surface reflectance due to its critical role in ocean color remote sensing applications. For these applications, many radiometric measurements have been collected for (i) the spectral diffuse attenuation coefficients Kd, Ku, and KLu for Ed, Eu, and Lu, respectively; (ii) the spectral irradiance reflectance, R = Eu/Ed; and (iii) the spectral remote-sensing reflectance just above the sea surface, Rrs(z = 0+) = Lw(z = 0+)/Ed(z = 0+) where Lw is the spectral water-leaving radiance and z = 0+ is just above the sea surface.
Radiance and irradiance sensors are typically categorized based on their ability to distinguish light across different spectral wavelengths [70]. Radiance refers to the light flux measured per unit solid angle and per unit projected area. It is typically obtained by narrowing the radiometer’s field of view and assuming the radiance remains spatially uniform or varies minimally within that solid angle. Plane irradiance, often simplified as irradiance, is quantified using a cosine collector and represents the light flux per unit surface area. Field measurements commonly include both downward and upward irradiance, defined as the radiant energy passing through a horizontal plane per unit time in the respective directions. At present, internationally representative marine radiometers include the RAMSES series (TRIOS), the OCR series (Seabird), and the C-OPS radiation measurement system (BioSpheric). Figure 6 shows typical commercial hyperspectral radiometer products.
In-water radiometric profiling relies primarily on deployments such as freefalls, which operate down to a few tens of meters from deployment platforms [73,74]. These systems enable vertical sampling from the surface to several tens of meters while minimizing interference from the deployment platform [75]. They have replaced the previous winch systems, which required extensive analysis to quantify the superstructure disturbances affecting the radiometric data [76]. Beyond eliminating disturbances from the platform’s superstructure, several further deployment criteria must be fulfilled to ensure measurement accuracy. These include (i) employing radiometric instruments and deployment mechanisms (e.g., free-fall systems) designed to reduce self-shading—an effect where the measurement apparatus itself disturbs the surrounding light field [77]; (ii) collecting a sufficient number of measurements—from just below the sea surface to several meters depth—to ensure statistical reliability, preferably under conditions where the water column exhibits vertically uniform optical properties; (iii) monitoring the pitch and roll angles of all measurement units (e.g., free-fall sensors and surface reference devices); and (iv) routinely logging system offset values to maintain data consistency. Some representative platforms are shown in Figure 7.

4. Feasibility of Hybrid Aerial Underwater Optical Observation System

Drawing from the preceding analysis, the performance characteristics of the two dominant HAUV types can be contrasted: (1) Most current HAUV platforms are adapted from established fixed-wing or multi-rotor UAV architectures, each offering distinct strengths and limitations. However, these systems still require further refinement, as their diving capabilities remain limited—making them primarily applicable to shallow-water environments (depths less than 100 m). (2) Most splash entry/exit HAUVs have the ability to fly at high speed in the air [4]. In contrast to the VTOL capabilities of multi-rotor HAUVs, fixed-wing systems face greater challenges in smoothly transitioning between air and water. Their cross-domain operations are harder to control and more susceptible to failure due to environmental disturbances such as wind and wave interference. Similar conclusions have been drawn in recent stability analyses of trans-media HAUVs, which emphasized that posture disturbances and hydrodynamic impacts are critical challenges for reliable operation [27]. In addition, the optical sensor can be damaged by impact forces during water entry. Therefore, for underwater optical observation of the ocean, the VTOL type of HAUV is more suitable.
To further clarify the impact of these technical challenges on optical measurements, we provide a qualitative ranking by degree of influence. The most critical factor is platform stability and hydrodynamic disturbances, because even minor posture fluctuations can significantly bias AOPs measurements, such as diffuse attenuation and remote-sensing reflectance [27]. The second most influential issues are self-shading and platform-induced turbulence, which modify the natural light field and particle distribution and thereby degrade both inherent and apparent optical observations [77]. Impact forces during water entry are assessed as having a medium influence: while they primarily threaten sensor survivability and alignment, they also interrupt data continuity if damage or misalignment occurs [7]. Finally, limitations in energy supply and endurance represent a moderate constraint, as they primarily restrict the achievable profiling duration and spatial coverage rather than directly degrading the quality of optical measurements [54].
Mitigation approaches include active control and attitude-stabilization algorithms demonstrated on amphibious multirotor prototypes (e.g., Naviator; TJ-FlyingFish) to minimize posture errors [47,52]; structural optimization (streamlined hulls, foldable arms) to reduce turbulence and self-shadowing [38,57]; protective housings and damping mechanisms to limit water-entry shocks on sensitive radiometers and IOP sensors [43]; and hybrid propulsion with buoyancy regulation to extend endurance while maintaining stable underwater orientation [68]. Collectively, these strategies target the primary error sources that currently limit HAUV-based optical measurements.
An ideal amphibious optical profiling system must take into account factors such as payload, air and underwater endurance, attitude, and shape. For inherent optical observation systems, the measurement of inherent optical parameters is an active observation method that does not rely on the attitude of the underwater platforms. Amphibious inherent optical platforms are relatively simple, and the only problem to be solved is air endurance. This requires large motor and battery reserves, which further affects the air endurance, and a balance must be struck between the two. For an apparent optical observation system, the apparent optical parameters require the platform to maintain a certain geometric attitude underwater, and both require synchronous measurement of water depth. Therefore, it is necessary to design a shape that can ensure posture underwater and adjust the center of gravity and buoyancy (Figure 8). Attitude adjustment can also assist some attitude adjustment algorithms to keep the observation attitude horizontal. In addition, the color of the amphibious drone platform should be black to avoid the influence of light; the arms and hull of amphibious drones should avoid self-shadowing as much as possible, or use Monte Carlo methods to eliminate shadow effects [77]. In short, as optical sensors become more modular and functional, more amphibious optical systems will emerge in the future, making optical measurements more convenient, automated, and intelligent.

5. Amphibious Optical Observation Systems: Potential Applications and Future Work

At present, it is important to note that the application of Hybrid Aerial Underwater Vehicles (HAUVs) in underwater optical observation is still at the conceptual and experimental stage. Most of the reported platforms have been tested only in laboratory pools or near-shore demonstrations, rather than in routine ocean observation campaigns. For instance, Rutgers University’s Naviator platform has successfully carried out seamless transitions between air and water and demonstrated the ability to support optical sensors in pool trials [46,47]. Similarly, Tongji University’s TJ-FlyingFish prototype has shown stable underwater hovering and maneuverability with tiltable propulsion units, which makes it a promising candidate for integrating radiometers and scattering sensors [52]. In addition, the Nezha series developed by Shanghai Jiao Tong University represents progressive advancements toward multi-modal amphibious operation, including vertical flight, underwater gliding, and real-sea trials. These cases represent successful proof-of-concept demonstrations, but they remain limited compared to the requirements of operational deployments.
Compared to existing intelligent mobile optical observation platforms, amphibious optical systems have advantages both in the air and underwater, making them particularly suitable for emergency and precision observation. For example, in the event of a red tide outbreak, an amphibious optical system can initially conduct small aerial patrols using a hyperspectral camera integrated into a drone. The location of the red tide can be pinpointed using real-time image processing by a shore-based computer. The amphibious optical drone then conducts optical observations of the seawater profile, obtaining underwater optical information and inverting parameters of phytoplankton, CDOM, and other particulate matter. The specific schematic diagram is shown in Figure 9. By conducting integrated observation of suspicious targets, thereby reducing observation costs and shortening response time, new observation methods can be provided for pollution spills, red tides, and conventional fixed point observation. In particular, with its excellent networking and observation capabilities, it can make observations more intelligent and efficient.
Overall, it is essential to enhance the theoretical framework by incorporating concrete application scenarios, proposing novel design strategies, conducting rigorous scheme evaluations, and actively performing experimental verification—rather than remaining constrained by the boundaries of current research. The main purpose of this article is to expand the scope of application based on existing amphibious drones. However, much remains to be done. To achieve rapid observation in the field of ocean optics, we should propose new shapes, structures, and dynamic layouts based on specific application scenarios to support the development of ocean optics and ocean remote sensing. Further research is needed in the following areas: 1. Conduct in-depth research on the hydrodynamic process of amphibious unmanned aerial vehicles entering and exiting the water, and optimize existing control algorithms; 2. Optimize the existing structural layout to make it easier for the body to maintain a stable posture underwater while avoiding self-shadowing; 3. Experiment with different types of optical probe combinations to link ocean optics and the ocean.
This review highlights the potential of HAUVs as emerging platforms for ocean optical observations. By integrating aerial and underwater capabilities, HAUVs simplify cross-domain monitoring and enable rapid, cost-effective responses to dynamic marine environments. Among current designs, VTOL-type HAUVs show greater suitability for optical profiling due to their stability and smooth transitions across the air–sea interface, which are essential for accurate measurements of apparent optical properties. While significant challenges remain in hydrodynamic stability, platform–sensor interactions, and endurance optimization, the integration of HAUVs with modern optical instruments offers a transformative pathway to complement satellite and buoy observations, enhance emergency monitoring, and advance marine remote sensing. Continued research on control strategies, structural design, and sensor integration will be key to realizing HAUVs as reliable operational tools in ocean science.

Author Contributions

Conceptualization, H.Q. and S.H.; methodology, H.Q.; validation, J.Z.; formal analysis, S.H.; resources, G.W.; writing—original draft preparation, S.H.; writing—review and editing, J.Z.; funding acquisition, G.W. and S.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Shenzhen Science and Technology Program (Grant No. JCYJ20210324120207020).

Data Availability Statements

No new data were created or analyzed in this study. Data sharing is not applicable to this article.

Acknowledgments

We would like to acknowledge anonymous reviewers for their helpful comments on the manuscript. We thank the AI-based tool for its assistance in language refinement, with all final revisions made by the authors.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Peng, Z.; Wang, J.; Wang, D.; Han, Q.-L. An Overview of Recent Advances in Coordinated Control of Multiple Autonomous Surface Vehicles. IEEE Trans. Ind. Inform. 2021, 17, 732–745. [Google Scholar] [CrossRef]
  2. Lock, R.; Vaidyanathan, R.; Burgess, S.C. Development of a biologically inspired multi-modal wing model for aerial-aquatic robotic vehicles. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots & Systems, Taipei, Taiwan, 18–22 October 2010. [Google Scholar]
  3. Park, H.; Choi, H. Aerodynamic characteristics of flying fish in gliding flight. J. Exp. Biol. 2010, 213, 3269–3279. [Google Scholar] [CrossRef] [PubMed]
  4. Zeng, Z.; Lyu, C.; Bi, Y.; Jin, Y.; Lu, D.; Lian, L. Review of hybrid aerial underwater vehicle: Cross-domain mobility and transitions control. Ocean. Eng. 2022, 248, 110840. [Google Scholar] [CrossRef]
  5. Valdivia y Alvarado, P.; Taher, T.; Kurniawati, H.; Weymouth, G.; Khan, R.R.; Leighton, J.; Papadopoulos, G.; Barbastathis, G.; Patrikalakis, N. A Coastal Distributed Autonomous Sensor Network. In Proceedings of the MTS/IEEE OCEANS Conference, Kona, HI, USA, 19–22 September 2011. [Google Scholar]
  6. Yang, X.; Wang, T.; Liang, J.; Yao, G.; Liu, M. Survey on the novel hybrid aquatic–aerial amphibious aircraft: Aquatic unmanned aerial vehicle (AquaUAV). Prog. Aerosp. Sci. 2015, 74, 131–151. [Google Scholar] [CrossRef]
  7. Lu, D.; Guo, Y.; Xiong, C.; Zeng, Z.; Lian, L. Takeoff and Landing Control of a Hybrid Aerial Underwater Vehicle on Disturbed Water’s Surface. IEEE J. Ocean. Eng. 2022, 47, 295–311. [Google Scholar] [CrossRef]
  8. Lyu, C.; Lu, D.; Xiong, C.; Hu, R.; Jin, Y.; Wang, J.; Zeng, Z.; Lian, L. Toward a gliding hybrid aerial underwater vehicle: Design, fabrication, and experiments. J. Field Robot. 2022, 39, 543–556. [Google Scholar] [CrossRef]
  9. Bowers, D.G.; Kratzer, S.; Morrison, J.R.; Smith, P.S.D.; Tett, P.; Walne, A.W.; Wild-Allen, K. On the calibration and use of in situ ocean colour measurements for monitoring algal blooms. Int. J. Remote Sens. 2001, 22, 359–368. [Google Scholar] [CrossRef]
  10. Wang, M.H.; Isaacman, A.; Franz, B.A.; McClain, C.R. Ocean-color optical property data derived from the Japanese ocean color and temperature scanner and the French polarization and directionality of the earth’s reflectances: A comparison study. Appl. Opt. 2002, 41, 974–990. [Google Scholar] [CrossRef]
  11. Stramska, M.; Stramski, D.; Hapter, R.; Kaczmarek, S.; Ston, J. Bio-optical relationships and ocean color algorithms for the north polar region of the Atlantic. J. Geophys. Res-Oceans 2003, 108, 314310. [Google Scholar] [CrossRef]
  12. Werdell, P.J.; McKinna, L.I.W.; Boss, E.; Ackleson, S.G.; Craig, S.E.; Gregg, W.W.; Lee, Z.; Maritorena, S.; Roesler, C.S.; Rousseaux, C.S.; et al. An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing. Prog. Oceanogr. 2018, 160, 186–212. [Google Scholar] [CrossRef]
  13. Liu, H.Z.; Zhou, Q.M.; Li, Q.Q.; Hu, S.B.; Shi, T.Z.; Wu, G.F. Determining switching threshold for NIR-SWIR combined atmospheric correction algorithm of ocean color remote sensing. Isprs. J. Photogramm. 2019, 153, 59–73. [Google Scholar] [CrossRef]
  14. Platt, T.; Sathyendranath, S.; Bouman, H.; Brockmann, C.; McKee, D. Special Issue on Remote Sensing of Ocean Color: Theory and Applications. Sensors 2020, 20, 3445. [Google Scholar] [CrossRef]
  15. Chen, S.L.; Smith, W.O.; Yu, X.L. Revisiting the Ocean Color Algorithms for Particulate Organic Carbon and Chlorophyll-a Concentrations in the Ross Sea. J. Geophys. Res-Oceans 2021, 126, e2021JC017749. [Google Scholar] [CrossRef]
  16. Ferreira, A.; Brotas, V.; Palma, C.; Borges, C.; Brito, A.C. Assessing Phytoplankton Bloom Phenology in Upwelling-Influenced Regions Using Ocean Color Remote Sensing. Remote Sens. 2021, 13, 675. [Google Scholar] [CrossRef]
  17. Balch, W.M.; Drapeau, D.T.; Bowler, B.C.; Booth, E.S.; Goes, J.I.; Ashe, A.; Frye, J.M. A multi-year record of hydrographic and bio-optical properties in the Gulf of Maine: I. Spatial and temporal variability. Prog. Oceanogr. 2004, 63, 57–98. [Google Scholar] [CrossRef]
  18. Barnard, A.H.; Pegau, W.S.; Zaneveld, J.R.V. Global relationships of the inherent optical properties of the oceans. J. Geophys. Res. Ocean. 1998, 103, 24955–24968. [Google Scholar] [CrossRef]
  19. Jones, B.H.; Lee, C.M.; Toro-Farmer, G.; Boss, E.S.; Gregg, M.C.; Villanoy, C.L. Tidally driven exchange in an archipelago strait: Biological and optical responses. Oceanography 2011, 24, 142–155. [Google Scholar] [CrossRef]
  20. Chang, G.C.; Dickey, T.D. Optical and physical variability on timescales from minutes to the seasonal cycle on the New England shelf: July 1996 to June 1997. J. Geophys. Res. 2001, 106, 19997. [Google Scholar] [CrossRef]
  21. Dall’Olmo, G.; Westberry, T.K.; Behrenfeld, M.J.; Boss, E.; Slade, W.H. Significant contribution of large particles to optical backscattering in the open ocean. Biogeosciences 2009, 6, 947–967. [Google Scholar] [CrossRef]
  22. Downing, B.D.; Boss, E.; Bergamaschi, B.A.; Fleck, J.A.; Lionberger, M.A.; Ganju, N.K.; Schoellhamer, D.H.; Fujii, R. Quantifying fluxes and characterizing compositional changes of dissolved organic matter in aquatic systems in situ using combined acoustic and optical measurements. Limnol. Oceanogr. Methods 2009, 7, 119–131. [Google Scholar] [CrossRef]
  23. Wijesekera, H.W.; Pegau, W.S.; Boyd, T.J. Effect of surface waves on the irradiance distribution in the upper ocean. Opt. Express 2005, 13, 9257–9264. [Google Scholar] [CrossRef]
  24. Slade, W.H.; Boss, E.; Dall’Olmo, G.; Langner, M.R.; Loftin, J.; Behrenfeld, M.J.; Roesler, C.; Westberry, T.K. Underway and Moored Methods for Improving Accuracy in Measurement of Spectral Particulate Absorption and Attenuation. J. Atmospheric Ocean. Technol. 2010, 27, 1733–1746. [Google Scholar] [CrossRef]
  25. Zaneveld, J.R.V.; Boss, E.; Moore, C.M. A Diver-Operated Optical and Physical Profiling System. J. Atmospheric Ocean. Technol. 2010, 18, 1421–1427. [Google Scholar] [CrossRef]
  26. Li, L.; Wang, S.; Zhang, Y.; Song, S.; Wang, C.; Tan, S.; Zhao, W.; Wang, G.; Sun, W.; Yang, F.; et al. Aerial-aquatic robots capable of crossing the air-water boundary and hitchhiking on surfaces. Sci. Robot. 2022, 7, eabm6695. [Google Scholar] [CrossRef] [PubMed]
  27. Wei, T.; Lu, D.; Zeng, Z.; Lian, L. Trans-Media Kinematic Stability Analysis for Hybrid Unmanned Aerial Underwater Vehicle. J. Mar. Sci. Eng. 2022, 10, 275. [Google Scholar] [CrossRef]
  28. Gao, A.; Techet, A.H. Design considerations for a robotic flying fish. In Proceedings of the Oceans’11 MTS/IEEE KONA, Waikoloa, HI, USA, 19–22 September 2011. [Google Scholar]
  29. Liang, J.; Yang, X.; Wang, T.; Yao, G.; Zhao, W. Design and Experiment of a Bionic Gannet for Plunge-Diving. J. Bionic Eng. 2013, 10, 282–291. [Google Scholar] [CrossRef]
  30. Yang, X.; Liang, J.; Wang, T.; Yao, G.; Han, C. Computational simulation of a submersible unmanned aerial vehicle impacting with water. In Proceedings of the IEEE International Conference on Robotics & Biomimetics, Shenzhen, China, 12–14 December 2013. [Google Scholar]
  31. Liang, J.; Yao, G.; Wang, T.; Yang, X.; Zhao, W.; Song, G.; Zhang, Y. Wing load investigation of the plunge-diving locomotion of a gannet Morus inspired submersible aircraft. Sci. China Technol. Sci. 2014, 57, 390–402. [Google Scholar] [CrossRef]
  32. Yao, G.; Liang, J.; Wang, T.; Yang, X.; Liu, M.; Zhang, Y. Submersible unmanned flying boat: Design and experiment. In Proceedings of the 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014), Bali, Indonesia, 5–10 December 2014; pp. 1308–1313. [Google Scholar]
  33. Chen, Y.; Wang, H.; Helbling, E.F.; Jafferis, N.T.; Zufferey, R.; Ong, A.; Ma, K.; Gravish, N.; Chirarattananon, P.; Kovac, M.; et al. A biologically inspired, flapping-wing, hybrid aerial-aquatic microrobot. Sci. Robot. 2017, 2, eaao5619. [Google Scholar] [CrossRef]
  34. Siddall, R.; Ortega, A.; Kovač, M. Wind and water tunnel testing of a morphing aquatic micro air vehicle. Interface Focus 2017, 7, 20160085. [Google Scholar] [CrossRef]
  35. Edwards, D.; Arnold, N.; Heinzen, S.; Strem, C.; Young, T. Flying emplacement of an underwater glider. In Proceedings of the OCEANS 2017—Anchorage, Anchorage, AK, USA, 18–21 September 2017; pp. 1–6. [Google Scholar]
  36. Moore, J.; Fein, A.; Setzler, W. Design and Analysis of a Fixed-Wing Unmanned Aerial-Aquatic Vehicle. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Brisbane, QLD, Australia, 21–25 May 2018; pp. 1236–1243. [Google Scholar]
  37. Weisler, W.; Stewart, W.; Anderson, M.B.; Peters, K.J.; Gopalarathnam, A.; Bryant, M. Testing and Characterization of a Fixed Wing Cross-Domain Unmanned Vehicle Operating in Aerial and Underwater Environments. IEEE J. Ocean. Eng. 2018, 43, 969–982. [Google Scholar] [CrossRef]
  38. Guo, D. Modelling and Experimental Investigations of a bi-Modal Unmanned Underwater/Air System. Ph.D. Thesis, RMIT University, Melbourne VIC, Australia, 2019. [Google Scholar]
  39. Stewart, W.; Weisler, W.; Anderson, M.; Bryant, M.; Peters, K. Dynamic Modeling of Passively Draining Structures for Aerial–Aquatic Unmanned Vehicles. IEEE J. Ocean. Eng. 2020, 45, 840–850. [Google Scholar] [CrossRef]
  40. Hou, T.; Yang, X.; Su, H.; Jiang, B.; Chen, L.; Wang, T.; Liang, J. Design and Experiments of a Squid-like Aquatic-aerial Vehicle with Soft Morphing Fins and Arms. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 20–24 May 2019; pp. 4681–4687. [Google Scholar]
  41. Fabian, A.; Feng, Y.; Swartz, E.; Thurmer, D.; Wang, R. Hybrid Aerial Underwater Vehicle; MIT Lincoln Lab: Lexington, MA, USA, 2012. [Google Scholar]
  42. Wang, T.M.; Yang, X.B.; Liang, J.H.; Yao, G.C.; Zhao, W.D. CFD based investigation on the impact acceleration when a gannet impacts with water during plunge diving. Bioinspir. Biomim. 2013, 8, 036006. [Google Scholar] [CrossRef] [PubMed]
  43. Zufferey, R.; Ancel, A.O.; Farinha, A.; Siddall, R.; Armanini, S.F.; Nasr, M.; Brahmal, R.V.; Kennedy, G.; Kovac, M. Consecutive aquatic jump-gliding with water-reactive fuel. Sci. Robot. 2019, 4, eaax7330. [Google Scholar] [CrossRef] [PubMed]
  44. da Rosa, R.T.S.; Evald, P.J.D.O.; Drews-Jr, P.L.J.; Neto, A.A.; Horn, A.C.; Azzolin, R.Z.; Botelho, S.S.C. A Comparative Study on Sigma-Point Kalman Filters for Trajectory Estimation of Hybrid Aerial-Aquatic Vehicles. In Proceedings of the 25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain, 1–5 October 2018; pp. 7460–7465. [Google Scholar]
  45. Horn, A.C.; Pinheiro, P.M.; Silva, C.B.; Alves Neto, A.; Drews, P.L.J., Jr. A Study on Configuration of Propellers for Multirotor-like Hybrid Aerial-Aquatic Vehicles. In Proceedings of the 19th International Conference on Advanced Robotics (ICAR), Belo Horizonte, Brazil, 2–6 December 2019; pp. 173–178. [Google Scholar]
  46. Maia, M.M.; Soni, P.; Diez, F.J. Demonstration of an Aerial and Submersible Vehicle Capable of Flight and Underwater Navigation with Seamless Air-Water Transition. arXiv 2015, arXiv:1507.01932. [Google Scholar] [CrossRef]
  47. Maia, M.M.; Mercado, D.A.; Diez, F.J. Design and Implementation of Multirotor Aerial-Underwater Vehicles with Experimental Results. In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, Canada, 24–28 September 2017; 2017; pp. 961–966. [Google Scholar]
  48. Chen, G.; Liu, A.; Hu, J.; Feng, J.; Ma, Z. Attitude and Altitude Control of Unmanned Aerial-Underwater Vehicle Based on Incremental Nonlinear Dynamic Inversion. IEEE Access 2020, 8, 156129–156138. [Google Scholar] [CrossRef]
  49. Zha, J.; Thacher, E.; Kroeger, J.; Makiharju, S.A.; Mueller, M.W. Towards breaching a still water surface with a miniature unmanned aerial underwater vehicle. In Proceedings of the International Conference on Unmanned Aircraft Systems (ICUAS), Atlanta, GA, USA, 11–14 June 2019; pp. 1178–1185. [Google Scholar]
  50. Tan, Y.H.; Chen, B.M. Design of a Morphable Multirotor Aerial-Aquatic Vehicle. In Proceedings of the MTS/IEEE Oceans Seattle Conference (Oceans Seattle), Seattle, WA, USA, 27–31 October 2019. [Google Scholar]
  51. Tan, Y.H.; Chen, B.M. A Morphable Aerial-Aquatic Quadrotor with Coupled Symmetric Thrust Vectoring. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Electr Network, 31 May–15 June 2020; pp. 2223–2229. [Google Scholar]
  52. Liu, X.; Dou, M.; Huang, D.; Gao, S.; Yan, R.; Wang, B.; Cui, J.; Ren, Q.; Dou, L.; Gao, Z.; et al. TJ-FlyingFish: Design and Implementation of an Aerial-Aquatic Quadrotor with Tiltable Propulsion Units. In Proceedings of the 2023 IEEE International Conference on Robotics and Automation (ICRA), London, UK, 29 May–2 June 2023; pp. 7324–7330. [Google Scholar]
  53. Chen, Q.; Zhu, D.; Liu, Z. Attitude control of aerial and underwater vehicles using single-input FUZZY P+ID controller. Appl. Ocean. Res. 2021, 107, 102460. [Google Scholar] [CrossRef]
  54. Alzu’bi, H.; Mansour, I.; Rawashdeh, O. Loon Copter: Implementation of a hybrid unmanned aquatic–aerial quadcopter with active buoyancy control. J. Field Robot. 2018, 35, 764–778. [Google Scholar] [CrossRef]
  55. Bershadsky, D.; Haviland, S.; Valdez, P.E.; Johnson, E. Design Considerations of Submersible Unmanned Flying Vehicle for Communications and Underwater Sampling. In Proceedings of the MTS/IEEE Oceans Conference, Monterey, CA, USA, 19–23 September 2016. [Google Scholar]
  56. Staff. Submersible Drone Can Hide Underwater Then Launch to Perform Aerial Missions. 2016. Available online: https://www.design-engineering.com/new-uav-can-launch-underwater-aerial-missions-1004023004/ (accessed on 15 September 2025).
  57. Bai, Y.; Jin, Y.; Liu, C.; Zeng, Z.; Lian, L. Nezha-F: Design and Analysis of a Foldable and Self-Deployable HAUV. IEEE Robot. Autom. Lett. 2023, 8, 2309–2316. [Google Scholar] [CrossRef]
  58. Jin, Y.F.; Bi, Y.B.; Lyu, C.X.; Bai, Y.L.; Zeng, Z.; Lian, L. Nezha-IV: A hybrid aerial underwater vehicle in real ocean environments. J. Field Robot. 2024, 41, 420–442. [Google Scholar] [CrossRef]
  59. Jin, Y.F.; Zeng, Z.; Lian, L. Nezha-SeaDart: A tail-sitting fixed-wing vertical takeoff and landing hybrid aerial underwater vehicle. J. Field Robot. 2025, 42, 137–152. [Google Scholar] [CrossRef]
  60. Liu, Y.; Li, C.; Li, J.; Lin, Z.; Meng, W.; Zhang, F. WuKong: Design, Modeling and Control of a Compact Flexible Hybrid Aerial-Aquatic Vehicle. IEEE Robot. Autom. Lett. 2025, 10, 1417–1424. [Google Scholar] [CrossRef]
  61. Wang, D.; Zhang, Z.; Zeng, Z.; Lian, L. Nezha-X: A Self-Foldable HAUV That can Launch From a Tube. IEEE Robot. Autom. Lett. 2025, 10, 6904–6911. [Google Scholar] [CrossRef]
  62. Alzu’Bi, H.; Akinsanya, O.; Kaja, N.; Mansour, I.; Rawashdeh, O. Evaluation of an aerial quadcopter power-plant for underwater operation. In Proceedings of the 2015 10th International Symposium on Mechatronics and Its Applications (ISMA), Sharjah, United Arab Emirates, 8–10 December 2015. [Google Scholar]
  63. Bi, Y.; Xu, Z.; Shen, Y.; Zeng, Z.; Lian, L. Design and Implementation of a Bone-Shaped Hybrid Aerial Underwater Vehicle. IEEE Robot. Autom. Lett. 2024, 9, 7318–7325. [Google Scholar] [CrossRef]
  64. Song, X.; Bai, Y.; Bi, Y.; Wang, Y.; Zeng, Z.; Zhang, H.; Zhou, F.; Lian, L. Nezha-H: An HAUV for Aerial and Underwater Observation and Sampling. IEEE Robot. Autom. Lett. 2025, 10, 6776–6783. [Google Scholar] [CrossRef]
  65. Lu, D.; Xiong, C.; Lyu, B.; Zeng, Z.; Lian, L. Multi-Mode Hybrid Aerial Underwater Vehicle with Extended Endurance. In Proceedings of the 2018 OCEANS—MTS/IEEE Kobe Techno-Oceans (OTO), Kobe, Japan, 28–31 May 2018; pp. 1–7. [Google Scholar]
  66. Lu, D.; Xiong, C.; Zeng, Z.; Lian, L. Adaptive Dynamic Surface Control for a Hybrid Aerial Underwater Vehicle With Parametric Dynamics and Uncertainties. IEEE J. Ocean. Eng. 2020, 45, 740–758. [Google Scholar] [CrossRef]
  67. Lu, D.; Xiong, C.; Zhou, H.; Lyu, C.; Hu, R.; Yu, C.; Zeng, Z.; Lian, L. Design, fabrication, and characterization of a multimodal hybrid aerial underwater vehicle. Ocean. Eng. 2021, 219, 108324. [Google Scholar] [CrossRef]
  68. Hu, R.; Lu, D.; Xiong, C.; Lyu, C.; Zhou, H.; Jin, Y.; Wei, T.; Yu, C.; Zeng, Z.; Lian, L. Modeling, characterization and control of a piston-driven buoyancy system for a hybrid aerial underwater vehicle. Appl. Ocean. Res. 2022, 120, 102925. [Google Scholar] [CrossRef]
  69. Boss, E.; Guidi, L.; Richardson, M.J.; Stemmann, L.; Gardner, W.; Bishop, J.K.B.; Anderson, R.F.; Sherrell, R.M. Optical techniques for remote and in-situ characterization of particles pertinent to GEOTRACES. Prog. Oceanogr. 2015, 133, 43–54. [Google Scholar] [CrossRef]
  70. Li, L.; Stramski, D.; Darecki, M. Characterization of the Light Field and Apparent Optical Properties in the Ocean Euphotic Layer Based on Hyperspectral Measurements of Irradiance Quartet. Appl. Sci. 2018, 8, 2677. [Google Scholar] [CrossRef]
  71. Lee, Z.P.; Arnone, R.; Hu, C.M.; Werdell, P.J.; Lubac, B. Uncertainties of optical parameters and their propagations in an analytical ocean color inversion algorithm. Appl. Opt. 2010, 49, 369–381. [Google Scholar] [CrossRef]
  72. McClain, C.R.; Feldman, G.C.; Hooker, S.B. An overview of the SeaWiFS project and strategies for producing a climate research quality global ocean bio-optical time series. Deep. Sea Res. Part II Top. Stud. Oceanogr. 2004, 51, 5–42. [Google Scholar] [CrossRef]
  73. Waters, K.J.; Smith, R.C.; Lewis, M. Avoiding Ship-Induced Light-Field Perturbation in the Determination of Oceanic Optical Properties. Oceanography 1990, 3, 8–21. [Google Scholar] [CrossRef]
  74. Hooker, S.B.; Maritorena, S. An Evaluation of Oceanographic Radiometers and Deployment Methodologies. J. Atmos. Ocean. Technol. 2000, 17, 811–830. [Google Scholar] [CrossRef]
  75. Voss, K.J.; Nolten, J.W.; Edwards, G.D. Ship Shadow Effects On Apparent Optical Properties. In Proceedings of the 1986 Technical Symposium Southeast, Orlando, FL, USA, 1–4 April 1986. [Google Scholar]
  76. Doyle, J.P.; Zibordi, G. Optical Propagation within a Three-Dimensional Shadowed Atmosphere–Ocean Field: Application to Large Deployment Structures. Appl. Opt. 2002, 41, 4283–4306. [Google Scholar] [CrossRef]
  77. Gordon, H.R.; Ding, K. Self-shading of in-water optical instruments. Oceanography 1992, 37, 491–500. [Google Scholar]
Figure 3. Representative two-layer multi-rotor HAUVs. (a) HyDrone [45], (b) Naviator [47], (c) Air Force Engineering University HAUV [48].
Figure 3. Representative two-layer multi-rotor HAUVs. (a) HyDrone [45], (b) Naviator [47], (c) Air Force Engineering University HAUV [48].
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Figure 4. Representative single-layer multi-rotor HAUVs. (a) Miniature quadrotor HUAV [49], (b) Tilt-quadrotor HAUV [51], (c) TJ-FlyingFish [52], (d) Shanghai Maritime University [53], (e) Loon Copter II [54], (f) GTQ-Cormorant [55], (g) CRACUNS [56], (h) Nezha-F [57], (i) Nezha-IV [58], (j) Nezha-SeaDart [59], (k) WuKong [60], (l) Nezha-X [61].
Figure 4. Representative single-layer multi-rotor HAUVs. (a) Miniature quadrotor HUAV [49], (b) Tilt-quadrotor HAUV [51], (c) TJ-FlyingFish [52], (d) Shanghai Maritime University [53], (e) Loon Copter II [54], (f) GTQ-Cormorant [55], (g) CRACUNS [56], (h) Nezha-F [57], (i) Nezha-IV [58], (j) Nezha-SeaDart [59], (k) WuKong [60], (l) Nezha-X [61].
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Figure 5. Representative Multimodal HAUV. (a) Nezha I, (b) Nezha II, (c) Nezha III, (VTOL) (d) Nezha III (tail-sitting).
Figure 5. Representative Multimodal HAUV. (a) Nezha I, (b) Nezha II, (c) Nezha III, (VTOL) (d) Nezha III (tail-sitting).
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Figure 6. Typical commercial hyperspectral radiometer products. (a) RAMSES series, TRIOS (b) OCR series, Seabird (c) Microradiometer, Biospherical Instruments Inc.
Figure 6. Typical commercial hyperspectral radiometer products. (a) RAMSES series, TRIOS (b) OCR series, Seabird (c) Microradiometer, Biospherical Instruments Inc.
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Figure 7. Typical field platforms for AOPs measurement. (a) THOR (held upright) with LoCNESS and miniNESS (on deck) in front of the SeaWiFS Portable Laboratory [72] (b) OCR series, Seabird (https://www.seabird.com/ accessed on 10 September 2025) (c) Compact Optical Profiling system (C-OPS, www.biospherical.com accessed on 10 September 2025) (d) XRL with Ed and Lu geometries (www.biospherical.com accessed on 10 September 2025).
Figure 7. Typical field platforms for AOPs measurement. (a) THOR (held upright) with LoCNESS and miniNESS (on deck) in front of the SeaWiFS Portable Laboratory [72] (b) OCR series, Seabird (https://www.seabird.com/ accessed on 10 September 2025) (c) Compact Optical Profiling system (C-OPS, www.biospherical.com accessed on 10 September 2025) (d) XRL with Ed and Lu geometries (www.biospherical.com accessed on 10 September 2025).
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Figure 8. A feasible underwater light field observation system: (a) arm folds when operating underwater; (b) arm unfolds during aerial flight.
Figure 8. A feasible underwater light field observation system: (a) arm folds when operating underwater; (b) arm unfolds during aerial flight.
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Figure 9. Workflow diagram of amphibious optical observation systems for emergency monitoring.
Figure 9. Workflow diagram of amphibious optical observation systems for emergency monitoring.
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Table 1. Comparison of representative HAUV types by parameters.
Table 1. Comparison of representative HAUV types by parameters.
Type of HAUVTransition MechanismPayload CapacityUnderwater ManeuverabilityAerial EnduranceStability in Water EntryRepresentative Applications
Bio-inspiredPlunge-dive biomimeticLow (miniaturized)Moderate (limited control)ModerateSensitive to turbulenceSmall-scale monitoring proof-of-concept research
Fixed-wing (splash)Glide or tilt entryMediumLow (propellers are inefficient)High (long range)High risk of vibrationWide-area patrols rapid deployment
VTOL Multi-rotorVertical descent/ascentMedium–HighHigh (hover precise positioning)Short–ModerateSmooth controllableOptical profiling localized surveys
Multi-modal HAUVVTOL + gliding capabilityMediumHigh (gliding + hovering)Moderate–HighStable with buoyancy systemLong-duration surveillance adaptive missions
Table 3. Commercially available in situ IOP optical instruments.
Table 3. Commercially available in situ IOP optical instruments.
InstrumentDrones 09 00667 i001Drones 09 00667 i002Drones 09 00667 i003Drones 09 00667 i004
Spectral absorption and attenuation sensor (ac-s) ECO BB9ECO fluorometers and scattering sensorsRBR tridente
CompanyWET Labs, Inc., Philomath, OR, USAWET Labs, Inc., Philomath, OR, USAWET Labs, Inc., Philomath, OR, USARBR Ltd.,
Ottawa, ON, Canada
weight in air /water5.9 kg/0.8 kg3.1 kg/1.8 kg0.4 kg/0.21 kg0.4 kg/0.02 kg
observation parametersc(λ), b(λ), a(λ), bp(λ)Fluorescence,
bp(λ)
Fluorescence,
bp(λ)
Fluorescence,
bp(λ)
deployment platformsCTD rosettes, Float profiler, AUV, ROV, Buoy
Compatibility with HAUVsLimited—heavy and high power, suitable only for large HAUVsModerate—feasible for mid-size HAUVs with endurance capacityHigh—light weight, low power, suitable for small HAUVsHigh—excellent compatibility with miniaturized HAUVs
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Qi, H.; Hu, S.; Zhang, J.; Wu, G. Review of Hybrid Aerial Underwater Vehicle: Potential Applications in the Field of Underwater Marine Optics. Drones 2025, 9, 667. https://doi.org/10.3390/drones9100667

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Qi H, Hu S, Zhang J, Wu G. Review of Hybrid Aerial Underwater Vehicle: Potential Applications in the Field of Underwater Marine Optics. Drones. 2025; 9(10):667. https://doi.org/10.3390/drones9100667

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Qi, Hongyu, Shuibo Hu, Jiasheng Zhang, and Guofeng Wu. 2025. "Review of Hybrid Aerial Underwater Vehicle: Potential Applications in the Field of Underwater Marine Optics" Drones 9, no. 10: 667. https://doi.org/10.3390/drones9100667

APA Style

Qi, H., Hu, S., Zhang, J., & Wu, G. (2025). Review of Hybrid Aerial Underwater Vehicle: Potential Applications in the Field of Underwater Marine Optics. Drones, 9(10), 667. https://doi.org/10.3390/drones9100667

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