A hybrid aerial underwater vehicle (HAUV) that could operate in the air and underwater might provide tremendous potential for ocean monitoring and search and rescue as well as underwater exploration. Differences between the aerial and underwater environments, along with common disturbances in wind or oceanic currents, present key challenges when designing a robust global controller. This paper presents a nonlinear dynamic controller, otherwise known as the adaptive dynamic surface control (ADSC) scheme, which effectively deals with the challenges aroused by the nonlinearities, uncertainties, and time-varying parameters of the system. First, the mathematical model of the HAUV is developed by means of the Newton–Euler formalism, highlighting the influence of the environment change on the vehicle dynamics. Second, the variations of added mass and damping during the water/air transition are estimated. Finally, the ADSC scheme is used to control and provided robust transition between distinct mediums for the vehicle in simulations, compared with the gain-scheduled proportional–integral–derivative scheme. The simulation results validate the good tracking performance and strong robustness of the presented scheme.

The distinct design concepts of the vehicles operating in air and water is one of the tremendous challenges that constrain the development of the hybrid aerial underwater vehicle (HAUV). This incompatibility consequently results in the enlarging volume and weight of the existing prototypes, as well as the unmatched maneuvering characteristics in both domains. This letter presented a novel miniaturized and lightweight HAUV, “Nezha-mini,” which weighs 953 g and is only A4-scaled. Besides, the low cost and high modularity allow the convenient repair and remanufacturing. Nezha-mini reconciles the complete multi-domain maneuverability within 50 m aerially and 6 m underwater whilst sufficing for the rapid and stable cross-domain locomotion, which benefits from the selection and unique layout of the propulsion system, as well as our proposed multi-modal control strategy and the cross-domain triggering mechanism. The results of the field experiments are in good agreement with the dynamics simulation, demonstrating the performance of multi-domain locomotion in real environments. The preliminary exploration in this letter provides a referential solution for the miniaturization of the highly maneuverable HAUVs for practical applications and creates a feasible platform for the future clustering and networking of HAUVs.

This letter introduces a small hybrid aerial underwater vehicle (HAUV), which we named Nezha-F, that can fly in the air, perform vertical profiling underwater, and vertically take off and land from both the water surface and ground. A foldable and self-deployable arm mechanism linked to and driven by a piston variable buoyancy system (PVBS) is proposed to reduce the excessive underwater drag caused by aerial structures. By having a compact size and successfully balanced aerial and underwater performance without adding excessive actuators, this design provides a feasible idea for the miniaturization of amphibious floats. The dynamic characteristics of the small PVBS are linear fitted, and modeled. The originally nonlinear actuator performance is linearized by the post-fitting mapping. Asymmetric dead zones of the actuator are removed by adding compensation to the algorithm. During a 10-day field test, the vehicle showed good aerial performance and underwater control effect. Several full mission cycle tests proved the vehicle's ability in semi-autonomous operation and robust domain crossing and verified the vehicle's endurance during each mission stage.

This article proposes a disturbance observer-based nonlinear control strategy for the accurate takeoff and landing control of a novel hybrid aerial underwater vehicle, Nezha III, subjected to wave and wind. The approach consists of the dynamic surface controller (DSC) and the nonlinear disturbance observers (NDOs). The problem is first modeled with full consideration of diverse external forces, including the capsizing buoyant moment, the added mass effect, and wave and wind loads. The DSC forms the base of the controller and benefits the tracking behavior by handling the nonlinearity of the system. Meanwhile, the integrated NDOs enhance the robustness of the closed-loop system by estimating the unmeasurable external forces. The proposed method is proved theoretically to stabilize the vehicle when it tracks the reference trajectory across different media in the presence of environmental disturbances. Finally, the proposed controller is tested numerically by challenging it under the wind and wave disturbances. The results show the controller makes Nezha III achieve successful takeoff and landing on the disturbed water’s surface in spite of the hazardous environment, which strongly evidence the outstanding performance of the proposed method.

This research presents a novel sample-based path planning algorithm for adaptive sampling. The goal is to find a near-optimal path for unmanned marine vehicles (UMVs) that maximizes information gathering over a scientific interest area, while satisfying constraints on collision avoidance and pre-specified mission time. The proposed rapidly-exploring adaptive sampling tree star (RAST*) algorithm combines inspirations from rapidly-exploring random tree star (RRT*) with a tournament selection method and informative heuristics to achieve efficient searching of informative data in continuous space. Results of numerical experiments and proof-of-concept field experiments demonstrate the effectiveness and superiority of the proposed RAST* over rapidly-exploring random sampling tree star (RRST*), rapidly-exploring adaptive sampling tree (RAST), and particle swarm optimization (PSO).