Search Results (77)

Vertical docking of the autonomous underwater shuttle (AUS) for deep-sea data relay relies heavily on ultra-short baseline (USBL) acoustic positioning, whose measurements can be intermittently unavailable and contaminated by outliers in complex underwater environments. This paper proposes a neural network-enhanced robust navigation framework to improve AUS navigation reliability during acoustically guided vertical docking under USBL outages. First, a model-aided batch maximum a posteriori trajectory estimation method (MA-BMAP) is developed to generate learning quality supervision under sensor-limited conditions. Based on the estimated trajectories, a long short-term memory (LSTM)-based horizontal velocity predictor is integrated into a robust fusion filter with online ocean current estimation, enabling stable state estimation during USBL outages and robust rejection of abnormal USBL measurements. The proposed framework is validated through simulations and field trials in lake and sea environments. In sea trials, during two representative 200 s USBL outage intervals, the end-of-window horizontal position errors are 7.86 m and 4.14 m, respectively, corresponding to AUS-to-docking station distances of 244 m and 51 m. In addition, the introduced USBL outliers are successfully detected and rejected. The results indicate that the proposed method enables accurate and stable navigation during USBL unavailability and rapid recovery once USBL measurements resume, demonstrating its practicality for vertical docking missions. Full article

Underwater wireless power transfer (UWPT) enables long-term deep-sea floor exploration by providing contactless energy replenishment for autonomous underwater vehicles (AUVs). However, conventional single-transmitter systems suffer reduced coupling and efficiency caused by high-loss underwater dielectrics and docking-induced perturbations. We propose a parallel-resonant dual-transmitter configuration based on the parity–time (PT) symmetric gain–loss-balanced modal framework. The proposed dual-transmitter single-receiver (DTSR) system forms a stronger and more symmetric field in the receiver than the single-transmitter baseline, counteracting the high-loss dielectric and improving the misalignment tolerance. According to the PT symmetry coupled-mode theory, we analyze how the quality factor and coupling strength determine the admissible PT-unbroken operating region over the docking-induced coupling range. An experimental prototype validates the analysis by comparing operating frequency and efficiency between DTSR and the single-transmitter baseline under distance (4.8–13.5 cm) and load (2.0–4.3 kΩ) variations. The results show that DTSR increases the critical coupling distance by 20–30% and reduces efficiency sensitivity to distance and load variations. These results suggest that the system can provide more robust and stable UWPT for AUV recharging under high-loss dielectric and perturbation, conducive to practically implementing AUV recharging in deep-sea operations. Full article

This paper addresses the multi-phase homing and docking missions of over-actuated autonomous underwater vehicles (AUVs), where switching among forward cruising, reverse braking, and hovering can induce actuator saturation, rate limit violations, and undesirable transients. We propose a unified framework that couples supervisory mode management with mode-driven constrained control allocation solved by a warm-started sequential quadratic programming (SQP) routine. The controllable wrench is modeled by a mode-dependent differentiable map constructed from the actuator models, and the allocator enforces amplitude bounds and per-cycle increment limits while trading off wrench tracking and actuator usage through mode-scheduled weights. To mitigate switching transients, a continuous transition factor is introduced to interpolate the desired wrench and dominant cost weights, and an integrator alignment reset is applied at switching instants to keep the outer-loop proportional–integral–derivative (PID) output continuous. The allocator is further warm-started by projecting the previous solution onto the post-switch constraint box. The framework is integrated into the Mission-Oriented Operating Suite–Interval Programming (MOOS-IvP) autonomy middleware with adaptive line-of-sight (ALOS) guidance and adaptive PID motion control and is validated on the TS-100 AUV in water tank experiments. Comparative results against a PID-only baseline without control allocation and a variant without bumpless switching show reduced roll transients during the reverse-to-hover transition and improved hover-mode depth station keeping while maintaining feasible actuator commands under constraints. Full article

Underwater wireless power transfer (UWPT) technology can improve the endurance of unmanned underwater vehicles (UUVs). The stability and efficiency of UWPT depend on the success rate of UUV docking. A novel detection model, TFDF-YOLO, is proposed for dynamic position identification of UUV docking. First, a spatial–frequency decoupling (SFD) module is proposed by using Fourier-based degradation cues to guide Top-K proxy attention to boost blurred edge extraction capability. A relevance-difference fusion (RD-Fusion) strategy is improved by a global channel attention mechanism to realize multi-scale feature recognition. Furthermore, a new adaptive loss function (U-CIoU) is developed to suppress illumination bias and anchor inflation. Results on a reliable multi-source dataset demonstrate that the proposed model achieves 91.5% accuracy and 92.7% mAP@0.5. This work could enhance the success rate and reliability of UWPT. It shows potential for broader underwater applications, including deep-sea docking and multi-AUV cooperative systems. Full article

Accurate pose estimation is crucial for reliable docking and recovery of Autonomous Underwater Vehicles (AUVs). Traditional visual-based pose estimation methods face inherent challenges: monocular methods often struggle with depth inference, and conventional Perspective-n-Point (PnP) algorithms exhibit accuracy degradation at large viewing angles and limited noise resistance, while binocular systems involve higher computational complexity. This paper proposes a two-stage algorithm that combines iterative PnP initialization with binocular constraint optimization. By using iterative PnP to establish reliable initial estimates, the approach avoids convergence difficulties of direct binocular optimization, while the subsequent binocular refinement leverages stereo geometric constraints to enhance accuracy. Comprehensive evaluation through simulation, land-based experiments, and underwater validation demonstrates consistent performance improvements over conventional geometric methods. In simulation experiments across $-60°$ to $60°$ yaw angles, the method achieves 93.2% and 28.6% improvements in translation and rotation accuracy respectively compared to iterative PnP. Land-based validation confirms 32.7% average rotation error reduction, while underwater experiments demonstrate 76.5% average distance error reduction under real optical conditions including refraction and light attenuation. The method maintains real-time processing capability (2.16 ms per frame), offering a practical solution for AUV pose estimation in docking applications. Full article

To meet the design and evaluation requirements of underwater vision-based docking localization, a Webots-based simulation platform for Autonomous Underwater Vehicle (AUV) visual docking localization was designed and implemented to address the high cost of real sea trials, uncontrollable operating conditions, and the difficulty of systematically covering extreme scenarios. An end-to-end simulation of the docking localization pipeline was provided. Visual components—including fiducial markers, underwater illumination and imaging, and occlusion—were modeled in relatively fine detail, while non-vision-dominant factors such as propulsion and hydrodynamics were treated with approximate models to balance visual realism and simulation efficiency. The platform supported multiple types of visual markers, parameterized configuration of underwater lighting and turbidity, and the generation of diverse occlusion scenarios, enabling unified integration and benchmarking of docking localization algorithms. The results showed that the platform offered tunable scene parameters, repeatable conditions, and broad algorithm compatibility, and it effectively revealed performance differences across algorithms for complex combinations of illumination, turbidity, and occlusion. These capabilities reduced the risk and cost of real underwater docking experiments and supported faster iterative improvement of vision-based localization methods. Full article

This study tackles real-time state estimation for autonomous underwater vehicle (AUV)–mobile docking station (MDS) cooperation over low-bandwidth, high-latency, jitter-dominated acoustic links, with the goal of turning delayed/out-of-sequence measurements (OOSM) into consistent and informative constraints without sacrificing online operation. We propose an integrated scheme centered on a delay-compensated extended Kalman filter (DC-EKF): a ring buffer enables backward updates and forward replay so that OOSM are absorbed strictly at their physical timestamps; a data-driven delay threshold is learned from “effective information gain” combined with normalized estimation error squared (NEES) filtering; and dynamic confidence, derived from innovation statistics, delay, and signal-to-noise ratio (SNR) proxies, scales the measurement noise to adapt fusion weights. Simulations show the learned delay threshold converges to about 6.4 s (final 6.35 s), error spikes are suppressed, and the overall position root-mean-square error (RMSE) is 5.751 m; across the full data stream, 1067 station measurements were accepted and 30 rejected, and the fusion weights shifted smoothly from inertial measurement unit (IMU)-dominant to station-dominant (≈0.16/0.84) over time. On this basis, a cooperative augmented EKF (Co-Aug-EKF) is added as a lightweight upper layer for unified-frame cooperative estimation, further improving relative consistency. The results indicate that the framework reliably maps delayed acoustic measurements into closed-loop useful information, significantly enhancing estimator stability and docking readiness, while remaining practical to deploy and readily extensible. Full article

Underwater optical docking is essential for enabling autonomous underwater vehicles (AUVs) to maintain long-duration operations through standardized energy replenishment and data exchange. However, existing optical docking guidance still faces challenges including discontinuous guidance space, fluctuating beacon visibility, and limited real-time feasibility on resource-constrained AUV platforms. This study proposes a three-layer underwater optical guidance framework designed to enhance both stability and deployment feasibility. First, a multi-dimensional beacon configuration is developed to provide stage-based optical guidance, supported by a spatial simulation tool that evaluates beacon placement and effective detection regions. Second, an adaptive spatiotemporal guidance algorithm is introduced, integrating Kalman-based prediction and correction mechanisms to maintain consistent beacon tracking under dynamic underwater conditions. Third, a lightweight optical beacon detection model is implemented to reduce computational cost while preserving sufficient detection accuracy for real-time onboard processing. Pool and lake experiments demonstrate that the proposed framework achieves continuous optical guidance over a range of 0–35 m, significantly improving guidance stability and perception continuity compared with conventional approaches. Full article

As a new kind of large observation platform, the three-anchor buoy system can effectively realize multifunctional ocean observation, e.g., ocean profiling and autonomous underwater vehicle docking. In order to understand effects of different anchor chain arrangements on the motion response of the three-anchor buoy system under the coupling effect of wind, wave, and current loads, a hydrodynamic model of the buoy system was developed. Wave-period-dependent characteristics of added mass, radiation damping, and the motion response amplitude operator (RAO) were analyzed to derive their response curves; the effects of adding additional viscous damping on RAO performance were investigated. Subsequently, frequency domain and time domain analyses were conducted on five three-anchor buoy systems with distinct anchor chain arrangements to investigate the variation patterns of 6-DOF motion response amplitudes, top-chain tension characteristics, and submarine anchor chain length alterations under combined wind, wave, and current loading conditions. The results show that under the same environmental load, when the three anchor chains are evenly distributed at 120°, the 6-DOF motion response amplitude of the buoy system is the smallest, the top-chain tension and the submarine anchor chain length are more in line with the design requirements, and the comprehensive performance is better. Full article

This paper presents a Gaussian Process (GP)-based Funnel Model Predictive Control (MPC) for docking control of unmanned underwater vehicles (UUVs). The control method employs a Gaussian Process regression to learn the residual dynamics, which compensates for the unmodeled dynamics to improve prediction accuracy. Furthermore, a distance-adaptive performance funnel is designed to satisfy the field of view (FOV) constraints of sensors during the terminal guidance phase. The funnel imposes time-varying constraints on the UUV to ensure that the docking station remains observable. This funnel constraint is integrated into the cost function of the MPC, which systematically enforces safety without the computational complexity of traditional invariant sets. Comparative simulations validate the framework’s reliability under external disturbances, demonstrating superior tracking precision against conventional MPC benchmarks. Full article

This paper presents a robust trajectory-tracking control framework for underwater vehicles operating in a relative coordinate system. Unlike conventional methods that define trajectories in the world frame, the proposed approach formulates the control problem directly in a moving reference frame, enabling accurate motion control with respect to dynamic and drifting objects affected by environmental disturbances such as ocean currents and waves. This relative-space formulation is particularly advantageous for tasks including diver guidance, floating-object inspection, and docking, where the reference itself is nonstationary. A coordinate transformation is introduced to consistently express the vehicle dynamics in the relative frame. Based on the transformed dynamics, a Time Delay Control (TDC) law is applied to estimate unmodeled dynamics and external disturbances without requiring precise system parameters. Theoretical stability analysis shows that the stability condition of the proposed controller is consistent with that of conventional TDC, allowing similar gain-tuning procedures. Simulation results demonstrate that the proposed controller achieves robust and smooth trajectory tracking even when the reference frame undergoes motion induced by ocean currents. Full article

Due to the limited and fixed field of view of the onboard camera, the guiding beacons gradually drift out of sight as the AUV approaches the docking station, resulting in unreliable positioning and intermittent data. This paper proposes an underwater autonomous docking visual localization method based on a cage-type dual-layer guiding light array. To address the gradual loss of beacon visibility during AUV approach, a rationally designed localization scheme employing a cage-type, dual-layer guiding light array is presented. A dual-layer light array localization algorithm is introduced to accommodate varying beacon appearances at different docking stages by dynamically distinguishing between front and rear guiding light arrays. Following layer-wise separation of guiding lights, a robust tag-matching framework is constructed for each layer. Particle swarm optimization (PSO) is employed for high-precision initial tag matching, and a filtering strategy based on distance and angular ratio consistency eliminates unreliable matches. Under extreme conditions with three missing lights or two spurious beacons, the method achieves 90.3% and 99.6% matching success rates, respectively. After applying filtering strategy, error correction using backtracking extended Kalman filter (BTEKF) brings matching success rate to 99.9%. Simulations and underwater experiments demonstrate stable and robust tag matching across all docking phases, with average detection time of 0.112 s, even when handling dual-layer arrays. The proposed method achieves continuous visual guidance-based docking for autonomous AUV recovery. Full article

This study addresses autonomous underwater vehicle (UUV) recovery onto dynamic docking stations by proposing a fork-column recovery control system with a segmented docking strategy (long-distance approach + guided descent). To enhance model fidelity, transmission lag of actuators is captured by a specified transfer function, and nonlinear dynamics are characterized as an improved quasi-linear parameter-varying (QLPV) model. An adaptive variable–prediction–step mechanism was designed to accommodate different phases of acoustic–optical guided recovery. A model predictive controller (MPC) was developed based on an improved dynamic model to effectively handle complex constraints during the recovery process. Simulation and physical experiments demonstrated that the proposed system significantly reduces errors, among which the control accuracy (tracking error under disturbance < 0.3 m) and docking success rate (>95%) are notably superior to traditional methods, providing a reliable solution for the dynamic recovery of unmanned underwater vehicles (UUVs). Full article

Inspired by the free swing of coral tentacles driven by water currents to actively repel microbial attachment, we have identified a unique physical anti-fouling strategy: coral “swinging effect” anti-fouling. Taking the fleshy soft coral (Sarcophyton trocheliophorum) as an example, its surface is covered with numerous soft tentacles. These coral tentacles utilize the force of water current fluctuations to freely sway, resembling a “feather duster” waving to repel microorganisms attempting to settle and establish themselves. Based on this characteristic, this study delves into the living habits of corals, observing the expansion and contraction cycles of their tentacles. Simultaneously, simulations of the anti-fouling performance of coral tentacles were conducted. It demonstrates that the “swinging effect” of the tentacles can effectively prevent the attachment of fouling organisms. Furthermore, this study uses S. trocheliophorum as a biomimetic prototype to design and prepare an artificial coral-mimic substrate (ACMS). It employs the common marine Gram-negative bacterium Paracoccus pantotrophus as a microbial sample to test anti-fouling performance in both pure static water environments and low-flow water environments. The results showed that the 13 mm-long ACMS could bend and overlap the surface of the rear tentacles to the greatest extent under the unidirectional scouring action of low-speed water flow (3.5 m/s), forming an anti-fouling protective layer. Additionally, the “swinging effect” phenomenon generated by the tentacles under water flow scouring demonstrated excellent anti-fouling effects. This study not only provides further evidence for research on coral antifouling performance but also offers new concepts and ideas for antifouling strategies in low-flow water environments, such as stationary ships in ports and underwater infrastructure facilities at docks. Full article