Search Results (62)

Maritime vision sensing can be applied to maritime unmanned systems to perform search and rescue (SAR) missions under complex marine environments, as multiple unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs) are able to conduct vision sensing through the air, the water-surface, and underwater. However, in these vision-based maritime SAR systems, collaboration between UAVs and USVs is a critical issue for successful SAR operations. To address this challenge, in this paper, we propose a long-endurance collaborative SAR scheme which exploits the complementary strengths of the maritime unmanned systems. In this scheme, a swarm of UAVs leverages a multi-agent reinforcement-learning (MARL) method and probability maps to perform cooperative first-phase search exploiting UAV’s high altitude and wide field of view of vision sensing. Then, multiple USVs conduct precise real-time second-phase operations by refining the probabilistic map. To deal with the energy constraints of UAVs and perform long-endurance collaborative SAR missions, a multi-USV charging scheduling method is proposed based on MARL to prolong the UAVs’ flight time. Through extensive simulations, the experimental results verified the effectiveness of the proposed scheme and long-endurance search capabilities. Full article

With the advancement of sixth-generation (6G) wireless communication technology, new demands have been placed on maritime communications. In maritime environments, factors such as evaporation ducts and sea waves significantly impact signal transmission. Moreover, in multi-user communication scenarios, interactions between different users introduce additional complexities. This paper proposes a novel channel model for maritime unmanned aerial vehicle (UAV) to multi-unmanned surface vehicle (USV) communications, which incorporates massive multiple-input–multiple-output (MIMO) antennas at both the transmitter (Tx) and receiver (Rx), while also accounting for the effects of evaporation ducts and sea waves on the channel. For the USV-single-user maritime model, the temporal auto-correlation function (ACF) and spatial cross-correlation function (CCF) are analyzed. For the UAV-to-multi-user channel model, key channel characteristics such as channel matrix collinearity (CMC) and channel capacity are examined. Finally, the accuracy and effectiveness of the proposed model are validated through a comparison between the measured and simulated data under a single-link environment. Meanwhile, a comparison between the CMC obtained from the proposed model and that derived from Ray-Tracing further verifies the model’s accuracy in multi-link environments. This model provides essential theoretical guidance for future 6G maritime communication systems. Full article

Accurate and efficient detection of floating waste is crucial for environmental protection and aquatic ecosystem preservation, yet remains challenging due to environmental interference and the prevalence of small targets. To address these limitations, we propose a Multi-scale Adaptive Real-time Detector (RTDETR-MARD) based on RT-DETR that introduces three key innovations for improved floating waste detection using unmanned surface vessels (USVs). First, our hierarchical multi-scale feature integration leverages the gather-and-distribute mechanism to enhance feature aggregation and cross-layer interaction. Second, we develop an advanced feature fusion module incorporating feature alignment, Information Fusion, information injection, and Scale Sequence Feature Fusion components to ensure precise spatial alignment and semantic consistency. Third, we implement the Wise-IoU loss function to optimize localization accuracy through high-quality anchor supervision. Extensive experiments demonstrate the framework’s effectiveness, achieving state-of-the-art performance of 86.6% mAP50 at 96.8 FPS on the FloW dataset and 49.2% mAP50 at 107.5 FPS on our custom water surface waste dataset. These results confirm RTDETR-MARD’s superior accuracy, real-time capability, and robustness across diverse environmental conditions, making it particularly suitable for practical deployment in ecological monitoring systems where both speed and precision are critical requirements. Full article

Unmanned Surface Vehicles (USVs) have emerged as vital tools in marine monitoring and management due to their high efficiency, low cost, and flexible deployment capabilities. This paper presents a systematic review focusing on four core areas of USV applications: communication networking, navigation, control, and data-driven operations. First, the characteristics and challenges of acoustic, electromagnetic, and optical communication methods for USV networking are analyzed, with an emphasis on the future trend toward multimodal communication integration. Second, a comprehensive review of global navigation, local navigation, cooperative navigation, and autonomous navigation technologies is provided, highlighting their applications and limitations in complex environments. Third, the evolution of USV control systems is examined, covering group control, distributed control, and adaptive control, with particular attention given to fault tolerance, delay compensation, and energy optimization. Finally, the application of USVs in data-driven marine tasks is summarized, including multi-sensor fusion, real-time perception, and autonomous decision-making mechanisms. This study aims to reveal the interaction and coordination mechanisms among communication, navigation, control, and data-driven operations from a system integration perspective, providing insights and guidance for the intelligent operations and comprehensive applications of USVs in marine environments. Full article

This paper mainly investigates the fault-tolerant consensus problem in heterogeneous multi-agent systems. Firstly, a control model of a leader–follower heterogeneous multi-agent system (HMAS) composed of multiple unmanned aerial vehicles (UAVs), multiple unmanned surface vehicles (USVs), and multiple unmanned underwater vehicles (UUVs) is established. Then, for the fault-tolerant control (FTC) consensus problem of heterogeneous systems under partial actuator failures and interruption failures, an optimal FTC protocol for heterogeneous multi-agent systems based on the control allocation algorithm is designed. The derived optimal FTC protocol is applied to the heterogeneous system. The asymptotic stability of the protocol is proved by the Lyapunov stability theory. Finally, the effectiveness of the control strategy is verified through simulation tests. Full article

To address the challenges of manual buoy inspection, this study enhances a previously proposed Unmanned Surface Vehicle (USV) inspection system by improving its navigation and obstacle avoidance capabilities using Proximal Policy Optimization (PPO). For improved usability, the entire system adopts a fully end-to-end design, with an angular deviation weighting mechanism for stable circular navigation, a novel image-based radar encoding technique for obstacle perception and a decoupled navigation and obstacle avoidance architecture that splits the complex task into three independently trained modules. Experiments validate that both navigation modules exhibit robustness and generalization capabilities, while the obstacle avoidance module partially achieves International Regulations for Preventing Collisions at Sea (COLREGs)-compliant maneuvers. Further tests in continuous multi-buoy inspection tasks confirm the architecture’s effectiveness in integrating these modules to complete the full task. Full article

For the design and verification of a motion control algorithm for unmanned surface vehicles, a simulation system is developed based on VRX and Simulink. Firstly, considering the effect of wind, a dynamic model of the USV with podded propellers is established. Secondly, combined with speed control, three control modes are considered, including yaw rate control, heading control, and path-following control, and speed, heading, yaw rate, and path guidance controllers are designed. Then, a real-time simulation system is developed based on the Virtual RobotX (VRX) environment and the Simulink ROS2 toolbox. Finally, motion control simulation experiments under three control modes and a path-following water tank experiment are carried out. The designed simulation system can simulate the motion of USVs and different environmental elements, such as wind, intuitively and realistically. In simulation experiments, the designed controllers can make the USV follow commands quickly and accurately under three control modes. In the water tank experiment, the USV could stably track the desired path with a relatively small tracking error. Therefore, the effectiveness of the simulation system is strongly confirmed through simulation experiments and the water tank experiment. The simulation system will be expanded in the future for more research on target recognition, path planning, and other aspects of USVs. Full article

Spherical buoys serve as water surface markers, and their location information can help unmanned surface vessels (USVs) identify navigation channel boundaries, avoid dangerous areas, and improve navigation accuracy. However, due to the presence of disturbances such as reflections, water obstruction, and changes in illumination for spherical buoys on the water surface, using binocular vision for positioning encounters difficulties in matching. To address this, this paper proposes a monocular vision-based localization method for spherical buoys using elliptical fitting. First, the edges of the spherical buoy are extracted through image preprocessing. Then, to address the issue of pseudo-edge points introduced by reflections that reduce the accuracy of elliptical fitting, a multi-step method for eliminating pseudo-edge points is proposed. This effectively filters out pseudo-edge points and obtains accurate elliptical parameters. Finally, based on these elliptical parameters, a monocular vision ranging model is established to solve the relative position between the USV and the buoy. The USV’s position from satellite observation is then fused with the relative position calculated using the method proposed in this paper to estimate the coordinates of the buoy in the geodetic coordinate system. Simulation experiments analyzed the impact of pixel noise, camera height, focal length, and rotation angle on localization accuracy. The results show that within a range of 40 m in width and 80 m in length, the coordinates calculated by this method have an average absolute error of less than 1.2 m; field experiments on actual ships show that the average absolute error remains stable within 2.57 m. This method addresses the positioning issues caused by disturbances such as reflections, water obstruction, and changes in illumination, achieving a positioning accuracy comparable to that of general satellite positioning. Full article

The cooperative patrol control of multiple unmanned surface vehicles (Multi-USVs) in dynamic aquatic environments presents significant challenges in global coverage efficiency and system robustness. The study proposes a cooperative patrol control algorithm for multiple unmanned surface vehicles (Multi-USVs) based on a hybrid embedded task state information model and reward reshaping techniques, addressing global coverage challenges in dynamic aquatic environments. By integrating patrol, collaboration, and obstacle information graphs, the algorithm generates kinematically feasible control actions in real time and optimizes the exploration-cooperation trade-off through a dense reward structure. Simulation results demonstrate that the algorithm achieves 99.75% coverage in a 1 km × 1 km task area, reducing completion time by 23% and 74% compared to anti-flocking and partition scanning algorithms, respectively, while maintaining collision rates between agents (CRBAA) and obstacles (CRBAO) below 0.15% and 0.5%. Compared to DDPG, SAC, and PPO frameworks, the proposed training framework (TFMUSV) achieves 28% higher rewards with 40% smaller fluctuations in later training stages. This study provides an efficient and reliable solution for autonomous monitoring and search-rescue missions in complex aquatic environments. Full article

In this study, a hybrid heading control framework for unmanned surface vehicles (USVs) is proposed, combining variable domain fuzzy Proportional–Integral–Derivative (VUF-PID) with an improved algorithmic Beetle Antennae Search–Particle Swarm Optimization–Simulated Annealing (BAS-PSO-SA) optimization to address the multi-objective control challenge. Key innovations include a self-tuning VUF mechanism that improves disturbance rejection by 42%, a weighted adaptive optimization strategy that reduces parameter tuning iterations by 37%, and an asymmetric learning factor that balances global exploration and local refinement. Benchmarks using Rastrigin, Griewank, and Sphere functions show superior convergence and 68% stability improvement. Ocean heading simulations of a 7.02 m unmanned surface vehicle (USV) using the Nomoto model show a 91.7% reduction in stabilization time, a 0.9% reduction in overshoot, and a 30% reduction in optimization iterations. The experimental validation under wind and wave disturbances shows that the heading deviation is less than 0.0392°, meeting the IMO MSC.1/Circ.1580 standard, and an 89.5% improvement in energy efficiency. Although the processing time is 12.7% longer compared to the GRO approach, this framework lays a solid foundation for ship autonomy systems, and future enhancements will focus on MPC-based time delay compensation and Field-Programmable Gate Array (FPGA) acceleration. Full article

Addressing the problem of inadequate environmental detection in the process of optimizing search for unmanned surface vehicles (USVs) by a heuristic algorithm, this paper proposes a comprehensive visual perception method that combines a lightweight convolutional neural network (CNN) with the USV’s real-time heading angle. This method employs a multi-feature input CNN with residual learning blocks, which takes both the current local environmental images and heading angle features as inputs to identify the complexity of the local environment with higher accuracy and a smaller load size. Meanwhile, human expertise is incorporated to classify labels through a majority voting system, thereby making the model’s perceptual classification more intuitive and allowing it to possess a human-like comprehensive perception ability compared to systems with classification methods with several parameters. Subsequently, this identification result can be used as feedback for the heuristic algorithm to optimize and plan the USV’s path. The simulation results indicate that the developed model achieves an 80% reduction in model size while maintaining an accuracy exceeding 90%. The proposed method significantly improves the environment recognition capability of the heuristic algorithm, enhances optimization search efficiency, and increases the overall performance of path planning by approximately 21%. Full article

For the guidance problem of trajectory tracking in multiple unmanned surface vehicles (USVs), a trajectory tracking guidance method with collision avoidance based on a novel guiding vector field is proposed. Firstly, within the framework of the virtual leader–follower method for formation control, a tracking error model for followers is developed based on the motion model of USVs. Secondly, considering the limitations of conventional trajectory tracking guidance methods in addressing various initial error conditions, a novel guiding vector field is developed for the design of the heading guidance law to enhance tracking performance. Then, a multi-USV collision avoidance strategy is proposed for formation navigation safety. The trigger conditions, actions and release conditions for collision avoidance are established in this strategy. USVs could avoid collision in time by following the commands outlined in the strategy, especially in complex situations where multiple USVs are simultaneously at risk of colliding with each other. And the theoretical proof is completed. Furthermore, the heading and velocity guidance laws are designed by combining the guidance vector field and the collision avoidance strategy. It is demonstrated that the tracking errors of the system are uniformly bounded based on Lyapunov stability theory. Finally, the effectiveness of the method is verified through simulation. Full article

Mobile edge computing is envisioned as a prospective technology for supporting time-sensitive and computation-intensive applications in marine vehicle systems. However, the offloading performance is highly impacted by the poor wireless channel. Recently, an Unmanned Aerial Vehicle (UAV) equipped with an Intelligent Reflecting Surface (IRS), i.e., UIRS, has drawn attention due to its capability to control wireless signals so as to improve the data rate. In this paper, we consider a multi-UIRS-assisted marine vehicle system where UIRSs are deployed to assist in the computation offloading of Unmanned Surface Vehicles (USVs). To improve energy efficiency, the optimization problem of the association relationships, computation resources of USVs, multi-UIRS phase shifts, and multi-UIRS trajectories is formulated. To solve the mixed-integer nonlinear programming problem, we decompose it into two layers and propose an integrated convex optimization and deep reinforcement learning algorithm to attain the near-optimal solution. Specifically, the inner layer solves the discrete variables by using the convex optimization based on Dinkelbach and relaxation methods, and the outer layer optimizes the continuous variables based on the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3). The numerical results demonstrate that the proposed algorithm can effectively improve the energy efficiency of the multi-UIRS-assisted marine vehicle system in comparison with the benchmarks. Full article

This study provides an overview of the literature on multi-unmanned surface vessel (multi-USV) systems, addressing the increasing attention on formation control of USVs due to their enhanced task execution ability, efficiency, and robustness in complex marine environments. Despite numerous studies on USVs covering fields, such as autonomous decision making, motion control, perception, and communication technologies, there is a significant lack of systematic literature review and bibliometric analysis specifically focused on a multi-USV system. This study aims to summarize advancements in multi-USV research, highlighting key aspects, including publication trends, influential scholars and papers, research hotspots, challenges, and future opportunities. By reviewing the current state of multi-USV research, this study contributes to the field as a beneficial reference for researchers, practitioners, and policymakers. It will not only highlight the progress made so far but also shed light on the gap that needs to be addressed to advance the field. Full article

Safety and efficiency are important when Unmanned Surface Vehicles (USVs) pass through narrow waters in complex marine environments. This paper considers the issue of path planning for USVs passing through narrow waterways. We propose a distributed optimization algorithm based on a polymorphic network architecture, which maintains connectivity and avoids collisions between USVs while planning optimal paths. Firstly, the initial path through the narrow waterway is planned for each USV using the narrow water standard route method, and then the interpolating spline method is used to determine its corresponding functional form and rewrite the function as a local cost function for the USV. Secondly, a polymorphic network architecture and a distributed optimization algorithm were designed for multi-USVs to maintain connectivity and avoid collisions between USVs, and to optimize the initial paths of the multi-USV system. The effectiveness of the algorithm is demonstrated by Lyapunov stability analysis. Finally, Lingshui Harbor of Dalian Maritime University and a curved narrow waterway were selected for the simulation experiments, and the results demonstrate that the paths planned by multiple USVs were optimal and collision-free, with velocities achieving consistency within a finite time. Full article