Surface Vehicle Research Articles

Evolution of Unmanned Surface Vehicle Path Planning: A Comprehensive Review of Basic, Responsive, and Advanced Strategic Pathfinders

Unmanned Surface Vehicles (USVs) are rapidly becoming mission-indispensable for a variety of naval operations, from search and rescue to environmental monitoring and surveillance. Path planning lies at the heart of the operational effectiveness of USVs, since it represents the key technology required to enable the vehicle to transit the unpredictable dynamics of the marine environment in an efficient and safe way. The paper develops a critical review of the most recent advances in USV path planning and a novel classification of algorithms according to operational complexity: Basic Pathfinders, Responsive Pathfinders, and Advanced Strategic Pathfinders. Each category can adapt to different requirements, from environmental predictability to the desired degree of human intervention, and from stable and controlled environments to highly dynamic and unpredictable conditions. The review includes current methodologies and points out the state-of-the-art algorithmic approaches in their experimental validations and real-time applications. Particular attention is paid to the description of experimental setups and navigational scenarios showing the realistic impact of these technologies. Moreover, this paper goes through the key, open challenges in the field and hints at the research direction to leverage in order to enhance the robustness and adaptability of path planning algorithms. This paper, by offering a critical analysis of the current state-of-the-art, lays down the foundation of future USV path planning algorithms.

Software Architecture Design of ASV Rybitwa: Development of an Autonomous Surface Vehicle for Dynamic Navigation and Task Execution

Abstract This paper introduces the software design of an Autonomous Surface Vehicle (ASV) named ASV Rybitwa. It was designed as an easily transportable platform capable of autonomous navigation and performing tasks during the RoboBoat 2024 competition, with emphasis on its modularity, generality and extendibility. The paper presents a software architecture for a small autonomous surface vehicle using novel tools that provide easy system integration and expansion. To meet such requirements, a generic control box connecting an autopilot (PX4) and a onboard computer (NVIDIA Jetson Nano) was developed so as to host the Robot Operating System 2 (ROS2) and to interact with sensors and actuators. Computer vision from three Oak-D cameras, equipped with AI algorithm support (YOLOv8), was used for navigation and obstacle avoidance. The decision-making system was designed using behavioural trees and computer vision, allowing the vehicle’s capabilities to be adapted to the needs of the current tasks and mission. In addition, an Omni X propulsion system was proposed, providing full holonomy and enhancing dynamic positioning and navigation capabilities in complex navigational conditions. In addition this paper describes lessons learned from ASV Rybitwa’s real-world testing during the aforementioned competition.

A Potential Field-Based Model Predictive Target Following Controller for Underactuated Unmanned Surface Vehicles

A Potential Field-Based Model Predictive Target Following Controller for Underactuated Unmanned Surface Vehicles

Time-Varying Formation Control of Autonomous Surface Vehicles Based on Affine Observer

Time-Varying Formation Control of Autonomous Surface Vehicles Based on Affine Observer

Improved Localization of Unmanned Underwater Vehicle via Cooperative Navigation of Unmanned Surface Vehicle Equipped with Ultrashort Baseline

Improved Localization of Unmanned Underwater Vehicle via Cooperative Navigation of Unmanned Surface Vehicle Equipped with Ultrashort Baseline

Quantized-States-Based Fuzzy Adaptive Course Tracking Control of an Unmanned Surface Vehicle with Input and State Quantization

Quantized-States-Based Fuzzy Adaptive Course Tracking Control of an Unmanned Surface Vehicle with Input and State Quantization

An iterative learning-based integrated motion planning and control method for autonomous patrolling of unmanned surface vehicles

Abstract The minimization of maritime patrol durations and the optimization of patrol trajectories are still a prevailing challenge for autonomous navigation of unmanned surface vehicles (USVs). In this paper, we propose an integrated trajectory planning and control method to achieve time-optimal autonomous patrol of USVs by a data-efficient iterative learning-based predictive control algorithm. We build the optimization problem of the algorithm by introducing a local cost and a local safe constraint set for closed-loop efficient data-driven learning. To guarantee recursive feasibility, stability and convergence properties of the optimization algorithm at each iteration, the local cost and the local constraint set are designed and update iteratively using the historical vehicle states at previous iterations as a dataset. Different from traditional optimization methods, the proposed method does not require a reference path. The cost function of the optimization method decreases monotonically and converge to obtain a time-optimal control law for trajectory planning and tracking of USVs only after several iterations. The proposed approach is validated on the robotic operation system in typical maritime patrol scenarios. The results show that the proposed method implement a 5% reduction of patrol time, fewer lateral track errors, and smoother trajectories compared to the traditional MPC algorithm under water flow conditions. In addition, Enhancements in patrol operation efficiency of USVs are achieved by the algorithm, even under the constraints of varied patrol paths, attesting to its versatility.

Local Path Planning of Unmanned Surface Vehicles’ Formation Based on Vector Field and Flow Field Traction

Local Path Planning of Unmanned Surface Vehicles’ Formation Based on Vector Field and Flow Field Traction

Distributed deadband event-triggered observer-based containment control for unmanned surface vehicles with channel fading

This article investigates the distributed deadband event-triggered containment control problem for multiple underactuated surface vehicles (USV) systems whose communication networks are subject to channel fading. The first distributed deadband event-triggered observer (DDETO) was proposed to observe the target positions of the followers in the convex hulls formed by the leaders. It also manages the internal communication between the followers in the presence of channel fading. In addition, the deadband event-triggered mechanism (DETM) in DDETO guarantees a strictly positive minimum inter-event times (MIET), which can be accurately calculated and adjusted according to the design parameters. Afterward, an adaptive controller is designed by backstepping based on the desired position information observed by DDETO. It is worth noting that the containment control scheme proposed in this paper is based on relative position measurement only, which reduces the amount of information transfer compared to transmitting position and velocity information when wireless signals are fading in the channel, improves the control accuracy, and also reduces the system’s requirements for sensors. Theoretical analysis leads to the conclusion that the error signals are uniformly ultimately bounded (UUB). Finally, the effectiveness of the control scheme is verified by numerical simulation.

GNSS/INS integrated navigation algorithm framework based on cascade vector tracking algorithm for USV

The safety of Unmanned Surface Vehicle during the autonomous phase of navigation relies heavily on the onboard navigation equipment. However, in the face of changing and diverse navigation environments, global satellite navigation systems utilizing radio communication often face signal occlusions. This significantly reduces the positioning accuracy of navigation systems. To ensure the navigation accuracy of vehicles in various harsh environments, a Global Navigation Satellite Systems and Inertial Navigation System (GNSS/INS) integrated navigation system structure based on cascaded vector-tracking loop is proposed in this paper. The integrated navigation scheme not only improved the positioning accuracy of the navigation system but also effectively improved the robustness of the system. Compared with the traditional scalar-tracking loop and vector-tracking loop methods, it exhibits better performance. The experimental results show that the proposed method can reduce the horizontal position positioning error by 73.7% compared with the traditional vector-tracking loop method in the case of signal occlusion. Simultaneously, it can continuously output reliable and high-precision positioning information in the case of serious signal occlusion. The integrated navigation scheme proposed in this paper can be used as a research direction for the development of Unmanned Surface Vehicle navigation applications and provides solutions for the development of related navigation systems.

Station-keeping strategy in emergency mode for wave gliders considering power shortages

The wave glider (WG) is an autonom surface vehicle (ASV) that is driven only by waves without propellers, and it maintains the power consumption of the control system and various payloads through solar power generation. To cope with the power shortages caused by extreme weather and sudden failures, a station-keeping strategy in emergency mode for WGs is proposed in this paper, so that the WG can remain in the current area with extremely low power consumption. More specifically, according to the power consumption mechanism of the WG, a partition control method is designed to set different operating modes in different areas. Also, an event-triggered (ET) motion control algorithm is proposed to reduce the execution rate of the rudder, which introduces adjustment factors to dynamically adjust the trigger threshold to further cut down rudder steering power consumption. Additionally, an online heading prediction system is developed to predict the submerged glider heading (SGH) of the WG through the float heading (FH) when the rudder management system shuts down. Through simulation and experimental analysis, the strategy in emergency mode can achieve positioning control with extremely low power consumption.

IRS-assisted UAV wireless powered communication network for sustainable federated learning

Intelligent reflective surface (IRS) and unmanned aerial vehicle (UAV) communication are indispensable potential technologies in the future sixth-generation mobile communication technology (6 G). Utilizing the high beamforming gain of IRS and the high mobility of UAV can achieve ubiquitous network coverage and ensure a high-quality communication environment. Wireless Powered Communication Network (WPCN) is an emerging green communication technology network that converts received radio frequency (RF) signals into electrical energy to power Federated Learning (FL) users. FL users perform local computing and model transmission through the collected energy, ensuring the sustainability of FL. In order to solve the problems of complex communication environment, privacy protection, and energy constraints on terminal devices, we design an FL system based on an IRS-assisted UAV wireless power communication network, which minimizes the UAV transmission energy by jointly optimizing UAV location, IRS phase shift, and resource allocation strategies. We use a low-complexity iterative algorithm to solve this complex non-convex problem. The simulation results show that the performance of the proposed algorithm is obviously better than that of other benchmark schemes, indicating that joint optimization plays an essential role in improving the performance of the system.

Cubature Kalman Hybrid Consensus Filter for Collaborative Localization of Unmanned Surface Vehicle Cluster with Random Measurement Delay.

This paper addresses the collaborative localization problem for unmanned surface vehicle (USV) clusters with random measurement delays. We propose a Cubature Kalman Hybrid Consensus Filter (CKHCF) based on the cubature Kalman filter (CKF) for widely distributed USV clusters lacking global communication capabilities. In this approach, each USV exchanges two pairs of information with all its neighbors and recalculates the received localization data based on distance and relative angle measurements. The recalculated information is then fused with the locally filtered data and updated to obtain localization information based on global measurements. To mitigate the impact of random measurement delays, we employ one-step prediction to compensate for delayed measurements. We present the derivation of the CKHCF algorithm and prove its consistency and boundedness using mathematical induction. Finally, we validate the effectiveness of the proposed algorithm through simulation experiments.

Uncrewed surface vehicles (USVs) as platforms for fisheries and plankton acoustics

Abstract Uncrewed surface vehicles (USVs) equipped with echosounders have the potential to replace or enhance acoustic observations from conventional research vessels (RVs), increase spatial and temporal coverage, and reduce cost and carbon emission. We discuss the objectives, system requirements, infrastructure, and regulations for using USVs with echosounders to conduct ecological experiments, acoustic-trawl surveys, and long-term monitoring. We present four example applications of USVs with lengths <8 m, and highlight some advantages and disadvantages relative to RV-based data acquisitions. Sail-driven USVs operate continuously for months and are more mature than motorized USVs, but they are slower. To maintain the pace of an RV, multiple sail-powered USVs sample in coordination. In comparison, motorized USVs can travel as fast as RVs and therefore may facilitate a combined survey, interleaving USV and RV transects, with RV-based biological sampling. Important considerations for all USVs include platform design, noise and transducer motion mitigation, communications and operations infrastructure, onboard data processing, biological sampling approach, and legal requirements. This technology is evolving and applied in multiple disciplines, but further development and institutional commitment are needed to allow USVs equipped with echosounders to become ubiquitous and useful components of a worldwide network of autonomous ocean observation platforms.

"Robust Adaptive Path Following Controllers for Autonomous Surface Vehicles with Unknown Disturbances"

"Robust Adaptive Path Following Controllers for Autonomous Surface Vehicles with Unknown Disturbances"

Distributed-observer-based adaptive fault tolerant formation maneuver for autonomous surface vehicles under stochastic cyber-attack

This paper investigates the distributed adaptive fault-tolerant formation maneuver control strategy for multiple autonomous surface vehicles (ASVs) systems subject to stochastic cyber-attack and actuator failures. Existing works have provided solutions against continuous attacks on communication channels while ignoring the increasingly prevalent intermittent attacks. Compared to the former, the latter are more challenging to detect, having been insufficiently described and addressed. Motivated by this observation, this article is concerned with the stochastic intermittent injection attacks, which are modeled as stochastic impulsive sequences, characterized by stochastic injection instant and intensity, leading to unpredictable changes in the state information transmitted by the neighbors. Taking this dilemma into consideration, a novel distributed observer is proposed, capable of effectively observing the target formation even in the presence of stochastic intermittent injection attacks. Meanwhile, a large feedback gain is incorporated into the observer to reduce the impact of attacks on system stability. A linear sliding manifold, together with the adaptive algorithm, is utilized to construct a fault tolerant control architecture for each follower ASV without employing model parameters which can confront the embarrassing scenario of actuator failures. Eventually, theoretical deduction and numerical simulations are conducted to confirm the feasibility of the proposed collaborative control scheme.

Analysis and optimization of self-propelled performance of wave-driven vehicle hydrofoil under high sea-level condition

The wave-driven vehicle is a surface vehicle powered by capturing wave energy, which is required to face harsh sea conditions when performing tasks in parts of the ocean. However, wave-driven vehicles are usually small in size, and their seakeeping and speed are generally poor in high sea conditions. Wave driven vehicles are usually equipped with rigid connected hydrofoils to capture wave energy, which can provide power for wave driven vehicles and enhance seakeeping. Aiming at the long-term survival and operation requirements of wave-driven vehicle under high sea conditions, this paper studies the effect of high sea conditions launching wing on the self- propelled performance of wave-driven vehicle. After installing rigid connected hydrofoils on wave-driven vehicles, the structural parameters of the hydrofoils are changed, and the kinematic and dynamic responses of wave-driven vehicles at 0–90 ° wave encounter Angle are numerically simulated based on CFD method. The effects of underwater wing depth, hydrofoil spacing and hydrofoil span length on the self- propelled performance of wave-driven vehicles are analyzed. Based on this, the structural parameters of rigidly connected hydrofoils are optimized, which improves the seakeeping and rapidity of wave-driven vehicles in high sea conditions.

USV-Tracker: A novel USV tracking system for surface investigation with limited resources

This paper introduces USV-Tracker, a novel tracking system for Unmanned Surface Vehicles (USVs) tailored for practical applications such as surface investigation and target tracking. The system tackles three pivotal challenges: perception robustness, tracking concealment, and planning efficiency. The contributions of this work are manifold: (1) A multi-sensor fusion framework utilizing an Extended Kalman Filter (EKF) to enhance target detection and positioning accuracy, integrating data from cameras, LiDAR, GPS, and IMU sensors. (2) A two-stage path planning algorithm that generates occlusion avoidance trajectories and employs a virtual elastic force constraint to maintain appropriate relative positioning. In dense obstacle environments, the algorithm tends to get closer to the target and incorporates FOV orientation constraints to ensure stable perception. (3) A visibility-aware control strategy that ensures continuous target observability through EKF-based trajectory prediction. Simulations in Gazebo and corresponding physical experiments validate the system’s effectiveness and robustness, demonstrating its applicability in real-world scenarios. The computational workload is managed on a constrained on-board computer, underscoring the system’s practicality.

Experimental-based hydrodynamic simulation of submarine glider for wave gliders

The wave glider is an unmanned surface vehicle propelled by wave energy, consisting of three main components: a surface float, a submarine glider, and a tether. The submarine glider serves as the primary propulsion mechanism, converting the wave-induced motions of the float into forward thrust, which is crucial for the wave glider’s energy absorption efficiency. However, predicting the motion performance of the submarine glider presents a significant challenge due to its complex and unique structure. In this study, we establish a kinematic and dynamic model of the submarine glider’s hydrofoils, considering the elastic effects such as spring stiffness, spring preload, and spring attachment positions. To support this model, wind tunnel tests were conducted to determine the lift and drag coefficients of the submarine glider under various motion states. Utilizing the elastic hydrofoil model and the experimentally obtained lift and drag coefficients, we developed a comprehensive kinematic and dynamic simulation model of the submarine glider under heave excitation forces. To validate the accuracy of this model, performance tests for the submarine glider were designed under different vertical excitation forces , with results compared to simulation outcomes. The findings indicate that the deviation between simulated and experimental outcomes is less than 5%, demonstrating the model’s precision. This accurate simulation capability allows for detailed analysis of the effects of various design parameters on the glider’s performance and lays a solid foundation for high-accuracy motion simulation of the entire wave glider.

A Bio-Inspired Sliding Mode Method for Autonomous Cooperative Formation Control of Underactuated USVs with Ocean Environment Disturbances

In this paper, a bio-inspired sliding mode control (bio-SMC) and minimal learning parameter (MLP) are proposed to achieve the cooperative formation control of underactuated unmanned surface vehicles (USVs) with external environmental disturbances and model uncertainties. Firstly, the desired trajectory of the follower USV is generated by the leader USV’s position information based on the leader–follower framework, and the problem of cooperative formation control is transformed into a trajectory tracking error stabilization problem. Besides, the USV position errors are stabilized by a backstepping approach, then the virtual longitudinal and virtual lateral velocities can be designed. To alleviate the system oscillation and reduce the computational complexity of the controller, a sliding mode control with a bio-inspired model is designed to avoid the problem of differential explosion caused by repeated derivation. A radial basis function neural network (RBFNN) is adopted for estimating and compensating for the environmental disturbances and model uncertainties, where the MLP algorithm is utilized to substitute for online weight learning in a single-parameter form. Finally, the proposed method is proved to be uniformly and ultimately bounded through the Lyapunov stability theory, and the validity of the method is also verified by simulation experiments.