LSDA-APF:A Local Obstacle Avoidance Algorithm for Unmanned Surface Vehicles Based on 5G Communication Environment

In view of the complex marine environment of navigation,especially in the case of multiple static and dynamic obstacles,the traditional obstacle avoidance algorithms applied to unmanned surface vehicles(USV)are prone to fall into the trap of local optimization.Therefore,this paper proposes an improved artificial potential field(APF)algorithm,which uses 5G communication technology to communicate between the USV and the control center.The algorithm introduces the USV discrimination mechanism to avoid the USV falling into local optimization when the USV encounter different obstacles in different scenarios.Considering the various scenarios between the USV and other dynamic obstacles such as vessels in the process of performing tasks,the algorithm introduces the concept of dynamic artificial potential field.For the multiple obstacles encountered in the process of USV sailing,based on the International Regulations for Preventing Collisions at Sea(COLREGS),the USV determines whether the next step will fall into local optimization through the discriminationmechanism.The local potential field of the USV will dynamically adjust,and the reverse virtual gravitational potential field will be added to prevent it from falling into the local optimization and avoid collisions.The objective function and cost function are designed at the same time,so that the USV can smoothly switch between the global path and the local obstacle avoidance.The simulation results show that the improved APF algorithm proposed in this paper can successfully avoid various obstacles in the complex marine environment,and take navigation time and economic cost into account.

Development and Missions of Unmanned Surface Vehicle

The navy and other Department of Defense organizations are increasingly interested in the use of unmanned surface vehicles (USVs) for a variety of missions and applications. The term USV refers to any vehicle that operates on the surface of the water without a crew. USVs have the potential, and in some cases the demonstrated ability, to reduce risk to manned forces, provide the necessary force multiplication to accomplish military missions, perform tasks which manned vehicles cannot, and do so in a way that is affordable for the navy. A survey of USV activities worldwide as well as the general technical challenges of USVs was presented below. A general description of USVs was provided along with their typical applications. The technical challenges of developing a USV include its intelligence level, control, high stability, and developmental cost reduction. Through the joint efforts of researchers around the world, it is believed that the development of USVs will enter a new phase in the near future, as USVs could soon be applied widely both in military and civilian service.

A Review of Current Research and Advances in Unmanned Surface Vehicles

Following developments in artificial intelligence and big data technology,the level of intelligence in intelligent vessels has been improved.Intelligent vessels are being developed into unmanned surface vehicles(USVs),which have widely interested scholars in the shipping industry due to their safety,high efficiency,and energy-saving qualities.Considering the current development of USVs,the types of USVs and applications domestically and internationally are being investigated.USVs emerged with technological developments and their characteristics show some differences from traditional vessels,which brings some problems and advantages for their application.Certain maritime regulations are not applicable to USVs and must be changed.The key technologies in the current development of USVs are being investigated.While the level of intelligence is improving,the protection of cargo cannot be neglected.An innovative approach to the internal structure of USVs is proposed,where the inner hull can automatically recover its original state in case of outer hull tilting.Finally,we summarize the development status of USVs,which are an inevitable direction of development in the marine field.

Trajectory tracking control for underactuated unmanned surface vehicles with dynamic uncertainties

The trajectory tracking control problem for underactuated unmanned surface vehicles(USV) was addressed, and the control system took account of the uncertain influences induced by model perturbation, external disturbance, etc. By introducing the reference, trajectory was generated by a virtual USV, and the error equation of trajectory tracking for USV was obtained, which transformed the tracking problem of underactuated USV into the stabilization problem of the trajectory tracking error equation. A backstepping adaptive sliding mode controller was proposed based on backstepping technology and method of dynamic slide model control. By means of theoretical analysis, it is proved that the proposed controller ensures that the solutions of closed loop system have the ultimate boundedness property. Simulation results are presented to illustrate the effectiveness of the proposed controller.

Path Planning Method Based on D^(*) lite Algorithm for Unmanned Surface Vehicles in Complex Environments

In recent decades,path planning for unmanned surface vehicles(USVs)in complex environments,such as harbours and coastlines,has become an important concern.The existing algorithms for real-time path planning for USVs are either too slow at replanning or unreliable in changing environments with multiple dynamic obstacles.In this study,we developed a novel path planning method based on the D^(*) lite algorithm for real-time path planning of USVs in complex environments.The proposed method has the following advantages:(1)the computational time for replanning is reduced significantly owing to the use of an incremental algorithm and a new method for modelling dynamic obstacles;(2)a constrained artificial potential field method is employed to enhance the safety of the planned paths;and(3)the method is practical in terms of vehicle performance.The performance of the proposed method was evaluated through simulations and compared with those of existing algorithms.The simulation results confirmed the efficiency of the method for real-time path planning of USVs in complex environments.

Dynamic modeling of wave driven unmanned surface vehicle in longitudinal profile based on D-H approach

Wave driven unmanned surface vehicle(WUSV) is a new concept ocean robot drived by wave energy and solar energy,and it is very suitable for the vast ocean observations with incomparable endurance.Its dynamic modeling is very important because it is the theoretical foundation for further study in the WUSV motion control and efficiency analysis.In this work,the multibody system of WUSV was described based on D-H approach.Then,the driving principle was analyzed and the dynamic model of WUSV in longitudinal profile is established by Lagrangian mechanics.Finally,the motion simulation of WUSV and comparative analysis are completed by setting different inputs of sea state.Simulation results show that the WUSV dynamic model can correctly reflect the WUSV longitudinal motion process,and the results are consistent with the wave theory.

Radar-Based Collision Avoidance for Unmanned Surface Vehicles'

Unmanned surface vehicles （USVs） have become a focus of research because of their extensive applications. To ensure safety and reliability and to perform complex tasks autonomously, USVs are required to possess accurate perception of the environment and effective collision avoidance capabilities. To achieve these, investigation into real- time marine radar target detection and autonomous collision avoidance technologies is required, aiming at solving the problems of noise jamming, uneven brightness, target loss, and blind areas in marine radar images. These technologies should also satisfy the requirements of real-time and reliability related to high navigation speeds of USVs. Therefore, this study developed an embedded collision avoidance system based on the marine radar, investigated a highly real-time target detection method which contains adaptive smoothing algorithm and robust segmentation algorithm, developed a stable and reliable dynamic local environment model to ensure the safety of USV navigation, and constructed a collision avoidance algorithm based on velocity obstacle （V-obstacle） which adjusts the USV＇s heading and speed in real-time. Sea trials results in multi-obstacle avoidance firstly demonstrate the effectiveness and efficiency of the proposed avoidance system, and then verify its great adaptability and relative stability when a USV sailing in a real and complex marine environment. The obtained results will improve the intelligent level of USV and guarantee the safety of USV independent sailing.

IAP's Solar-Powered Unmanned Surface Vehicle Actively Passes through the Center of typhoon Sinlaku(2020)

The solar-powered marine unmanned surface vehicle(USV) developed by the USV team of the Institute of Atmospheric Physics is a rugged, long-duration, and autonomous navigation vessel designed for the collection of longrange, continuous, real-time, meteorological and oceanographic measurements, especially under extreme sea conditions(sea state 6–7). These solar-powered USVs completed a long-term continuous navigation observation test over 26 days.During this time, they coordinated double-USV observations and actively navigated into the path of Typhoon Sinlaku(2020) before collecting data very close to its center during the 2020 USV South China Sea Typhoon Observation Experiment. Detailed high temporal resolution(1 min) real-time observations collected by the USV on the typhoon were used for operational typhoon forecasting and warning for the first time. As a mobile meteorological and oceanographic observation station capable of reliable, automated deployment, data collection, and transmission, such solar-powered USVs can replace traditional observation platforms to provide valuable real-time data for research, forecasting, and early warnings for potential marine meteorological disasters.

Serret-Frenet frame based on path following control for underactuated unmanned surface vehicles with dynamic uncertainties

The path following problem for an underactuated unmanned surface vehicle(USV) in the Serret-Frenet frame is addressed. The control system takes account of the uncertain influence induced by model perturbation, external disturbance, etc. By introducing the Serret-Frenet frame and global coordinate transformation, the control problem of underactuated system(a nonlinear system with single-input and ternate-output) is transformed into the control problem of actuated system(a single-input and single-output nonlinear system), which simplifies the controller design. A backstepping adaptive sliding mode controller(BADSMC)is proposed based on backstepping design technique, adaptive method and theory of dynamic slide model control(DSMC). Then, it is proven that the state of closed loop system is globally stabilized to the desired configuration with the proposed controller. Simulation results are presented to illustrate the effectiveness of the proposed controller.

LSTM-DPPO based deep reinforcement learning controller for path following optimization of unmanned surface vehicle

To solve the path following control problem for unmanned surface vehicles(USVs),a control method based on deep reinforcement learning(DRL)with long short-term memory(LSTM)networks is proposed.A distributed proximal policy opti-mization(DPPO)algorithm,which is a modified actor-critic-based type of reinforcement learning algorithm,is adapted to improve the controller performance in repeated trials.The LSTM network structure is introduced to solve the strong temporal cor-relation USV control problem.In addition,a specially designed path dataset,including straight and curved paths,is established to simulate various sailing scenarios so that the reinforcement learning controller can obtain as much handling experience as possible.Extensive numerical simulation results demonstrate that the proposed method has better control performance under missions involving complex maneuvers than trained with limited scenarios and can potentially be applied in practice.

Modeling and Simulation of Automatic Berthing based on Bow and Stern Thruster Assist for Unmanned Surface Vehicle

In order to solve the technical problems of autonomous berthing of the Unmanned Surface Vehicle(USV),this research has met the requirements of maneuverability berthing under different conditions by effectively using the bow and stern thrusters,which is a technological breakthrough in actual production and life.Based on the MMG model,the maneuverability mathematical model of the USV with bow and stern thruster was established.And the motion simulation of USV maneuvering was carried out through the numerical simulation calculation.Then the berthing plan was designed based on the maneuverability analysis of the USV low-speed motion,and the simulation of automatic berthing for USV was carried out.The research results of this paper can be of certain practical significance for the USV based on the support of the bow and stern thruster in the berthing.At the same time,it also provides a certain theoretical reference for the handling of the USV automatic berthing.

Cooperative multi-target hunting by unmanned surface vehicles based on multi-agent reinforcement learning

To solve the problem of multi-target hunting by an unmanned surface vehicle(USV)fleet,a hunting algorithm based on multi-agent reinforcement learning is proposed.Firstly,the hunting environment and kinematic model without boundary constraints are built,and the criteria for successful target capture are given.Then,the cooperative hunting problem of a USV fleet is modeled as a decentralized partially observable Markov decision process(Dec-POMDP),and a distributed partially observable multitarget hunting Proximal Policy Optimization(DPOMH-PPO)algorithm applicable to USVs is proposed.In addition,an observation model,a reward function and the action space applicable to multi-target hunting tasks are designed.To deal with the dynamic change of observational feature dimension input by partially observable systems,a feature embedding block is proposed.By combining the two feature compression methods of column-wise max pooling(CMP)and column-wise average-pooling(CAP),observational feature encoding is established.Finally,the centralized training and decentralized execution framework is adopted to complete the training of hunting strategy.Each USV in the fleet shares the same policy and perform actions independently.Simulation experiments have verified the effectiveness of the DPOMH-PPO algorithm in the test scenarios with different numbers of USVs.Moreover,the advantages of the proposed model are comprehensively analyzed from the aspects of algorithm performance,migration effect in task scenarios and self-organization capability after being damaged,the potential deployment and application of DPOMH-PPO in the real environment is verified.

Trajectory-tracking control of an unmanned surface vehicle based on characteristic modelling approach:Implementation and field testing

In this study,a practical adaptive control scheme is proposed for the trajectory tracking of an unmanned surface vehicle via the characteristic modelling approach.Therefore,accurate tracking control can be achieved in the presence of unknown time‐varying model parameters and environmental disturbances.The control scheme comprises a trajectory guidance module based on the virtual target approach and a tracking control module designed by characteristic modelling theory.Firstly,the ideal control commands of the yaw speed and surge speed are generated using the position errors between the vehicle and the virtual target.Then,a second‐order characteristic model for the heading and surge speed channel is developed.The parameters of the model are updated by a real‐time parameter identification algorithm.Based on this model,an integrated adaptive control law is designed which consists of golden‐section control,feed‐forward control and integral control.Finally,the development processes of the vehicle platform and the control algorithms are described,and the results of simulation and field experiments are presented and discussed.

Multi-role Remotely Operated Marine Surface Vehicle

Development of man-packable,versatile marine surface vehicle with ability to rescue a drowning victim and also capable of carrying mission specific sensor is explored.Design thinking methodology is implemented by using existing equipment/platform with the addition of external attachment to make it a functional product.Iterative prototyping process with extensive testing to achieve user-centric solution.Individual prototypes and their possible sub-configurations with their integration and characteristics are studied and compared with numerical model,inferences obtained are utilised to improve for the next iteration.A novel hinge-clamp assembly enables this marine surface vehicle to operate in the event of an overturn,this phenomenon is further studied with the aid of a mathematical model(Pendulum in a fluid).This research project aims to demonstrate a multi-role unmanned surface vehicle.

Adaptive sliding-mode path following control system of the underactuated USV under the influence of ocean currents

The path-following control of the asymmetry underactuated unmanned surface vehicle(USV) under external disturbances such as unknown constant and irrational ocean currents is discussed, and an adaptive sliding-mode path-following control system is proposed, which comprises a path-variable updated law,a modified integral line-of-sight(ILOS) guidance law based on a time-varying lookahead distance and adaptive feedback linearizing controllers combined with sliding-mode technique. A more accurate USV model without the assumption of having diagonal inertia and damping matrices is first presented, aiming at improving the performance of the path-following control. Next, the coordinate transformation is adopted to decouple the sway dynamic from the rudder angle, and the path-following errors dynamics without non-singular problem are presented in the moving Frenet-Serret frame. Then, based on the cascaded theorem and the adaptive sliding-mode method, the adaptive control law of position errors and course error are designed, among which the lookahead distance and integral gain are all computed as different functions of cross-track error to estimate and compensate the sideslip angle caused by external disturbances adaptively. Finally, according to the Lyapunov and cascaded theorem, the control system proposed is proved to be uniform globally asymptotic stability(UGAS) and uniform semiglobal exponential stability(USGES) when the control objectives are all achieved. Simulation results illustrate the precision and high-quality performance of this new controller.

Development of a Remotely Controlled Testing Platform with Low-drag Air-ventilated Hull

This paper addresses the development and testing of a remotely controlled boat platform with an innovative air-ventilated hull. The application of air cavities on the underside of ship hulls is a promising means for reducing hydrodynamic drag and pollutant emissions and increasing marine transportation efficiency. Despite this concept＇s potential, design optimization and high-performance operation of novel air-cavity ships remain a challenging problem. Hull construction and sensor instrumentation of the model-scale air-cavity boat is described in the paper. The modular structure of the hull allows for easy modifications, and an electric propulsion unit enables self-propelled operation. The boat is controlled remotely via a radio transmission system. Results of initial tests are reported, including thrust, speed, and airflow rate in several loading conditions. The constructed platform can be used for optimizing air-cavity systems and testing other innovative hull designs. This system can be also developed into a high-performance unmanned boat.

洋流干扰下无人船限制水域直线跟踪安全视距制导

The collision-free straight-line following of an unmanned surface vehicle(USV)moving in a constrained water region subject to stationary and moving obstacles is addressed in this paper.USV systems are normally subjected to surge velocity constraints,yaw rate constraints,and unknown ocean currents.Herein,a safety-certificated line-of-sight(LOS)guidance method is proposed to achieve a constrained straight-line following task.First,an antidisturbance LOS guidance law is designed based on the LOS guidance scheme and an extended state observer.Furthermore,collision avoidance with waterway boundaries and stationary/moving obstacles is encoded in control barrier functions,utilizing which the safety constraints are transformed into input constraints.Finally,safety-certificated guidance signals are obtained by solving a quadratic programming problem subject to input constraints.Using the proposed safety-certified LOS guidance method,the USV can accomplish a straight-line following task with guaranteed input-to-state safety.Simulation results substantiate the efficacy of the proposed safety-certificated LOS guidance method for the straight-line following of USVs moving in a constrained water region subject to unknown ocean currents.

基于反演积分技术的无人驾驶水面飞行器的自动驾驶仪设计及其实验结果

Controller tuning is the correct setting of controller parameters to control complex dynamic systems appropriately and with high accuracy.Therefore,this study addressed the development of a method for tuning the heading controller of an unmanned surface vehicle(USV)based on the backstepping integral technique to enhance the vehicle behavior while tracking a desired position for water monitoring missions.The vehicle self-steering system(autopilot system)is designed theoretically and tested via a simulation.Based on the Lyapunov theory,the stability in the closed-loop system is guaranteed,and the convergence of the heading tracking errors is obtained.In addition,the designed control law is implemented via a microcontroller and tested experimentally in real time.Conclusion,experimental results were carried out to verify the robustness of the designed controller when disturbances and uncertainties are introduced into the system.

Fusion Algorithm Based on Improved A^(*)and DWA for USV Path Planning

The traditional A^(*)algorithm exhibits a low efficiency in the path planning of unmanned surface vehicles(USVs).In addition,the path planned presents numerous redundant inflection waypoints,and the security is low,which is not conducive to the control of USV and also affects navigation safety.In this paper,these problems were addressed through the following improvements.First,the path search angle and security were comprehensively considered,and a security expansion strategy of nodes based on the 5×5 neighborhood was proposed.The A^(*)algorithm search neighborhood was expanded from 3×3 to 5×5,and safe nodes were screened out for extension via the node security expansion strategy.This algorithm can also optimize path search angles while improving path security.Second,the distance from the current node to the target node was introduced into the heuristic function.The efficiency of the A^(*)algorithm was improved,and the path was smoothed using the Floyd algorithm.For the dynamic adjustment of the weight to improve the efficiency of DWA,the distance from the USV to the target point was introduced into the evaluation function of the dynamic-window approach(DWA)algorithm.Finally,combined with the local target point selection strategy,the optimized DWA algorithm was performed for local path planning.The experimental results show the smooth and safe path planned by the fusion algorithm,which can successfully avoid dynamic obstacles and is effective and feasible in path planning for USVs.