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 usin...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.展开更多
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 ope...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.展开更多
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)...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.展开更多
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 wit...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.展开更多
Swarm robot systems are an important application of autonomous unmanned surface vehicles on water surfaces.For monitoring natural environments and conducting security activities within a certain range using a surface ...Swarm robot systems are an important application of autonomous unmanned surface vehicles on water surfaces.For monitoring natural environments and conducting security activities within a certain range using a surface vehicle,the swarm robot system is more efficient than the operation of a single object as the former can reduce cost and save time.It is necessary to detect adjacent surface obstacles robustly to operate a cluster of unmanned surface vehicles.For this purpose,a LiDAR(light detection and ranging)sensor is used as it can simultaneously obtain 3D information for all directions,relatively robustly and accurately,irrespective of the surrounding environmental conditions.Although the GPS(global-positioning-system)error range exists,obtaining measurements of the surface-vessel position can still ensure stability during platoon maneuvering.In this study,a three-layer convolutional neural network is applied to classify types of surface vehicles.The aim of this approach is to redefine the sparse 3D point cloud data as 2D image data with a connotative meaning and subsequently utilize this transformed data for object classification purposes.Hence,we have proposed a descriptor that converts the 3D point cloud data into 2D image data.To use this descriptor effectively,it is necessary to perform a clustering operation that separates the point clouds for each object.We developed voxel-based clustering for the point cloud clustering.Furthermore,using the descriptor,3D point cloud data can be converted into a 2D feature image,and the converted 2D image is provided as an input value to the network.We intend to verify the validity of the proposed 3D point cloud feature descriptor by using experimental data in the simulator.Furthermore,we explore the feasibility of real-time object classification within this framework.展开更多
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,wh...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.展开更多
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 r...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.展开更多
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 headi...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.展开更多
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 subject...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.展开更多
文摘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.
基金Research Fund from Science and Technology on Underwater Vehicle Laboratory
文摘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.
基金Shanghai High-level Local University Innovation Team(Maritime Safety&Technical Support)the National Natural Science Foundation of China (Grant No. 42176217)
文摘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.
基金financial support from National Natural Science Foundation of China(Grant No.61601491)Natural Science Foundation of Hubei Province,China(Grant No.2018CFC865)Military Research Project of China(-Grant No.YJ2020B117)。
文摘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.
基金supported by the Future Challenge Program through the Agency for Defense Development funded by the Defense Acquisition Program Administration (No.UC200015RD)。
文摘Swarm robot systems are an important application of autonomous unmanned surface vehicles on water surfaces.For monitoring natural environments and conducting security activities within a certain range using a surface vehicle,the swarm robot system is more efficient than the operation of a single object as the former can reduce cost and save time.It is necessary to detect adjacent surface obstacles robustly to operate a cluster of unmanned surface vehicles.For this purpose,a LiDAR(light detection and ranging)sensor is used as it can simultaneously obtain 3D information for all directions,relatively robustly and accurately,irrespective of the surrounding environmental conditions.Although the GPS(global-positioning-system)error range exists,obtaining measurements of the surface-vessel position can still ensure stability during platoon maneuvering.In this study,a three-layer convolutional neural network is applied to classify types of surface vehicles.The aim of this approach is to redefine the sparse 3D point cloud data as 2D image data with a connotative meaning and subsequently utilize this transformed data for object classification purposes.Hence,we have proposed a descriptor that converts the 3D point cloud data into 2D image data.To use this descriptor effectively,it is necessary to perform a clustering operation that separates the point clouds for each object.We developed voxel-based clustering for the point cloud clustering.Furthermore,using the descriptor,3D point cloud data can be converted into a 2D feature image,and the converted 2D image is provided as an input value to the network.We intend to verify the validity of the proposed 3D point cloud feature descriptor by using experimental data in the simulator.Furthermore,we explore the feasibility of real-time object classification within this framework.
基金Supported by the EDD of China(No.80912020104)the Science and Technology Commission of Shanghai Municipality(No.22ZR1427700 and No.23692106900).
文摘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.
基金Foundation item： Supported by the National Science Foundation （CMMI-1026264 and EEC-1157094）.
文摘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.
文摘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.
基金Supported by the National Key R&D Program of China under Grant No.2022ZD0119902the National Natural Science Foundation of China under Grant No.51979020+5 种基金the Top-notch Young Talents Program of China under Grant No.36261402the Dalian High-level Talents Innovation Support Program under Grant No.2022RQ010the Liaoning Revitalization Talents Program under Grant No.XLYC2007188the Natural Science Foundation of Fujian Province under Grant No.2022J01131710the Postdoctoral Research Foundation of China under Grant No.2022M720619in part by the Fundamental Research Funds for the Central Universities 3132023107.
文摘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.
