In the process of performing a task,autonomous unmanned systems face the problem of scene changing,which requires the ability of real-time decision-making under dynamically changing scenes.Therefore,taking the unmanne...In the process of performing a task,autonomous unmanned systems face the problem of scene changing,which requires the ability of real-time decision-making under dynamically changing scenes.Therefore,taking the unmanned system coordinative region control operation as an example,this paper combines knowledge representation with probabilistic decisionmaking and proposes a role-based Bayesian decision model for autonomous unmanned systems that integrates scene cognition and individual preferences.Firstly,according to utility value decision theory,the role-based utility value decision model is proposed to realize task coordination according to the preference of the role that individual is assigned.Then,multi-entity Bayesian network is introduced for situation assessment,by which scenes and their uncertainty related to the operation are semantically described,so that the unmanned systems can conduct situation awareness in a set of scenes with uncertainty.Finally,the effectiveness of the proposed method is verified in a virtual task scenario.This research has important reference value for realizing scene cognition,improving cooperative decision-making ability under dynamic scenes,and achieving swarm level autonomy of unmanned systems.展开更多
Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e....Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities.In this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource constraints.Specifically,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as machines.By analyzing the constraints in sortie scheduling,a mixed-integer planning model is constructed.In particular,the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency.The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue.To efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is developed.The solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing strategies.And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.展开更多
The influence of ocean environment on navigation of autonomous underwater vehicle(AUV)cannot be ignored.In the marine environment,ocean currents,internal waves,and obstacles are usually considered in AUV path planning...The influence of ocean environment on navigation of autonomous underwater vehicle(AUV)cannot be ignored.In the marine environment,ocean currents,internal waves,and obstacles are usually considered in AUV path planning.In this paper,an improved particle swarm optimization(PSO)is proposed to solve three problems,traditional PSO algorithm is prone to fall into local optimization,path smoothing is always carried out after all the path planning steps,and the path fitness function is so simple that it cannot adapt to complex marine environment.The adaptive inertia weight and the“active”particle of the fish swarm algorithm are established to improve the global search and local search ability of the algorithm.The cubic spline interpolation method is combined with PSO to smooth the path in real time.The fitness function of the algorithm is optimized.Five evaluation indexes are comprehensively considered to solve the three-demensional(3D)path planning problem of AUV in the ocean currents and internal wave environment.The proposed method improves the safety of the path planning and saves energy.展开更多
A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approa...A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.展开更多
In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-ey...In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.展开更多
To resolve the path tracking problem of autonomous ground vehicles,an analysis of existing path tracking methods was carried out and an important conclusion was got.The vehicle-road model is crucial for path following...To resolve the path tracking problem of autonomous ground vehicles,an analysis of existing path tracking methods was carried out and an important conclusion was got.The vehicle-road model is crucial for path following.Based on the conclusion,a new vehicle-road model named "ribbon model" was constructed with consideration of road width and vehicle geometry structure.A new vehicle-road evaluation algorithm was proposed based on this model,and a new path tracking controller including a steering controller and a speed controller was designed.The difficulties of preview distance selection and parameters tuning with speed in the pure following controller are avoided in this controller.To verify the performance of the novel method,simulation and real vehicle experiments were carried out.Experimental results show that the path tracking controller can keep the vehicle in the road running as fast as possible,so it can adjust the control strategy,such as safety,amenity,and rapidity criteria autonomously according to the road situation.This is important for the controller to adapt to different kinds of environments,and can improve the performance of autonomous ground vehicles significantly.展开更多
The autonomous "celestial navigation scheme" for deep space probe departing from the earth and the autonomous "optical navigation scheme" for encountering object celestial body are presented. Then,...The autonomous "celestial navigation scheme" for deep space probe departing from the earth and the autonomous "optical navigation scheme" for encountering object celestial body are presented. Then, aiming at the conditions that large initial estimation errors and non-Gaussian distribution of state or measurement errors may exist in orbit determination process of the two phases, UPF (unscented particle filter) is introduced into the navigation schemes. By tackling nonlinear and non-Gaussian problems, UPF overcomes the accuracy influence brought by the traditional EKF (extended Kalman filter), UKF (unscented Kalman filter), and PF (particle filter) schemes in approximate treatment to nonlinear and non-Gaussian state model and measurement model. The numerical simulations demonstrate the feasibility and higher accuracy of the UPF navigation scheme.展开更多
Autonomous underwater vehicles(AUV) work in a complex marine environment. Its system reliability and autonomous fault diagnosis are particularly important and can provide the basis for underwater vehicles to take corr...Autonomous underwater vehicles(AUV) work in a complex marine environment. Its system reliability and autonomous fault diagnosis are particularly important and can provide the basis for underwater vehicles to take corresponding security policy in a failure. Aiming at the characteristics of the underwater vehicle which has uncertain system and modeling difficulty, an improved Elman neural network is introduced which is applied to the underwater vehicle motion modeling. Through designing self-feedback connection with fixed gain in the unit connection as well as increasing the feedback of the output layer node, improved Elman network has faster convergence speed and generalization ability. This method for high-order nonlinear system has stronger identification ability. Firstly, the residual is calculated by comparing the output of the underwater vehicle model(estimation in the motion state) with the actual measured values. Secondly, characteristics of the residual are analyzed on the basis of fault judging criteria. Finally, actuator fault diagnosis of the autonomous underwater vehicle is carried out. The results of the simulation experiment show that the method is effective.展开更多
Advanced driver-assistance systems such as Honda’s collision mitigation brake system(CMBS)can help achieve traffic safety.In this paper,the naturalistic driving study and a series of simulations are combined to bette...Advanced driver-assistance systems such as Honda’s collision mitigation brake system(CMBS)can help achieve traffic safety.In this paper,the naturalistic driving study and a series of simulations are combined to better evaluate the performance of the CMBS in the Chinese traffic environment.First,because safety-critical situations can be diverse especially in the Chinese environment,the Chinese traffic-accident characteristics are analyzed according to accident statistics over the past 17 years.Next,10 Chinese traffic-accident scenarios accounting for more than 80%of traffic accidents are selected.For each typical scenario,353 representative cases are collected from the traffic-management department of Beijing.These real-world accident cases are then reconstructed by the traffic-accident-reconstruction software PC-Crash on the basis of accident-scene diagrams.This study also proposes a systematic analytical process for estimating the effectiveness of the technology using the co-simulation platform of PC-Crash and rateEFFECT,in which 176 simulations are analyzed in detail to assess the accident-avoidance performance of the CMBS.The overall collision-avoidance effectiveness reaches 82.4%,showing that the proposed approach is efficient for avoiding collisions,thereby enhancing traffic safety and improving traffic management.展开更多
The distributed cooperative decision problems of missiles autonomous formation with network packet loss are investigated by using the potential game based on formation principles.In particular,a dynamic target allocat...The distributed cooperative decision problems of missiles autonomous formation with network packet loss are investigated by using the potential game based on formation principles.In particular,a dynamic target allocation method for missiles formation is provided based on the potential game and formation principles,after the introduction of cooperative guidance and control system of the missiles formation.Then we seek the optimization of a global utility function through autonomous missiles that are capable of making individually rational decisions to optimize their own utility functions.The first important aspect of the problem is to design an individual utility function considering the characteristics of the missiles formation,with which the objective of the missiles are localized to each missile yet aligned with the global utility function.The second is to equip the missiles with an appropriate coordination mechanism with each missile pursuing the optimization of its own utility function.We present the design procedure for the utility,and present a coordination mechanism based on spatial adaptive play and then introduce the idea of“cyclical selected spatial adaptive play”and“negotiation based on time division multiple address(TDMA)protocol formation support network”.Finally,we present simulations for the distributed dynamic target allocation on the comprehensive digital simulation system,and the results illustrate the effectiveness and engineering applicability of the method.展开更多
The flexible transmission shaft and wheel propeller are combined as the kinetic source equipment, which realizes the nmlti-motion modes of the autonomous underwater vehicle （AUV） such as vectored thruster and wheele...The flexible transmission shaft and wheel propeller are combined as the kinetic source equipment, which realizes the nmlti-motion modes of the autonomous underwater vehicle （AUV） such as vectored thruster and wheeled movement. In order to study the interactional principle between the hull and the wheel propellers while the AUV navigating in water, the computational fluid dynamics （CFD） method is used to simulate numerically the unsteady viscous flow around AUV with propellers by using the Reynolds-averaged Navier-Stokes （RANS） equations, shear-stress transport （SST） k-w model and pressure with splitting of operators （PISO） algorithm based on sliding mesh. The hydrodynamic parameters of AUV with propellers such as resistance, pressure and velocity are got, which reflect well the real ambient flow field of AUV with propellers. Then, the semi-implicit method for pressure-linked equations （SIMPLE） algorithm is used to compute the steady viscous flow field of AUV hull and propellers, respectively. The computational results agree well with the experimental data, which shows that the numerical method has good accuracy in the prediction of hydrodynamic performance. The interaction between AUV hull and wheel propellers is predicted qualitatively and quantitatively by comparing the hydrodynamic parameters such as resistance, pressure and velocity with those from integral computation and partial computation of the viscous flow around AUV with propellers, which provides an effective reference to the shady on noise and vibration of AUV hull and propellers in real environment. It also provides technical support for the design of new AUVs.展开更多
A full distribution CNC system based on SERCOS bus is studied in accordance with the limitations of traditional PC-based motion card. The conventional PC-based motion control card is dispersed into several autonomous ...A full distribution CNC system based on SERCOS bus is studied in accordance with the limitations of traditional PC-based motion card. The conventional PC-based motion control card is dispersed into several autonomous intelligent servo-control units with the function of servo driver. The autonomous intelligent servocontrol units realize the loop control of position, velocity and current. Interpolation computation is completed in PC and the computational results are transferred to every autonomous intelligent servo-control unit by high speed SERCOS bus. Software or hardware synchronization technology is used to ensure all servomotors are successive and synchronously running. The communication and synchronization technology of SERCOS are also researched and the autonomous intelligent servo-control card is developed byself. Finally, the experiment of circle contour process on a prototype system proves the feasibility.展开更多
Many vehicle platoons are interrupted while traveling on roads,especially at urban signalized intersections.One reason for such interruptions is the inability to exchange real-time information between traditional huma...Many vehicle platoons are interrupted while traveling on roads,especially at urban signalized intersections.One reason for such interruptions is the inability to exchange real-time information between traditional human-driven vehicles and intersection infrastructure.Thus,this paper develops a Markov chain-based model to recognize platoons.A simulation experiment is performed in Vissim based on field data extracted from video recordings to prove the model’s applicability.The videos,recorded with a high-definition camera,contain field driving data from three Tesla vehicles,which can achieve Level 2 autonomous driving.The simulation results show that the recognition rate exceeds 80%when the connected and autonomous vehicle penetration rate is higher than 0.7.Whether a vehicle is upstream or downstream of an intersection also affects the performance of platoon recognition.The platoon recognition model developed in this paper can be used as a signal control input at intersections to reduce the unnecessary interruption of vehicle platoons and improve traffic efficiency.展开更多
How to make use of limited onboard resources for complex and heavy space tasks has attracted much attention.With the continuous improvement on satellite payload capacity and the increasing complexity of observation re...How to make use of limited onboard resources for complex and heavy space tasks has attracted much attention.With the continuous improvement on satellite payload capacity and the increasing complexity of observation requirements,the importance of satellite autonomous task scheduling research has gradually increased.This article first gives the problem description and mathematical model for the satellite autonomous task scheduling and then follows the steps of"satellite autonomous task scheduling,centralized autonomous collaborative task scheduling architecture,distributed autonomous collaborative task scheduling architecture,solution algorithm".Finally,facing the complex and changeable environment situation,this article proposes the future direction of satellite autonomous task scheduling.展开更多
Rich semantic information in natural language increases team efficiency in human collaboration, reduces dependence on high precision data information, and improves adaptability to dynamic environment. We propose a sem...Rich semantic information in natural language increases team efficiency in human collaboration, reduces dependence on high precision data information, and improves adaptability to dynamic environment. We propose a semantic centered cloud control framework for cooperative multi-unmanned ground vehicle(UGV) system. Firstly, semantic modeling of task and environment is implemented by ontology to build a unified conceptual architecture, and secondly, a scene semantic information extraction method combining deep learning and semantic web rule language(SWRL) rules is used to realize the scene understanding and task-level cloud task cooperation. Finally, simulation results show that the framework is a feasible way to enable autonomous unmanned systems to conduct cooperative tasks.展开更多
After a brief emphasis about the interconnected world, including Cyber-Physical Systems of Systems, the increasing importance of the decision-making by autonomous, quasi-autonomous, and autonomic systems is emphasised...After a brief emphasis about the interconnected world, including Cyber-Physical Systems of Systems, the increasing importance of the decision-making by autonomous, quasi-autonomous, and autonomic systems is emphasised. Promising roles of computational understanding, computational awareness, and computational wisdom for better autonomous decision-making are outlined. The contributions of simulation-based approaches are listed.展开更多
This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater ve...This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.展开更多
This paper presents a deep reinforcement learning(DRL)-based motion control method to provide unmanned aerial vehicles(UAVs)with additional flexibility while flying across dynamic unknown environments autonomously.Thi...This paper presents a deep reinforcement learning(DRL)-based motion control method to provide unmanned aerial vehicles(UAVs)with additional flexibility while flying across dynamic unknown environments autonomously.This method is applicable in both military and civilian fields such as penetration and rescue.The autonomous motion control problem is addressed through motion planning,action interpretation,trajectory tracking,and vehicle movement within the DRL framework.Novel DRL algorithms are presented by combining two difference-amplifying approaches with traditional DRL methods and are used for solving the motion planning problem.An improved Lyapunov guidance vector field(LGVF)method is used to handle the trajectory-tracking problem and provide guidance control commands for the UAV.In contrast to conventional motion-control approaches,the proposed methods directly map the sensorbased detections and measurements into control signals for the inner loop of the UAV,i.e.,an end-to-end control.The training experiment results show that the novel DRL algorithms provide more than a 20%performance improvement over the state-ofthe-art DRL algorithms.The testing experiment results demonstrate that the controller based on the novel DRL and LGVF,which is only trained once in a static environment,enables the UAV to fly autonomously in various dynamic unknown environments.Thus,the proposed technique provides strong flexibility for the controller.展开更多
基金the Military Science Postgraduate Project of PLA(JY2020B006).
文摘In the process of performing a task,autonomous unmanned systems face the problem of scene changing,which requires the ability of real-time decision-making under dynamically changing scenes.Therefore,taking the unmanned system coordinative region control operation as an example,this paper combines knowledge representation with probabilistic decisionmaking and proposes a role-based Bayesian decision model for autonomous unmanned systems that integrates scene cognition and individual preferences.Firstly,according to utility value decision theory,the role-based utility value decision model is proposed to realize task coordination according to the preference of the role that individual is assigned.Then,multi-entity Bayesian network is introduced for situation assessment,by which scenes and their uncertainty related to the operation are semantically described,so that the unmanned systems can conduct situation awareness in a set of scenes with uncertainty.Finally,the effectiveness of the proposed method is verified in a virtual task scenario.This research has important reference value for realizing scene cognition,improving cooperative decision-making ability under dynamic scenes,and achieving swarm level autonomy of unmanned systems.
基金the financial support of the National Key Research and Development Plan(2021YFB3302501)the financial support of the National Natural Science Foundation of China(12102077)。
文摘Safe and efficient sortie scheduling on the confined flight deck is crucial for maintaining high combat effectiveness of the aircraft carrier.The primary difficulty exactly lies in the spatiotemporal coordination,i.e.,allocation of limited supporting resources and collision-avoidance between heterogeneous dispatch entities.In this paper,the problem is investigated in the perspective of hybrid flow-shop scheduling problem by synthesizing the precedence,space and resource constraints.Specifically,eight processing procedures are abstracted,where tractors,preparing spots,catapults,and launching are virtualized as machines.By analyzing the constraints in sortie scheduling,a mixed-integer planning model is constructed.In particular,the constraint on preparing spot occupancy is improved to further enhance the sortie efficiency.The basic trajectory library for each dispatch entity is generated and a delayed strategy is integrated to address the collision-avoidance issue.To efficiently solve the formulated HFSP,which is essentially a combinatorial problem with tightly coupled constraints,a chaos-initialized genetic algorithm is developed.The solution framework is validated by the simulation environment referring to the Fort-class carrier,exhibiting higher sortie efficiency when compared to existing strategies.And animation of the simulation results is available at www.bilibili.com/video/BV14t421A7Tt/.The study presents a promising supporting technique for autonomous flight deck operation in the foreseeable future,and can be easily extended to other supporting scenarios,e.g.,ammunition delivery and aircraft maintenance.
基金supported by the High-tech Ship Projects of the Ministry of Industry and Information Technology of China(2021-342).
文摘The influence of ocean environment on navigation of autonomous underwater vehicle(AUV)cannot be ignored.In the marine environment,ocean currents,internal waves,and obstacles are usually considered in AUV path planning.In this paper,an improved particle swarm optimization(PSO)is proposed to solve three problems,traditional PSO algorithm is prone to fall into local optimization,path smoothing is always carried out after all the path planning steps,and the path fitness function is so simple that it cannot adapt to complex marine environment.The adaptive inertia weight and the“active”particle of the fish swarm algorithm are established to improve the global search and local search ability of the algorithm.The cubic spline interpolation method is combined with PSO to smooth the path in real time.The fitness function of the algorithm is optimized.Five evaluation indexes are comprehensively considered to solve the three-demensional(3D)path planning problem of AUV in the ocean currents and internal wave environment.The proposed method improves the safety of the path planning and saves energy.
基金Project(90820302) supported by the National Natural Science Foundation of China
文摘A new vision-based long-distance lane perception and front vehicle location method was developed for decision making of full autonomous vehicles on highway roads,Firstly,a real-time long-distance lane detection approach was presented based on a linear-cubic road model for two-lane highways.By using a novel robust lane marking feature which combines the constraints of intensity,edge and width,the lane markings in far regions were extracted accurately and efficiently.Next,the detected lane lines were selected and tracked by estimating the lateral offset and heading angle of ego vehicle with a Kalman filter,Finally,front vehicles were located on correct lanes using the tracked lane lines,Experiment results show that the proposed lane perception approach can achieve an average correct detection rate of 94.37% with an average false positive detection rate of 0.35%,The proposed approaches for long-distance lane perception and front vehicle location were validated in a 286 km full autonomous drive experiment under real traffic conditions.This successful experiment shows that the approaches are effective and robust enough for full autonomous vehicles on highway roads.
基金Project(2006AA04Z202)supported by the National High Technology Research and Development Program of ChinaProject(51105281)supported by the National Natural Science Foundation of China
文摘In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.
基金Project(90820302)supported by the National Natural Science Foundation of China
文摘To resolve the path tracking problem of autonomous ground vehicles,an analysis of existing path tracking methods was carried out and an important conclusion was got.The vehicle-road model is crucial for path following.Based on the conclusion,a new vehicle-road model named "ribbon model" was constructed with consideration of road width and vehicle geometry structure.A new vehicle-road evaluation algorithm was proposed based on this model,and a new path tracking controller including a steering controller and a speed controller was designed.The difficulties of preview distance selection and parameters tuning with speed in the pure following controller are avoided in this controller.To verify the performance of the novel method,simulation and real vehicle experiments were carried out.Experimental results show that the path tracking controller can keep the vehicle in the road running as fast as possible,so it can adjust the control strategy,such as safety,amenity,and rapidity criteria autonomously according to the road situation.This is important for the controller to adapt to different kinds of environments,and can improve the performance of autonomous ground vehicles significantly.
基金the National "863" High Technology Development Project of China (2005AA735080).
文摘The autonomous "celestial navigation scheme" for deep space probe departing from the earth and the autonomous "optical navigation scheme" for encountering object celestial body are presented. Then, aiming at the conditions that large initial estimation errors and non-Gaussian distribution of state or measurement errors may exist in orbit determination process of the two phases, UPF (unscented particle filter) is introduced into the navigation schemes. By tackling nonlinear and non-Gaussian problems, UPF overcomes the accuracy influence brought by the traditional EKF (extended Kalman filter), UKF (unscented Kalman filter), and PF (particle filter) schemes in approximate treatment to nonlinear and non-Gaussian state model and measurement model. The numerical simulations demonstrate the feasibility and higher accuracy of the UPF navigation scheme.
基金Project(2012T50331)supported by China Postdoctoral Science FoundationProject(2008AA092301-2)supported by the High-Tech Research and Development Program of China
文摘Autonomous underwater vehicles(AUV) work in a complex marine environment. Its system reliability and autonomous fault diagnosis are particularly important and can provide the basis for underwater vehicles to take corresponding security policy in a failure. Aiming at the characteristics of the underwater vehicle which has uncertain system and modeling difficulty, an improved Elman neural network is introduced which is applied to the underwater vehicle motion modeling. Through designing self-feedback connection with fixed gain in the unit connection as well as increasing the feedback of the output layer node, improved Elman network has faster convergence speed and generalization ability. This method for high-order nonlinear system has stronger identification ability. Firstly, the residual is calculated by comparing the output of the underwater vehicle model(estimation in the motion state) with the actual measured values. Secondly, characteristics of the residual are analyzed on the basis of fault judging criteria. Finally, actuator fault diagnosis of the autonomous underwater vehicle is carried out. The results of the simulation experiment show that the method is effective.
基金Project(51625503) supported by the National Science Fund for Distinguished Young Scholars,ChinaProject(61790561) supported by the National Natural Science Foundation of China+1 种基金Project(20163000124) supported by Tsinghua-Honda Joint Research,ChinaProject(TTS2017-02) supported by the Open Fund for Jiangsu Key Laboratory of Traffic and Transportation Security,China
文摘Advanced driver-assistance systems such as Honda’s collision mitigation brake system(CMBS)can help achieve traffic safety.In this paper,the naturalistic driving study and a series of simulations are combined to better evaluate the performance of the CMBS in the Chinese traffic environment.First,because safety-critical situations can be diverse especially in the Chinese environment,the Chinese traffic-accident characteristics are analyzed according to accident statistics over the past 17 years.Next,10 Chinese traffic-accident scenarios accounting for more than 80%of traffic accidents are selected.For each typical scenario,353 representative cases are collected from the traffic-management department of Beijing.These real-world accident cases are then reconstructed by the traffic-accident-reconstruction software PC-Crash on the basis of accident-scene diagrams.This study also proposes a systematic analytical process for estimating the effectiveness of the technology using the co-simulation platform of PC-Crash and rateEFFECT,in which 176 simulations are analyzed in detail to assess the accident-avoidance performance of the CMBS.The overall collision-avoidance effectiveness reaches 82.4%,showing that the proposed approach is efficient for avoiding collisions,thereby enhancing traffic safety and improving traffic management.
基金supported by the Industrial Technology Development Program(B1120131046)
文摘The distributed cooperative decision problems of missiles autonomous formation with network packet loss are investigated by using the potential game based on formation principles.In particular,a dynamic target allocation method for missiles formation is provided based on the potential game and formation principles,after the introduction of cooperative guidance and control system of the missiles formation.Then we seek the optimization of a global utility function through autonomous missiles that are capable of making individually rational decisions to optimize their own utility functions.The first important aspect of the problem is to design an individual utility function considering the characteristics of the missiles formation,with which the objective of the missiles are localized to each missile yet aligned with the global utility function.The second is to equip the missiles with an appropriate coordination mechanism with each missile pursuing the optimization of its own utility function.We present the design procedure for the utility,and present a coordination mechanism based on spatial adaptive play and then introduce the idea of“cyclical selected spatial adaptive play”and“negotiation based on time division multiple address(TDMA)protocol formation support network”.Finally,we present simulations for the distributed dynamic target allocation on the comprehensive digital simulation system,and the results illustrate the effectiveness and engineering applicability of the method.
基金Project(2006AA09Z235) supported by National High Technology Research and Development Program of ChinaProject(CX2009B003) supported by Hunan Provincial Innovation Foundation For Postgraduate,China
文摘The flexible transmission shaft and wheel propeller are combined as the kinetic source equipment, which realizes the nmlti-motion modes of the autonomous underwater vehicle （AUV） such as vectored thruster and wheeled movement. In order to study the interactional principle between the hull and the wheel propellers while the AUV navigating in water, the computational fluid dynamics （CFD） method is used to simulate numerically the unsteady viscous flow around AUV with propellers by using the Reynolds-averaged Navier-Stokes （RANS） equations, shear-stress transport （SST） k-w model and pressure with splitting of operators （PISO） algorithm based on sliding mesh. The hydrodynamic parameters of AUV with propellers such as resistance, pressure and velocity are got, which reflect well the real ambient flow field of AUV with propellers. Then, the semi-implicit method for pressure-linked equations （SIMPLE） algorithm is used to compute the steady viscous flow field of AUV hull and propellers, respectively. The computational results agree well with the experimental data, which shows that the numerical method has good accuracy in the prediction of hydrodynamic performance. The interaction between AUV hull and wheel propellers is predicted qualitatively and quantitatively by comparing the hydrodynamic parameters such as resistance, pressure and velocity with those from integral computation and partial computation of the viscous flow around AUV with propellers, which provides an effective reference to the shady on noise and vibration of AUV hull and propellers in real environment. It also provides technical support for the design of new AUVs.
文摘A full distribution CNC system based on SERCOS bus is studied in accordance with the limitations of traditional PC-based motion card. The conventional PC-based motion control card is dispersed into several autonomous intelligent servo-control units with the function of servo driver. The autonomous intelligent servocontrol units realize the loop control of position, velocity and current. Interpolation computation is completed in PC and the computational results are transferred to every autonomous intelligent servo-control unit by high speed SERCOS bus. Software or hardware synchronization technology is used to ensure all servomotors are successive and synchronously running. The communication and synchronization technology of SERCOS are also researched and the autonomous intelligent servo-control card is developed byself. Finally, the experiment of circle contour process on a prototype system proves the feasibility.
基金Project(71871013)supported by the National Natural Science Foundation of China。
文摘Many vehicle platoons are interrupted while traveling on roads,especially at urban signalized intersections.One reason for such interruptions is the inability to exchange real-time information between traditional human-driven vehicles and intersection infrastructure.Thus,this paper develops a Markov chain-based model to recognize platoons.A simulation experiment is performed in Vissim based on field data extracted from video recordings to prove the model’s applicability.The videos,recorded with a high-definition camera,contain field driving data from three Tesla vehicles,which can achieve Level 2 autonomous driving.The simulation results show that the recognition rate exceeds 80%when the connected and autonomous vehicle penetration rate is higher than 0.7.Whether a vehicle is upstream or downstream of an intersection also affects the performance of platoon recognition.The platoon recognition model developed in this paper can be used as a signal control input at intersections to reduce the unnecessary interruption of vehicle platoons and improve traffic efficiency.
基金supported by the National Natural Science Foundation of China(72001212,61773120)Hunan Postgraduate Research Innovation Project(CX20210031)+1 种基金the Foundation for the Author of National Excellent Doctoral Dissertation of China(2014-92)the Innovation Team of Guangdong Provincial Department of Education(2018KCXTD031)。
文摘How to make use of limited onboard resources for complex and heavy space tasks has attracted much attention.With the continuous improvement on satellite payload capacity and the increasing complexity of observation requirements,the importance of satellite autonomous task scheduling research has gradually increased.This article first gives the problem description and mathematical model for the satellite autonomous task scheduling and then follows the steps of"satellite autonomous task scheduling,centralized autonomous collaborative task scheduling architecture,distributed autonomous collaborative task scheduling architecture,solution algorithm".Finally,facing the complex and changeable environment situation,this article proposes the future direction of satellite autonomous task scheduling.
基金supported by the National Defense Science and Technology Innovation Zone of China (193-A13-203-01-01)the Military Science Postgraduate Project of PLA (JY2020B006)。
文摘Rich semantic information in natural language increases team efficiency in human collaboration, reduces dependence on high precision data information, and improves adaptability to dynamic environment. We propose a semantic centered cloud control framework for cooperative multi-unmanned ground vehicle(UGV) system. Firstly, semantic modeling of task and environment is implemented by ontology to build a unified conceptual architecture, and secondly, a scene semantic information extraction method combining deep learning and semantic web rule language(SWRL) rules is used to realize the scene understanding and task-level cloud task cooperation. Finally, simulation results show that the framework is a feasible way to enable autonomous unmanned systems to conduct cooperative tasks.
文摘After a brief emphasis about the interconnected world, including Cyber-Physical Systems of Systems, the increasing importance of the decision-making by autonomous, quasi-autonomous, and autonomic systems is emphasised. Promising roles of computational understanding, computational awareness, and computational wisdom for better autonomous decision-making are outlined. The contributions of simulation-based approaches are listed.
基金supported by the National Natural Science Foundation of China (6197317561973172)Tianjin Natural Science Foundation (19JCZDJC32800)。
文摘This paper proposes a liner active disturbance rejection control(LADRC) method based on the Q-Learning algorithm of reinforcement learning(RL) to control the six-degree-of-freedom motion of an autonomous underwater vehicle(AUV).The number of controllers is increased to realize AUV motion decoupling.At the same time, in order to avoid the oversize of the algorithm, combined with the controlled content, a simplified Q-learning algorithm is constructed to realize the parameter adaptation of the LADRC controller.Finally, through the simulation experiment of the controller with fixed parameters and the controller based on the Q-learning algorithm, the rationality of the simplified algorithm, the effectiveness of parameter adaptation, and the unique advantages of the LADRC controller are verified.
基金supported by the National Natural Science Foundation of China(62003267)the Natural Science Foundation of Shaanxi Province(2020JQ-220)the Open Project of Science and Technology on Electronic Information Control Laboratory(JS20201100339)。
文摘This paper presents a deep reinforcement learning(DRL)-based motion control method to provide unmanned aerial vehicles(UAVs)with additional flexibility while flying across dynamic unknown environments autonomously.This method is applicable in both military and civilian fields such as penetration and rescue.The autonomous motion control problem is addressed through motion planning,action interpretation,trajectory tracking,and vehicle movement within the DRL framework.Novel DRL algorithms are presented by combining two difference-amplifying approaches with traditional DRL methods and are used for solving the motion planning problem.An improved Lyapunov guidance vector field(LGVF)method is used to handle the trajectory-tracking problem and provide guidance control commands for the UAV.In contrast to conventional motion-control approaches,the proposed methods directly map the sensorbased detections and measurements into control signals for the inner loop of the UAV,i.e.,an end-to-end control.The training experiment results show that the novel DRL algorithms provide more than a 20%performance improvement over the state-ofthe-art DRL algorithms.The testing experiment results demonstrate that the controller based on the novel DRL and LGVF,which is only trained once in a static environment,enables the UAV to fly autonomously in various dynamic unknown environments.Thus,the proposed technique provides strong flexibility for the controller.
