Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion pl...Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion planners is challenged.With the development of machine learning,the deep reinforcement learning(DRL)-based motion planner has gradually become a research hotspot due to its several advantageous feature.The DRL-based motion planner is model-free and does not rely on the prior structured map.Most importantly,the DRL-based motion planner achieves the unification of the global planner and the local planner.In this paper,we provide a systematic review of various motion planning methods.Firstly,we summarize the representative and state-of-the-art works for each submodule of the classical motion planning architecture and analyze their performance features.Then,we concentrate on summarizing reinforcement learning(RL)-based motion planning approaches,including motion planners combined with RL improvements,map-free RL-based motion planners,and multi-robot cooperative planning methods.Finally,we analyze the urgent challenges faced by these mainstream RLbased motion planners in detail,review some state-of-the-art works for these issues,and propose suggestions for future research.展开更多
As low-cost and highly autonomous ocean observation platforms,underwater gliders encounter risks during their launch and recovery,especially when coordinating multi-glider deployments.This work focuses on cooperative ...As low-cost and highly autonomous ocean observation platforms,underwater gliders encounter risks during their launch and recovery,especially when coordinating multi-glider deployments.This work focuses on cooperative path planning of an underwater glider fleet with simultaneous launch and recovery to enhance the autonomy of sampling and reduce deployment risks.Specifically,the gliders collaborate to achieve sampling considering the specified routines of interest.The overall paths to be planned are divided into four rectangular parts with the same starting point,and each glider is assigned a local sampling route.A clipped-oriented line-of-sight algorithm is proposed to ensure the coverage of the desired edges.The pitch angle of the glider is selected as the optimizing parameter to coordinate the overall progress considering the susceptibility of gliders to currents and the randomness of paths produced by complex navigational strategies.Therefore,a multi-actuation deep-Q network algorithm is proposed to ensure simultaneous launch and recovery.Simulation results demonstrate the acceptable effectiveness of the proposed method.展开更多
For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning...For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning. There are still lack of authoritative indicator and method for the cooperating path planning. The calculation of the voyage time is a difficult problem in the time-varying ocean, for the existing methods of the cooperating path planning, the computation time will increase exponentially as the autonomous underwater vehicle（AUV） counts increase, rendering them unfeasible. A collaborative path planning method is presehted for multi-AUV under the influence of time-varying ocean currents based on the dynamic programming algorithm. Each AUV cooperates with the one who has the longest estimated time of sailing, enabling the arrays of AUV to get their common goal in the shortest time with minimum timedifference. At the same time, they could avoid the obstacles along the way to the target. Simulation results show that the proposed method has a promising applicability.展开更多
Cooperative path planning is an important area in fixed-wing UAV swarm.However,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic environment.Fir...Cooperative path planning is an important area in fixed-wing UAV swarm.However,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic environment.Firstly,a normalized artificial potential field optimization is proposed by reconstructing a novel function with anisotropy in each dimension,which can make the flight speed of a fixed UAV swarm independent of the repulsive/attractive gain coefficient and avoid trapping into local optimization and local oscillation.Then,taking into account minimum velocity and turning angular velocity of fixed-wing UAV swarm,a strategy of decomposing target vector to avoid moving obstacles and pop-up threats is proposed.Finally,several simulations are carried out to illustrate superiority and effectiveness.展开更多
Cooperative planning is one of the critical problems in the field of multi-agent system gaming.This work focuses on cooperative planning when each agent has only a local observation range and local communication.We pr...Cooperative planning is one of the critical problems in the field of multi-agent system gaming.This work focuses on cooperative planning when each agent has only a local observation range and local communication.We propose a novel cooperative planning architecture that combines a graph neural network with a task-oriented knowledge fusion sampling method.Two main contributions of this paper are based on the comparisons with previous work:(1)we realize feasible and dynamic adjacent information fusion using GraphSAGE(i.e.,Graph SAmple and aggreGatE),which is the first time this method has been used to deal with the cooperative planning problem,and(2)a task-oriented sampling method is proposed to aggregate the available knowledge from a particular orientation,to obtain an effective and stable training process in our model.Experimental results demonstrate the good performance of our proposed method.展开更多
Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Trac...Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Tracking(HPT) method, to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems is developed. In the homogenization layer, any towed aircraft system involved in the sortie task is abstracted into a virtual taxiing aircraft. This layer transforms the heterogeneous systems into a homogeneous configuration. Then in the planning layer, a centralized optimal control problem is formulated for the homogeneous system. Compared with conducting the path planning directly with the original heterogeneous system, the homogenization layer contributes to reduce the dimension and nonlinearity of the formulated optimal control problem in the planning layer and consequently improves the robustness and efficiency of the solution process. Finally, in the tracking layer, a receding horizon controller is developed to track the reference trajectory obtained in the planning layer. To improve the tracking performance,multi-objective optimization techniques are implemented offline in advance to determine optimal weight parameters used in the tracking layer. Simulations demonstrate that smooth and collision-free cooperative trajectory can be generated efficiently in the planning phase. And robust trajectory tracking can be realized in the presence of external disturbances in the tracking phase.The developed HPT method provides a promising solution to the autonomous deck dispatch for unmanned carrier aircraft in the future.展开更多
Cooperative guidance strategy for multiple hypersonic gliding vehicles system with flight constraints and cooperative constraints is investigated.This paper mainly cares about the coordination of the entry glide fligh...Cooperative guidance strategy for multiple hypersonic gliding vehicles system with flight constraints and cooperative constraints is investigated.This paper mainly cares about the coordination of the entry glide flight phase and driving-down phase.Different from the existing results,both the attack time and the attack angle constraints are considered simultaneously.Firstly, for the entry glide flight phase, a two-stage method is proposed to achieve the rapid cooperative trajectories planning, where the control signal corridors are designed based on the quasi-equilibrium gliding conditions.In the first stage, the bank angle curve is optimized to achieve the attack angle coordination.In the second stage, the angle of attack curve is optimized to achieve the attack time coordination.The optimized parameters can be obtained by the secant method.Secondly, for the driving-down phase, the cooperative terminal guidance law is designed where the terminal attack time and attack angle are considered.The guidance law is then transformed into the bank angle and angle of attack commands.The cooperative guidance strategy is summarized as an algorithm.Finally, a numerical simulation example with three hypersonic gliding vehicles is provided for revealing the effectiveness of the acquired strategy and algorithm.展开更多
With the development of vehicle-to-vehicle(V2V)communication,it is possible to share information among multiple vehicles.However,the existing research on automated lane changes concentrates only on the single-vehicle ...With the development of vehicle-to-vehicle(V2V)communication,it is possible to share information among multiple vehicles.However,the existing research on automated lane changes concentrates only on the single-vehicle lane change with self-detective information.Cooperative lane changes are still a new area with more complicated scenarios and can improve safety and lane-change efficiency.Therefore,a multi-vehicle cooperative automated lane-change maneuver based on V2V communication for scenarios of eight vehicles on three lanes was proposed.In these scenarios,same-direction and intersectant-direction cooperative lane changes were defined.The vehicle that made the cooperative decision obtained the information of surrounding vehicles that were used to cooperatively plan the trajectories,which was called cooperative trajectory planning.The cooperative safety spacing model was proposed to guarantee and improve the safety of all vehicles,and it essentially developed constraints for the trajectory-planning task.Trajectory planning was treated as an optimization problem with the objective of maximizing safety,comfort,and lane-change efficiency under the constraints of vehicle dynamics and the aforementioned safety spacing model.Trajectory tracking based on a model predictive control method was designed to minimize tracking errors and control increments.Finally,to verify the validity of the proposed maneuver,an integrated simulation platform combining MATLAB/Simulink with CarSim was established.Moreover,a hardware-in-the-loop test bench was performed for further verification.The results indicated that the proposed multi-vehicle cooperative automated lane-change maneuver can achieve lane changes of multiple vehicles and increase lane-change efficiency while guaranteeing safety and comfort.展开更多
Folowing the establishment of free trade zones（FTZs）,China has selected 12 cities and areas to try out a new open-economy system which is more open to foreign collaboration,Shen Danyang,spokesman of the Ministry of ...Folowing the establishment of free trade zones（FTZs）,China has selected 12 cities and areas to try out a new open-economy system which is more open to foreign collaboration,Shen Danyang,spokesman of the Ministry of Commerce,announced on May 17 at a press briefing.展开更多
基金supported by the National Natural Science Foundation of China (62173251)the“Zhishan”Scholars Programs of Southeast University+1 种基金the Fundamental Research Funds for the Central UniversitiesShanghai Gaofeng&Gaoyuan Project for University Academic Program Development (22120210022)
文摘Motion planning is critical to realize the autonomous operation of mobile robots.As the complexity and randomness of robot application scenarios increase,the planning capability of the classical hierarchical motion planners is challenged.With the development of machine learning,the deep reinforcement learning(DRL)-based motion planner has gradually become a research hotspot due to its several advantageous feature.The DRL-based motion planner is model-free and does not rely on the prior structured map.Most importantly,the DRL-based motion planner achieves the unification of the global planner and the local planner.In this paper,we provide a systematic review of various motion planning methods.Firstly,we summarize the representative and state-of-the-art works for each submodule of the classical motion planning architecture and analyze their performance features.Then,we concentrate on summarizing reinforcement learning(RL)-based motion planning approaches,including motion planners combined with RL improvements,map-free RL-based motion planners,and multi-robot cooperative planning methods.Finally,we analyze the urgent challenges faced by these mainstream RLbased motion planners in detail,review some state-of-the-art works for these issues,and propose suggestions for future research.
基金supported by the National Natural Science Foundation of China(No.51909252)the Fundamental Research Funds for the Central Universities(No.202061004)This work is also partly supported by the China Scholar Council.
文摘As low-cost and highly autonomous ocean observation platforms,underwater gliders encounter risks during their launch and recovery,especially when coordinating multi-glider deployments.This work focuses on cooperative path planning of an underwater glider fleet with simultaneous launch and recovery to enhance the autonomy of sampling and reduce deployment risks.Specifically,the gliders collaborate to achieve sampling considering the specified routines of interest.The overall paths to be planned are divided into four rectangular parts with the same starting point,and each glider is assigned a local sampling route.A clipped-oriented line-of-sight algorithm is proposed to ensure the coverage of the desired edges.The pitch angle of the glider is selected as the optimizing parameter to coordinate the overall progress considering the susceptibility of gliders to currents and the randomness of paths produced by complex navigational strategies.Therefore,a multi-actuation deep-Q network algorithm is proposed to ensure simultaneous launch and recovery.Simulation results demonstrate the acceptable effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(5110917951179156+2 种基金5137917661473233)the Natural Science Basic Research Plan in Shaanxi Province of China(2014JQ8330)
文摘For low-speed underwater vehicles, the ocean currents has a great influence on them, and the changes in ocean currents is complex and continuous, thus whose impact must be taken into consideration in the path planning. There are still lack of authoritative indicator and method for the cooperating path planning. The calculation of the voyage time is a difficult problem in the time-varying ocean, for the existing methods of the cooperating path planning, the computation time will increase exponentially as the autonomous underwater vehicle（AUV） counts increase, rendering them unfeasible. A collaborative path planning method is presehted for multi-AUV under the influence of time-varying ocean currents based on the dynamic programming algorithm. Each AUV cooperates with the one who has the longest estimated time of sailing, enabling the arrays of AUV to get their common goal in the shortest time with minimum timedifference. At the same time, they could avoid the obstacles along the way to the target. Simulation results show that the proposed method has a promising applicability.
文摘Cooperative path planning is an important area in fixed-wing UAV swarm.However,avoiding multiple timevarying obstacles and avoiding local optimum are two challenges for existing approaches in a dynamic environment.Firstly,a normalized artificial potential field optimization is proposed by reconstructing a novel function with anisotropy in each dimension,which can make the flight speed of a fixed UAV swarm independent of the repulsive/attractive gain coefficient and avoid trapping into local optimization and local oscillation.Then,taking into account minimum velocity and turning angular velocity of fixed-wing UAV swarm,a strategy of decomposing target vector to avoid moving obstacles and pop-up threats is proposed.Finally,several simulations are carried out to illustrate superiority and effectiveness.
基金Project supported by the National Natural Science Foundation。
文摘Cooperative planning is one of the critical problems in the field of multi-agent system gaming.This work focuses on cooperative planning when each agent has only a local observation range and local communication.We propose a novel cooperative planning architecture that combines a graph neural network with a task-oriented knowledge fusion sampling method.Two main contributions of this paper are based on the comparisons with previous work:(1)we realize feasible and dynamic adjacent information fusion using GraphSAGE(i.e.,Graph SAmple and aggreGatE),which is the first time this method has been used to deal with the cooperative planning problem,and(2)a task-oriented sampling method is proposed to aggregate the available knowledge from a particular orientation,to obtain an effective and stable training process in our model.Experimental results demonstrate the good performance of our proposed method.
基金the National Key Research and Development Plan,China(No.2019YFB1706502)the National Natural Science Foundation of China(Nos.62003366,12102077,12072059)+1 种基金the China Postdoctoral Science Foundation(No.2020M670744)the Natural Science Foundation of Liaoning Province,China(No.2010-ZD-0021)。
文摘Taxiing aircraft and towed aircraft with drawbar are two typical dispatch modes on the flight deck of aircraft carriers. In this paper, a novel hierarchical solution strategy, named as the Homogenization-Planning-Tracking(HPT) method, to solve cooperative autonomous motion control for heterogeneous carrier dispatch systems is developed. In the homogenization layer, any towed aircraft system involved in the sortie task is abstracted into a virtual taxiing aircraft. This layer transforms the heterogeneous systems into a homogeneous configuration. Then in the planning layer, a centralized optimal control problem is formulated for the homogeneous system. Compared with conducting the path planning directly with the original heterogeneous system, the homogenization layer contributes to reduce the dimension and nonlinearity of the formulated optimal control problem in the planning layer and consequently improves the robustness and efficiency of the solution process. Finally, in the tracking layer, a receding horizon controller is developed to track the reference trajectory obtained in the planning layer. To improve the tracking performance,multi-objective optimization techniques are implemented offline in advance to determine optimal weight parameters used in the tracking layer. Simulations demonstrate that smooth and collision-free cooperative trajectory can be generated efficiently in the planning phase. And robust trajectory tracking can be realized in the presence of external disturbances in the tracking phase.The developed HPT method provides a promising solution to the autonomous deck dispatch for unmanned carrier aircraft in the future.
基金supported by the National Natural Science Foundation of China(Nos.61922008,61973013,61873011,61803014)the Innovation Zone Project of China(No.18-163-00-TS-001-001-34)+3 种基金the Beijing Natural Science Foundation of China(No.4182035)the Young Elite Scientists Sponsorship Program by CAST of China(No.017QNRC001)the Aeronautical Science Foundation of China(No.20170151001)the Special Research Project of Chinese Civil Aircraft,the State Key Laboratory of Intelligent Control and Decision of Complex Systems,the Key Laboratory of System Control and Information Processing,and the Shananxi Key Laboratory of Integrated and Intelligent Navigation(No.SKLIIN-20180105)。
文摘Cooperative guidance strategy for multiple hypersonic gliding vehicles system with flight constraints and cooperative constraints is investigated.This paper mainly cares about the coordination of the entry glide flight phase and driving-down phase.Different from the existing results,both the attack time and the attack angle constraints are considered simultaneously.Firstly, for the entry glide flight phase, a two-stage method is proposed to achieve the rapid cooperative trajectories planning, where the control signal corridors are designed based on the quasi-equilibrium gliding conditions.In the first stage, the bank angle curve is optimized to achieve the attack angle coordination.In the second stage, the angle of attack curve is optimized to achieve the attack time coordination.The optimized parameters can be obtained by the secant method.Secondly, for the driving-down phase, the cooperative terminal guidance law is designed where the terminal attack time and attack angle are considered.The guidance law is then transformed into the bank angle and angle of attack commands.The cooperative guidance strategy is summarized as an algorithm.Finally, a numerical simulation example with three hypersonic gliding vehicles is provided for revealing the effectiveness of the acquired strategy and algorithm.
基金This research was funded by the National Key R&D Program of China(Grant No.2016YFB0100905)the State Key Program of National Natural Science Foundation of China under Grant No.U1564208.
文摘With the development of vehicle-to-vehicle(V2V)communication,it is possible to share information among multiple vehicles.However,the existing research on automated lane changes concentrates only on the single-vehicle lane change with self-detective information.Cooperative lane changes are still a new area with more complicated scenarios and can improve safety and lane-change efficiency.Therefore,a multi-vehicle cooperative automated lane-change maneuver based on V2V communication for scenarios of eight vehicles on three lanes was proposed.In these scenarios,same-direction and intersectant-direction cooperative lane changes were defined.The vehicle that made the cooperative decision obtained the information of surrounding vehicles that were used to cooperatively plan the trajectories,which was called cooperative trajectory planning.The cooperative safety spacing model was proposed to guarantee and improve the safety of all vehicles,and it essentially developed constraints for the trajectory-planning task.Trajectory planning was treated as an optimization problem with the objective of maximizing safety,comfort,and lane-change efficiency under the constraints of vehicle dynamics and the aforementioned safety spacing model.Trajectory tracking based on a model predictive control method was designed to minimize tracking errors and control increments.Finally,to verify the validity of the proposed maneuver,an integrated simulation platform combining MATLAB/Simulink with CarSim was established.Moreover,a hardware-in-the-loop test bench was performed for further verification.The results indicated that the proposed multi-vehicle cooperative automated lane-change maneuver can achieve lane changes of multiple vehicles and increase lane-change efficiency while guaranteeing safety and comfort.
文摘Folowing the establishment of free trade zones（FTZs）,China has selected 12 cities and areas to try out a new open-economy system which is more open to foreign collaboration,Shen Danyang,spokesman of the Ministry of Commerce,announced on May 17 at a press briefing.
