Wireless communication with unmanned aerial vehicles(UAVs) has aroused great research interest recently. This paper is concerned with the UAV's trajectory planning problem for secrecy energy efficiency maximizatio...Wireless communication with unmanned aerial vehicles(UAVs) has aroused great research interest recently. This paper is concerned with the UAV's trajectory planning problem for secrecy energy efficiency maximization(SEEM) in the UAV communication system. Specifically, we jointly consider the secrecy throughput and UAV's energy consumption in a three-node(fixed-wing UAV-aided source, destination, and eavesdropper) wiretap channel. By ignoring the energy consumption on radiation and signal processing, the system's secrecy energy efficiency is defined as the total secrecy rate normalized by the UAV's propulsion energy consumption within a given time horizon. Nonetheless, the SEEM problem is nonconvex and thus is intractable to solve. As a compromise, we propose an iterative algorithm based on sequential convex programming(SCP) and Dinkelbach's method to seek a suboptimal solution for SEEM. The algorithm only needs to solve convex problems, and thus is computationally efficient to implement. Additionally, we prove that the proposed algorithm has Karush-KuhnTucker(KKT) point convergence guarantee. Lastly, simulation results demonstrate the efficacy of our proposed algorithm in improving the secrecy energy efficiency for the UAV communication system.展开更多
Unmanned Aerial Vehicles(UAVs)acting as aerial users to access the cellular network form a promising solution to guarantee its safe and efficient operations via the high-quality communication.Due to the flexible mobil...Unmanned Aerial Vehicles(UAVs)acting as aerial users to access the cellular network form a promising solution to guarantee its safe and efficient operations via the high-quality communication.Due to the flexible mobility of UAVs and the coverage range limits of ground base station(GBS),the signalto-noise ratio(SNR)of the communication link between UAVs and GBS will fluctuate.It is an important requirement to maintain the UAV’s cellular connection to meet a certain SNR requirement during the mission for UAV flying from take off to landing.In this paper,we study an efficient trajectory planning method that can minimize a cellular-connected UAV’s mission completion time under the connectivity requirement.The conventional method to tackle this problem adopts graph theory or a dynamic programming method to optimize the trajectory,which generally incurs high computational complexities.Moreover,there is a nonnegligible performance gap compared to the optimal solution.To this end,we propose an iterative trajectory optimizing algorithm based on geometric planning.Firstly,we apply graph theory to obtain all the possible UAV-GBS association sequences and select the candidate association sequences based on the topological relationship among UAV and GBSs.Next,adopting the triangle inequality property,an iterative handover location design is proposed to determine the shortest flight trajectory with fast convergence and low computation complexity.Then,the best flight trajectory can be obtained by comparing all the candidate trajectories.Lastly,we revealed the tradeoff between mission completion time and flight energy consumption.Numerical results validate that our proposed solution can obtain the effectiveness with set accuracy and outperform against the benchmark schemes with affordable computation time.展开更多
Unmanned aerial vehicles(UAVs)have attracted growing research interests in recent years,which can be used as cost-effective aerial platforms to transmit collected data packets to ground access points(APs).Thus,it is c...Unmanned aerial vehicles(UAVs)have attracted growing research interests in recent years,which can be used as cost-effective aerial platforms to transmit collected data packets to ground access points(APs).Thus,it is crucial to investigate robust airto-ground(A2G)wireless links for high-speed UAVs.However,the A2G wireless link is unstable as it suffers from large path-loss and severe Doppler effect due to the high mobility of UAVs.In order to meet these challenges,we propose an orthogonal time frequency space(OTFS)-based UAV communication system to relief the Doppler effect.Besides,considering that the energy of UAV is limited,we optimize the trajectory planning of UAV to minimize the energy consumption under the constraints of bit error rate(BER)and transmission rate,where the Doppler compensation is taken into account.Simulation results show that the performance of OTFS-based UAV system is superior to orthogonal frequency division multiplexing(OFDM)-based UAV systems,which can accomplish transmission tasks over shorter distances with lower energy consumption.展开更多
Four-dimensional trajectory based operation(4D-TBO)is believed to enhance the planning and execution of efficient flights,reduce potential conflicts and resolve upcoming tremendous flight demand.Most of the 4D traject...Four-dimensional trajectory based operation(4D-TBO)is believed to enhance the planning and execution of efficient flights,reduce potential conflicts and resolve upcoming tremendous flight demand.Most of the 4D trajectory planning related studies have focused on manned aircraft instead of unmanned aerial vehicles(UAVs).This paper focuses on planning conflict-free 4D trajectories for fixed-wing UAVs before the departure or during the flight planning.A 4D trajectory generation technique based on Tau theory is developed,which can incorporate the time constraints over the waypoint sequence in the flight plan.Then the 4D trajectory is optimized by the particle swarm optimization(PSO)algorithm.Further simulations are performed to demonstrate the effectiveness of the proposed method,which would offer a good chance for integrating UAV into civil airspace in the future.展开更多
In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by ...In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by on-board sensors and upload to the UAVs through their allocated spectrum resource.We adopt the expected sum age of information(ESAoI)to measure the network-wide information freshness.ESAoI is jointly affected by both the UAVs trajectory and the resource allocation,which are coupled with each other and make the analysis of ESAoI challenging.To tackle this challenge,we introduce a joint trajectory planning and resource allocation procedure,where the UAVs firstly fly to their destinations and then hover to allocate resource blocks(RBs)during a time-slot.Based on this procedure,we formulate a trajectory planning and resource allocation problem for ESAoI minimization.To solve the mixed integer nonlinear programming(MINLP)problem with hybrid decision variables,we propose a TD3 trajectory planning and Round-robin resource allocation(TTPRRA).Specifically,we exploit the exploration and learning ability of the twin delayed deep deterministic policy gradient algorithm(TD3)for UAVs trajectory planning,and utilize Round Robin rule for the optimal resource allocation.With TTP-RRA,the UAVs obtain their flight velocities by sensing the locations and the age of information(AoI)of the vehicles,then allocate the RBs to the vehicles in a descending order of AoI until the remaining RBs are not sufficient to support another successful uploading.Simulation results demonstrate that TTP-RRA outperforms the baseline approaches in terms of ESAoI and average AoI(AAoI).展开更多
Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed,and the optimization goal is the shortest taxi time.Although it is easy to solve,it does not consider the changes in the ...Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed,and the optimization goal is the shortest taxi time.Although it is easy to solve,it does not consider the changes in the speed profile of the aircraft when turning,and the shortest taxi time does not necessarily bring the best taxi fuel consumption.In this paper,the number of turns is considered,and the improved A*algorithm is used to obtain the P static paths with the shortest sum of the straight-line distance and the turning distance of the aircraft as the feasible taxi paths.By balancing taxi time and fuel consumption,a set of Pareto optimal speed profiles are generated for each preselected path to predict the 4-D trajectory of the aircraft.Based on the 4-D trajectory prediction results,the conflict by the occupied time window in the taxiing area is detected.For the conflict aircraft,based on the priority comparison,the waiting or changing path is selected to solve the taxiing conflict.Finally,the conflict free aircraft taxiing path is generated and the area occupation time window on the path is updated.The experimental results show that the total taxi distance and turn time of the aircraft are reduced,and the fuel consumption is reduced.The proposed method has high practical application value and is expected to be applied in real-time air traffic control decision-making in the future.展开更多
To provide hexapod robots with strategies of locomotion planning, observation experiments were operated on a kind of ant with the use of high speed digital photography and computer assistant analysis. Through digitali...To provide hexapod robots with strategies of locomotion planning, observation experiments were operated on a kind of ant with the use of high speed digital photography and computer assistant analysis. Through digitalization of original analog video, locomotion characters of ants were obtained, the biomimetic foundation was laid for polynomial trajectory planning of multi-legged robots, which was deduced with mathematics method. In addition, five rules were concluded, which apply to hexapod robots marching locomotion planning. The first one is the fundamental strategy of multi-legged robots＇ leg trajectory planning. The second one helps to enhance the static and dynamic stability of multi-legged robots. The third one can improve the validity and feasibility of legs＇ falling points. The last two give criterions of multi-legged robots＇ toe trajectory figures and practical recommendatory constraints. These five rules give a good method for marching locomotion planning of multi-legged robots, and can be expended to turning planning and any other special locomotion.展开更多
In order to solve kinematic redundancy problems of a hydraulic quadruped walking robot,which include leg dragging,sliding,impingement against the ground,an improved gait planning algorithm for this robot is proposed i...In order to solve kinematic redundancy problems of a hydraulic quadruped walking robot,which include leg dragging,sliding,impingement against the ground,an improved gait planning algorithm for this robot is proposed in this paper.First,the foot trajectory is designated as the improved composite cycloid foot trajectory.Second,the landing angle of each leg of the robot is controlled to satisfy friction cone to improve the stability performance of the robot.Then with the controllable landing angle of quadruped robot and a geometry method,the kinematic equation is derived in this paper.Finally,agait planning method of quadruped robot is proposed,a dynamic co-simulation is done with ADAMS and MATLAB,and practical experiments are conducted.The validity of the proposed algorithm is confirmed through the co-simulation and experimentation.The results show that the robot can avoid sliding,reduce impingement,and trot stably in trot gait.展开更多
基金supported in part by the National Natural Science Foundation of China under Grant 61631004 and 61571089
文摘Wireless communication with unmanned aerial vehicles(UAVs) has aroused great research interest recently. This paper is concerned with the UAV's trajectory planning problem for secrecy energy efficiency maximization(SEEM) in the UAV communication system. Specifically, we jointly consider the secrecy throughput and UAV's energy consumption in a three-node(fixed-wing UAV-aided source, destination, and eavesdropper) wiretap channel. By ignoring the energy consumption on radiation and signal processing, the system's secrecy energy efficiency is defined as the total secrecy rate normalized by the UAV's propulsion energy consumption within a given time horizon. Nonetheless, the SEEM problem is nonconvex and thus is intractable to solve. As a compromise, we propose an iterative algorithm based on sequential convex programming(SCP) and Dinkelbach's method to seek a suboptimal solution for SEEM. The algorithm only needs to solve convex problems, and thus is computationally efficient to implement. Additionally, we prove that the proposed algorithm has Karush-KuhnTucker(KKT) point convergence guarantee. Lastly, simulation results demonstrate the efficacy of our proposed algorithm in improving the secrecy energy efficiency for the UAV communication system.
基金This work was supported by National Natural Science Foundation of China(NO.61703197 and NO.62061027).
文摘Unmanned Aerial Vehicles(UAVs)acting as aerial users to access the cellular network form a promising solution to guarantee its safe and efficient operations via the high-quality communication.Due to the flexible mobility of UAVs and the coverage range limits of ground base station(GBS),the signalto-noise ratio(SNR)of the communication link between UAVs and GBS will fluctuate.It is an important requirement to maintain the UAV’s cellular connection to meet a certain SNR requirement during the mission for UAV flying from take off to landing.In this paper,we study an efficient trajectory planning method that can minimize a cellular-connected UAV’s mission completion time under the connectivity requirement.The conventional method to tackle this problem adopts graph theory or a dynamic programming method to optimize the trajectory,which generally incurs high computational complexities.Moreover,there is a nonnegligible performance gap compared to the optimal solution.To this end,we propose an iterative trajectory optimizing algorithm based on geometric planning.Firstly,we apply graph theory to obtain all the possible UAV-GBS association sequences and select the candidate association sequences based on the topological relationship among UAV and GBSs.Next,adopting the triangle inequality property,an iterative handover location design is proposed to determine the shortest flight trajectory with fast convergence and low computation complexity.Then,the best flight trajectory can be obtained by comparing all the candidate trajectories.Lastly,we revealed the tradeoff between mission completion time and flight energy consumption.Numerical results validate that our proposed solution can obtain the effectiveness with set accuracy and outperform against the benchmark schemes with affordable computation time.
基金supported by the National Key Research and Development Program of China(Grant 2020YFB1804800)the National Natural Science Foundation of China(Grant U22B2008 and Grant 61922010)the Beijing Natural Science Foundation(Grant JQ20019)。
文摘Unmanned aerial vehicles(UAVs)have attracted growing research interests in recent years,which can be used as cost-effective aerial platforms to transmit collected data packets to ground access points(APs).Thus,it is crucial to investigate robust airto-ground(A2G)wireless links for high-speed UAVs.However,the A2G wireless link is unstable as it suffers from large path-loss and severe Doppler effect due to the high mobility of UAVs.In order to meet these challenges,we propose an orthogonal time frequency space(OTFS)-based UAV communication system to relief the Doppler effect.Besides,considering that the energy of UAV is limited,we optimize the trajectory planning of UAV to minimize the energy consumption under the constraints of bit error rate(BER)and transmission rate,where the Doppler compensation is taken into account.Simulation results show that the performance of OTFS-based UAV system is superior to orthogonal frequency division multiplexing(OFDM)-based UAV systems,which can accomplish transmission tasks over shorter distances with lower energy consumption.
文摘Four-dimensional trajectory based operation(4D-TBO)is believed to enhance the planning and execution of efficient flights,reduce potential conflicts and resolve upcoming tremendous flight demand.Most of the 4D trajectory planning related studies have focused on manned aircraft instead of unmanned aerial vehicles(UAVs).This paper focuses on planning conflict-free 4D trajectories for fixed-wing UAVs before the departure or during the flight planning.A 4D trajectory generation technique based on Tau theory is developed,which can incorporate the time constraints over the waypoint sequence in the flight plan.Then the 4D trajectory is optimized by the particle swarm optimization(PSO)algorithm.Further simulations are performed to demonstrate the effectiveness of the proposed method,which would offer a good chance for integrating UAV into civil airspace in the future.
基金supported in part by the Project of International Cooperation and Exchanges NSFC under Grant No.61860206005in part by the Joint Funds of the NSFC under Grant No.U22A2003.
文摘In this paper,multi-UAV trajectory planning and resource allocation are jointly investigated to improve the information freshness for vehicular networks,where the vehicles collect time-critical traffic information by on-board sensors and upload to the UAVs through their allocated spectrum resource.We adopt the expected sum age of information(ESAoI)to measure the network-wide information freshness.ESAoI is jointly affected by both the UAVs trajectory and the resource allocation,which are coupled with each other and make the analysis of ESAoI challenging.To tackle this challenge,we introduce a joint trajectory planning and resource allocation procedure,where the UAVs firstly fly to their destinations and then hover to allocate resource blocks(RBs)during a time-slot.Based on this procedure,we formulate a trajectory planning and resource allocation problem for ESAoI minimization.To solve the mixed integer nonlinear programming(MINLP)problem with hybrid decision variables,we propose a TD3 trajectory planning and Round-robin resource allocation(TTPRRA).Specifically,we exploit the exploration and learning ability of the twin delayed deep deterministic policy gradient algorithm(TD3)for UAVs trajectory planning,and utilize Round Robin rule for the optimal resource allocation.With TTP-RRA,the UAVs obtain their flight velocities by sensing the locations and the age of information(AoI)of the vehicles,then allocate the RBs to the vehicles in a descending order of AoI until the remaining RBs are not sufficient to support another successful uploading.Simulation results demonstrate that TTP-RRA outperforms the baseline approaches in terms of ESAoI and average AoI(AAoI).
基金supported by the National Key R&D Project(No.2020YFB1600101)National Natural Science Foundations of China(Nos.U1833103,71801215)Civil Aviation Flight Wide Area Surveillance and Safety Control Technology Key Laboratory Open Fund(No.202008)。
文摘Most of the traditional taxi path planning studies assume that the aircraft is in uniform speed,and the optimization goal is the shortest taxi time.Although it is easy to solve,it does not consider the changes in the speed profile of the aircraft when turning,and the shortest taxi time does not necessarily bring the best taxi fuel consumption.In this paper,the number of turns is considered,and the improved A*algorithm is used to obtain the P static paths with the shortest sum of the straight-line distance and the turning distance of the aircraft as the feasible taxi paths.By balancing taxi time and fuel consumption,a set of Pareto optimal speed profiles are generated for each preselected path to predict the 4-D trajectory of the aircraft.Based on the 4-D trajectory prediction results,the conflict by the occupied time window in the taxiing area is detected.For the conflict aircraft,based on the priority comparison,the waiting or changing path is selected to solve the taxiing conflict.Finally,the conflict free aircraft taxiing path is generated and the area occupation time window on the path is updated.The experimental results show that the total taxi distance and turn time of the aircraft are reduced,and the fuel consumption is reduced.The proposed method has high practical application value and is expected to be applied in real-time air traffic control decision-making in the future.
基金Sponsored by the Ministerial Level Advanced Research Foundation(65822576)
文摘To provide hexapod robots with strategies of locomotion planning, observation experiments were operated on a kind of ant with the use of high speed digital photography and computer assistant analysis. Through digitalization of original analog video, locomotion characters of ants were obtained, the biomimetic foundation was laid for polynomial trajectory planning of multi-legged robots, which was deduced with mathematics method. In addition, five rules were concluded, which apply to hexapod robots marching locomotion planning. The first one is the fundamental strategy of multi-legged robots＇ leg trajectory planning. The second one helps to enhance the static and dynamic stability of multi-legged robots. The third one can improve the validity and feasibility of legs＇ falling points. The last two give criterions of multi-legged robots＇ toe trajectory figures and practical recommendatory constraints. These five rules give a good method for marching locomotion planning of multi-legged robots, and can be expended to turning planning and any other special locomotion.
基金Supported by National High Technology Research and Development Program of China(863 Program)(2011AA041002)
文摘In order to solve kinematic redundancy problems of a hydraulic quadruped walking robot,which include leg dragging,sliding,impingement against the ground,an improved gait planning algorithm for this robot is proposed in this paper.First,the foot trajectory is designated as the improved composite cycloid foot trajectory.Second,the landing angle of each leg of the robot is controlled to satisfy friction cone to improve the stability performance of the robot.Then with the controllable landing angle of quadruped robot and a geometry method,the kinematic equation is derived in this paper.Finally,agait planning method of quadruped robot is proposed,a dynamic co-simulation is done with ADAMS and MATLAB,and practical experiments are conducted.The validity of the proposed algorithm is confirmed through the co-simulation and experimentation.The results show that the robot can avoid sliding,reduce impingement,and trot stably in trot gait.
