In this paper,a cooperative region reconnaissance problem is investigated where a group of agents are required to fly across and detect events occur in an environment with static obstacles until an effective coverage ...In this paper,a cooperative region reconnaissance problem is investigated where a group of agents are required to fly across and detect events occur in an environment with static obstacles until an effective coverage is achieved.First,the region reconnaissance is formulated as a non-convex optimization problem.A coverage performance index with additional collision and obstacle avoidance constraints is given.Since the optimization index is an implicit function of state variables and cannot be used to compute gradients on state variables directly,an approximate optimization index is selected.Then,a non-convex optimization-based coverage algorithm is proposed to find the optimal reconnaissance location for each agent and guarantee no collisions trajectories among agents and obstacles.Finally,simulation experiments are performed to verify the effectiveness of the proposed approach.展开更多
A distributed self-control coverage method for mobile multi-target based on virtual force(MMTVF)is proposed to monitor dynamic targets using a mobile sensor network(MSN).The dynamic coverage method is introduced to ma...A distributed self-control coverage method for mobile multi-target based on virtual force(MMTVF)is proposed to monitor dynamic targets using a mobile sensor network(MSN).The dynamic coverage method is introduced to maintain network connectivity and optimize the coverage of moving targets.The method consists of two parts,one is the virtual force model which is proposed for motion control,and the other is the whale optimization algorithm which is improved to optimize node positions and achieve a steady state quickly.The virtual resultant force stretches the network towards uncovered targets using its multi-target attractive force,maintains network connectivity during network stretching using its attractive force,and prevents node collisions while nodes are moving using its repulsive force.The operating mechanism of the multi-target attractive force and other forces is thoroughly analyzed.Adjustment criteria for the model in different application scenarios are also provided.The comparisons demonstrate MMTVF has significant advantages over other similar approaches.展开更多
Dynamic area coverage with small unmanned aerial vehicle(UAV)systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process.Collaborative behavior of a ...Dynamic area coverage with small unmanned aerial vehicle(UAV)systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process.Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved.In this paper,we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems.The proposed decentralized decision-making dynamic area coverage(DDMDAC)method utilizes reinforcement learning(RL)where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable environment.Intelligent agents increase their global observations by gathering information about the environment by connecting with other agents.The connectivity provides a consensus for the decision-making process,while each agent takes decisions.At each step,agents acquire all reachable agents’states,determine the optimum location for maximal area coverage and receive reward using the covered rate on the target area,respectively.The method was tested in a multi-agent actor-critic simulation platform.In the study,it has been considered that each UAV has a certain communication distance as in real applications.The results show that UAVs with limited communication distance can act jointly in the target area and can successfully cover the area without guidance from the central command unit.展开更多
Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV...Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.展开更多
Beam hopping technology provides a foundation for the flexible allocation and efficient utilization of satellite resources,which is considered as a key technology for the next generation of high throughput satellite s...Beam hopping technology provides a foundation for the flexible allocation and efficient utilization of satellite resources,which is considered as a key technology for the next generation of high throughput satellite systems.To alleviate the contradiction between resource utilization and co-frequency interference in beam hopping technology,this paper firstly studies dynamic clustering to balance traffic between clusters and proposes cluster hopping pool optimization method to avoid inter-cluster interference.Then based on the optimization results,a novel joint beam hopping and precoding algorithm is provided to combine resource allocation and intra-cluster interference suppression,which can make efficient utilization of system resources and achieve reliable and near-optimal transmission capacity.The simulation results show that,compared with traditional methods,the proposed algorithms can dynamically adjust to balance demand traffic between clusters and meet the service requirements of each beam,also eliminate the co-channel interference to improve the performance of satellite network.展开更多
Using an integrated method combining wavelet analysis and non-parameter Mann-Kendall test, this paper analyzed spatial-temporal variations of vegetation cover in the Yellow River Basin based on SPOT-VEG images from 19...Using an integrated method combining wavelet analysis and non-parameter Mann-Kendall test, this paper analyzed spatial-temporal variations of vegetation cover in the Yellow River Basin based on SPOT-VEG images from 1998 to 2008 The results indicate： （1） Vegetation cover presented marked seasonal variation during the study period, with minima around winter and maxima in summer. The detail component D5 （with semi-period of 240 days） has presented a major contribution to the intra-armual variability. Forest vegetation presents a marked decreasing trend, while alpine shrubs, meadow, typical steppe, desert steppe, and forest （meadow） steppe vegetation all show a marked increasing trend. （2） Mean vegetation amount increased from the upper to lower reaches of the basin. It is low in the Ordos Plateau and Loess Plateau, and high in the southern Loess Plateau and the lower reaches. Amplitude of the annual phenological cycle pre- sents an opposite pattern in spatial distribution with that of the mean vegetation amount. （3） Vegetation cover presented a dominant positive inter-annual change trend, which implies that the eco-environment in the region has steadily improved. Only a few areas show a negative trend, which are located in the upper reaches and the southern Loess Plateau.展开更多
基金partially supported by the National Natural Science Foundation of China under Grant Nos.6147309961333001。
文摘In this paper,a cooperative region reconnaissance problem is investigated where a group of agents are required to fly across and detect events occur in an environment with static obstacles until an effective coverage is achieved.First,the region reconnaissance is formulated as a non-convex optimization problem.A coverage performance index with additional collision and obstacle avoidance constraints is given.Since the optimization index is an implicit function of state variables and cannot be used to compute gradients on state variables directly,an approximate optimization index is selected.Then,a non-convex optimization-based coverage algorithm is proposed to find the optimal reconnaissance location for each agent and guarantee no collisions trajectories among agents and obstacles.Finally,simulation experiments are performed to verify the effectiveness of the proposed approach.
文摘A distributed self-control coverage method for mobile multi-target based on virtual force(MMTVF)is proposed to monitor dynamic targets using a mobile sensor network(MSN).The dynamic coverage method is introduced to maintain network connectivity and optimize the coverage of moving targets.The method consists of two parts,one is the virtual force model which is proposed for motion control,and the other is the whale optimization algorithm which is improved to optimize node positions and achieve a steady state quickly.The virtual resultant force stretches the network towards uncovered targets using its multi-target attractive force,maintains network connectivity during network stretching using its attractive force,and prevents node collisions while nodes are moving using its repulsive force.The operating mechanism of the multi-target attractive force and other forces is thoroughly analyzed.Adjustment criteria for the model in different application scenarios are also provided.The comparisons demonstrate MMTVF has significant advantages over other similar approaches.
文摘Dynamic area coverage with small unmanned aerial vehicle(UAV)systems is one of the major research topics due to limited payloads and the difficulty of decentralized decision-making process.Collaborative behavior of a group of UAVs in an unknown environment is another hard problem to be solved.In this paper,we propose a method for decentralized execution of multi-UAVs for dynamic area coverage problems.The proposed decentralized decision-making dynamic area coverage(DDMDAC)method utilizes reinforcement learning(RL)where each UAV is represented by an intelligent agent that learns policies to create collaborative behaviors in partially observable environment.Intelligent agents increase their global observations by gathering information about the environment by connecting with other agents.The connectivity provides a consensus for the decision-making process,while each agent takes decisions.At each step,agents acquire all reachable agents’states,determine the optimum location for maximal area coverage and receive reward using the covered rate on the target area,respectively.The method was tested in a multi-agent actor-critic simulation platform.In the study,it has been considered that each UAV has a certain communication distance as in real applications.The results show that UAVs with limited communication distance can act jointly in the target area and can successfully cover the area without guidance from the central command unit.
基金National Natural Science Foundation of China(Grant No.52472417)to provide fund for conducting experiments.
文摘Complex multi-area collaborative coverage path planning in dynamic environments poses a significant challenge for multi-fixed-wing UAVs(multi-UAV).This study establishes a comprehensive framework that incorporates UAV capabilities,terrain,complex areas,and mission dynamics.A novel dynamic collaborative path planning algorithm is introduced,designed to ensure complete coverage of designated areas.This algorithm meticulously optimizes the operation,entry,and transition paths for each UAV,while also establishing evaluation metrics to refine coverage sequences for each area.Additionally,a three-dimensional path is computed utilizing an altitude descent method,effectively integrating twodimensional coverage paths with altitude constraints.The efficacy of the proposed approach is validated through digital simulations and mixed-reality semi-physical experiments across a variety of dynamic scenarios,including both single-area and multi-area coverage by multi-UAV.Results show that the coverage paths generated by this method significantly reduce both computation time and path length,providing a reliable solution for dynamic multi-UAV mission planning in semi-physical environments.
基金National Natural Science Foundation of China (No. 61901230, 61801445 and 91738201)Key pre-research project for civil space technology: Research project on VHTS communication technology (No. B0106)。
文摘Beam hopping technology provides a foundation for the flexible allocation and efficient utilization of satellite resources,which is considered as a key technology for the next generation of high throughput satellite systems.To alleviate the contradiction between resource utilization and co-frequency interference in beam hopping technology,this paper firstly studies dynamic clustering to balance traffic between clusters and proposes cluster hopping pool optimization method to avoid inter-cluster interference.Then based on the optimization results,a novel joint beam hopping and precoding algorithm is provided to combine resource allocation and intra-cluster interference suppression,which can make efficient utilization of system resources and achieve reliable and near-optimal transmission capacity.The simulation results show that,compared with traditional methods,the proposed algorithms can dynamically adjust to balance demand traffic between clusters and meet the service requirements of each beam,also eliminate the co-channel interference to improve the performance of satellite network.
基金supported by National Natural Science Foundation of China (Grant Nos. 41130525,41040015)
文摘Using an integrated method combining wavelet analysis and non-parameter Mann-Kendall test, this paper analyzed spatial-temporal variations of vegetation cover in the Yellow River Basin based on SPOT-VEG images from 1998 to 2008 The results indicate： （1） Vegetation cover presented marked seasonal variation during the study period, with minima around winter and maxima in summer. The detail component D5 （with semi-period of 240 days） has presented a major contribution to the intra-armual variability. Forest vegetation presents a marked decreasing trend, while alpine shrubs, meadow, typical steppe, desert steppe, and forest （meadow） steppe vegetation all show a marked increasing trend. （2） Mean vegetation amount increased from the upper to lower reaches of the basin. It is low in the Ordos Plateau and Loess Plateau, and high in the southern Loess Plateau and the lower reaches. Amplitude of the annual phenological cycle pre- sents an opposite pattern in spatial distribution with that of the mean vegetation amount. （3） Vegetation cover presented a dominant positive inter-annual change trend, which implies that the eco-environment in the region has steadily improved. Only a few areas show a negative trend, which are located in the upper reaches and the southern Loess Plateau.
