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8th Symposium on Novel Photoelectronic Detection technology and Applications

作者： Li, Haitan Ding, Yan Huang, Xinliang Liang, Weidong Guo, Lingxi Key Laboratory of Dynamics and Control of Flight Vehicle Ministry of Education School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China Science and Technology on Space Physics Laboratory Beijing China

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

DenseFuse is a new approach for infrared and visible image fusion. Considering the single encoding strategy of DenseFuse, we propose a dual-encoder DenseNet (DEDNet), which develops a heterogenous image dual-encoder and a channel picking/Gaussian filtering based fusion strategy. The proposed method includes encoding layers, fusion strategy and decoder, in which encoding layers consist of dual encoders. Since infrared and visible images have different imaging mechanisms, the dual encoders can extract the features of infrared and visible images more effectively and improve the quality of fused images. The fusion strategy based on l1-norm's channel selection and Gaussian filtering improves the structural integrity and spatial correlation of the fused features. In the DEDNet, the infrared image is input to the infrared encoder to get the infrared features while the visible image is input to the visible encoder to get the visible features. Then, the fusion strategy fuses the infrared and visible features structurally and spatially. Finally, the decoder reconstructs the fused features to obtain the fused image. Experiments show that the DEDNet achieves competitive results in both subjective and objective evaluation metrics compared with other fusion approaches. © 2022 SPIE

关键词： Image fusion

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Optimal Multi-agent Collision-Free Path Planning with Temporal Logic Constraints 5th

Optimal Multi-agent Collision-Free Path Planning with Tempo...

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5th Chinese Conference on Swarm intelligence and Cooperative control, CCSICC 2021

作者： Zheng, Yiwei Liu, Zhaocong Lai, Aiwen Yu, Xiao Lan, Weiyao Department of Automation Xiamen University Fujian Xiamen361005 China The Science and Technology on Space Intelligent Control Laboratory Beijing Institute of Control Engineering Beijing100094 China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9789811939976

In this paper, we present a novel optimal multi-agent collision-free path planning algorithm (OMPATL) for the problem of multi-robot path planning with temporal logic constraints. Given a high-level mission specification in the form of linear temporal logic (LTL), OMPATL can automatically synthesize a set of trajectories for the multi-agent system (MAS), which achieves the collision avoidance among agents and minimizes the cost of the maximum traveling time between successive satisfactions. To synthesize the optimal trajectories, the motion of all agents, together with the mission area, is modeled as a weighted team transition system (TS) with a set of atomic propositions (APs). If the collision avoidance were not required, the optimal trajectories would be easily synthesized by an algorithm such as shortest paths. However, once the multi-agent systems are required to be safety-critical and collision-free, these trajectories may become infeasible. In OMPATL, a strategy is proposed for adding a set of transitions including "wait" and "go-back" to each individual TS based on the optimal run which does not consider collision avoidance. Then, the states and transitions with collisions can be removed such that the optimal collision-free trajectories are founded by the synthesis algorithm. The synthesized run balances collision avoidance, mission fulfillment, and optimality. The optimal run is synthesized offline and online adjustments are not needed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Motion planning

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UAV Path Planning from Human Demonstrations Using Inverse Reinforcement Learning

UAV Path Planning from Human Demonstrations Using Inverse R...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Xu, Zhiang Dong, Jin Hua, Yongzhao Dong, Xiwang Li, Qingdong Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China

ISBN: (纸本)9789811966125

In UAV path planning tasks, classical algorithms can only solve the tasks where environment is knowable and can be changed into mathematical model. For the tasks with unknown environment information is difficult to solve. However, such tasks can be easily solved by human. In this paper, we first bulid a UAV path planning environment and train the agent with deep reinforcement learning as human demonstration. Then, we use inverse reinforcement learning algorithm and processed human demonstrations to learn human policy. Finally, we test the trained policy in path planning tasks to verify the feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Distributed Time-Varying Optimization for a Class of Second-Order Multi-agent Systems with Disturbance

Distributed Time-Varying Optimization for a Class of Seco...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Su, Piaoyi Zheng, Hongwei Yu, Jianglong Hua, Yongzhao Dong, Xiwang Ren, Zhang School of Automation Science and Electronic Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China Institute of Artificial Intelligence Beihang University Beijing100191 China

ISBN: (纸本)9789811966125

This paper investigates the distributed convex time-varying optimization issue for multi-agent systems described by second-order with local disturbances produced by exosystems. Assuming each agent possessing a local cost function, the objective of this paper is to realize zero optimal tracking error considering the influences of extra disturbances and time-varying cost function simultaneously. Firstly, construst a local observer for each agent to obtain the accurate value of disturbance. Then, a distributed optimization algorithm is proposed to consensus optimal realization term. Thirdly, the system stability is confirmed by some Lyapunov-based analysis method. At last, in order to demonstrate the effectiveness of the proposed algorithm, a numerical simulation is constructed. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Cost functions

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SOM Neural Network Based Gaussian Mixture PHD Algorithm for Multi-Sensor Multi-Target Tracking

SOM Neural Network Based Gaussian Mixture PHD Algorithm for ...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Zhang, Yujie Zheng, Hongwei Zhang, Zheng Yu, Jianglong Hua, Yongzhao Dong, Xiwang Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China

ISBN: (纸本)9789811966125

In the multi-sensor multi-target tracking (MSMTT) problem, the matching of the measurements and the targets will generate a huge computational burden, resulting in an unsatisfactory real-time performance of the maneuvering targets tracking. In order to reduce the computational burden, this paper proposes a self-organizing feature map (SOM) neural network based Gaussian mixture probability hypothesis density algorithm (SOM-GMPHD). Firstly, a distributed filtering MSMTT algorithm based on SOM neural network is proposed. The distributed SOM-GMPHD algorithm (DSOM-GMPHD) has two fusion steps. Secondly, to further reduce the computational complexity, a centralized SOM-GMPHD algorithm (CSOM-GMPHD) with only one-step fusion is proposed. The computational complexity analysis of the existing MSMTT algorithms (DGMPHD and CGMPHD) and the proposed SOM-GMPHD algorithms are carried out in this paper. Finally, the effect of the proposed algorithms is evaluated in the simulation experiment. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Self organizing maps

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Improved Auction Algorithm for Weapon Target Assignment with Firepower-Health Model 42

Improved Auction Algorithm for Weapon Target Assignment with...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Shuobo Heng, Yong Hua, Yongzhao Dong, Xiwang Ren, Zhang Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Institute of Electronic System Engineering Beijing100854 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789887581543

This paper proposes an improved auction algorithm to optimize the efficiency of dynamic weapon target assignment (WTA) problem. Firstly, the dynamic battlefield environment of firepower-health model is analyzed and the constraints of weapon assignment problem are established. The firepower-health model is about the idea of adding constraints of weapon firepower and target health to promote the result of assignment more effectively. Secondly, in order to improve the computing speed of WTA algorithm, the penalty mechanism is introduced in the compensation auction algorithm. The main idea of improved algorithm is to reduce the extra consuming of the weapon during the assignment, from which penalty mechanism can optimize the assignment results and reduce the number of algorithm iterations by punishing the overkilled target under certain rules. Finally, the simulation results based on the dynamic firepower-health model show that the proposed algorithm can meet the requirements of firepower allocation, and can promote the effectiveness of assignment with high real-time response. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Dynamics

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In-Band Full-Duplex Communication for OFDM Integrated Sensing and Communication Systems

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IEEE Internet of Things Journal 2025年

作者： Duan, Baiyu Li, Tong Pan, Wensheng Zhou, Hui Shen, Ying Liu, Ying Shao, Shihai University of Electronic Science and Technology of China National Key Laboratory of Wireless Communications Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100089 China

In-band full-duplex (IBFD) integrated sensing and communication (ISAC) systems, where the base station (BS) simultaneously conducts the IBFD mode for both communication and sensing functions, increase spectral efficiency and reduce both communication and sensing latency. However, it is challenging to decouple the target echo and uplink communication signal at the digital domain of the receiver within serious self-interference (SI) from the transmitter. This paper investigates a digital canceller for IBFD ISAC systems with orthogonal frequency-division multiplexing (OFDM) waveform, enabling IBFD communication and sensing within the same time-frequency resource. With the proposed frequency-domain two-stage interference cancellation method, the ISAC receiver cancels the static interference and extracts the moving target echo signal for the sensing function. Subsequently, the uplink communication signal is decoupled after mitigating the target echo signal. Both sensing and communication performance are evaluated under different merits. Meanwhile, simulation and experiment results demonstrate the feasibility and effectiveness of the frequency-domain-canceller-enabling IBFD communication-based ISAC system. © 2014 IEEE.

关键词： Orthogonal frequency division multiplexing

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Event-Triggered Distributed Multisensor Multitarget Tracking with GM-PHD Filter

Event-Triggered Distributed Multisensor Multitarget Tracking...

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International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Qi, Jialin Zheng, Zhang Dong, Jin Hong, Jiang Xiwang, Dong Yu, Jianglong Zhang, Ren School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Academy of Blockchain and Edge Computing Beijing100086 China

ISBN: (纸本)9789811966125

This paper focuses on a distributed event-triggered Gaussian mixture probability hypothesis density (GM-PHD) filtering algorithm. In this algorithm, sensors transmit their Gaussian components to neighbors basing on the event-triggered conditions. Then Gaussian components are fused for certain times by matrix reformulation method. This algorithm can reduce data transmission and energy consumption with guaranteeing the estimation performance. Simulation experiment verifies the performance of this algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Matrix algebra

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Can Digital intelligence and Cyber-Physical-Social Systems Achieve Global Food Security and Sustainability?

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IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2070-2080页

作者： Yanfen Wang Mengzhen Kang Yali Liu Juanjuan Li Kai Xue Xiujuan Wang Jianqing Du Yonglin Tian Qinghua Ni Fei-Yue Wang College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049 Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408 State Key Laboratory of Tibetan Plateau Earth System Environment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Grassland Science Beijing Forestry UniversityBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXining 810016 Key Laboratory of Adaptation and Evolution of Plateau Biota Northwest Institute of Plateau BiologyChinese Academy of SciencesXining 810001 Binzhou Institute of Technology Weiqiao-UCAS Science and Technology ParkBinzhou 256606China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078 State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078 Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China IEEE

Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration *** the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the

关键词： Carbon-water balance decision-support digital intelligence(DI) foundation models planning

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Impact Angle control Guidance for a Moving Target with General Field-of-View Constraints 42

Impact Angle Control Guidance for a Moving Target with Gener...

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42nd Chinese control Conference, CCC 2023

作者： Tang, Xiangyu Yu, Jianglong Peng, Siting Dong, Xiwang Li, Qingdong Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China

ISBN: (纸本)9789887581543

This paper studies the impact angle control guidance problem with general field-of-view (FOV) constraints for a moving target. Firstly, the control Lyapunov function (CLF) is constructed based on the state-dependent Riccati equation (SDRE) technique, and a nominal controller is designed to intercept the moving target at the desired impact angle without FOV constraints. The control barrier functions (CBFs) are designed according to the FOV constraints. Secondly, the CLF that guarantees stability is combined with the CBFs that guarantee forward invariance of the constraint sets. The minimum modification framework is used to numerically solve the guidance command through quadratic programming to ensure that the look angle of the missile always remains within the constraint interval during the interception process. Finally, the effectiveness of the proposed guidance law is verified by numerical examples. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Electronic guidance systems

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