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Chinese intelligent systems Conference, CISC 2020

作者： Tong, Jiahui Liu, Jin Li, Jing Zhan, Tianming Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China TAIJI Computer Corporation Limited Beijing China

ISBN: (纸本)9789811584572

This paper analyzed the structure and characteristics of cooperative guidance system of aircraft formation, puts forward a multi-level simulation system architecture of centralized/distributed driving to solve the cooperative guidance for aircraft formation, realized the modeling of aircraft formation members and interaction by using multi-agent method, discussed the simulation methods of data link networking transmission and positioning, space-time registration of simulation system, and so on. The simulation is carried out based on a certain combat scenario, and the results show that the simulation system constructed in this paper can simulate the whole process of cooperative guidance of aircraft formation. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computer architecture

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Research on scattering characteristics of antenna array 4

Research on scattering characteristics of antenna array

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4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021

作者： Chen, Ao Zong, Xianzheng Nie, Zaiping Liu, Fan Wang, Youcheng Jiang, Peng School of Electronic Science and Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781733509619

A new RCS reduction method for the antenna array is proposed. Previous works have shown that the radiation pattern function of an antenna array is equal to the array element radiation pattern function multiplying the radiation array factor. Similarly, scattering factor is used to express an important parameter for analyzing the scattering characteristics of antenna arrays. The expression equation of the scattering factor of several conventional arrays can be derived directly, and then the maximum scattering direction of the antenna array can be obtained. In order to prove the validation of the scattering factor, several arrays are simulated by integral equation method, and finally proposed the condition of non-scattering-grating-lobe. © 2021 Applied Computational Electromagnetics Society (ACES).

关键词： Antenna arrays

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A Multi-Robot Task Allocation Method Based on Graph Attention Network and Unsupervised Learning

A Multi-Robot Task Allocation Method Based on Graph Attentio...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Zirui Wu Zhen Li Dong Zhu Qiuhan Liao Weiran Yao School of Astronautics Harbin Institute of Technology Harbin China Beijing Electro-Mechanical Engineering Institute Beijing China Chengdu CHG Robots & Intelligent Equipment Institute Co. Ltd Chengdu China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

The task allocation for multiple robots is a critical component in the coordination of unmanned clusters. The existing heuristic algorithms are hard to achieve satisfactory results in large-scale problems, and reinforcement learning-based methods face challenges in ensuring the rationality of reward design. This paper introduces a model based on multi-head attention and graph neural networks to address the schedule-dependent multi-robot task allocation problem, trained using unsupervised learning techniques. This model can be trained with varying numbers of robots and tasks without necessitating changes to its structure or parameters. In the experiment of this paper, the model is trained under two different conditions, and the performance is evaluated across six different problem scales. Comparing the proposed model against greedy algorithms and genetic algorithms, the results demonstrate that the proposed model has sianiflcant advantages in overall performance.

关键词： Greedy algorithms Robot kinematics Heuristic algorithms Computational modeling Reinforcement learning Graph neural networks Resource management Unsupervised learning Faces Genetic algorithms

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Safe RL-based Adaptive Cooperative Game control of Wing Deformation and Flight State Tracking for Morphing Hypersonic Vehicles

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Wang, Jun-Wei Wang, Feng Wu, Huai-Ning Liu, Zhou-Yang University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Hangzhou International Innovation Institute Hangzhou311115 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

This study addresses the issue of adaptive cooperative game control (ACGC) design for wing deformation and flight state tracking of morphing hypersonic vehicles (MHVs) with variable wing shapes, input constraints and state constraints. To access a better flight control performance, the wing deformation parameter is extended in this work as an auxiliary control input. An oriented-coordinated-control nonlinear differential equation model is first established to describe the complicated longitudinal flight state tracking error dynamics of the MHV. Then, a control barrier function (CBF) is introduced and incorporated into the value function as a risk penalty term of state security constraint. Based on the differential game (DG) theory, the optimal coordinated control problem for the MHV with input constraints and state constraints is treated as a constrained cooperative DG that is further formulated as a Hamilton-Jacobi-Bellman (HJB) equation with barrier and hyperbolic functions. A safe RL algorithm is proposed to solve the above HJB equation and an online Pareto joint control strategy is achieved thereby. Hereafter the stability analysis of the closed-loop state tracking error system is done by the Lyapunov technique. Meanwhile, both state and input constraints are met during the the parameter learning regulation process. At last, a simulation study is performed to support the proposed safe RL-ACGC algorithm. © 2025 IEEE.

关键词： Hyperbolic functions

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Visual Explanation of Object Detectors via Saliency Maps

Visual Explanation of Object Detectors via Saliency Maps

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Jin Xiao Wenrui Liu Xiaoguang Hu Hao Jiang Weipeng Wang Li Yahang State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Beihang University Beijing China The Third Academy of CASIC Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

In recent years, rapid progress of deep learning has resulted in object detection algorithms based on deep neural networks nearly completely replacing traditional methods. This shift has led to significant improvements in both accuracy and speed of object detection. However, deep neural networks that support decision-making inobject detection are complex black boxes with hidden internal logic and operations. This lack of transparency results in deep learning models being unexplainable, which limits their practical deployment. In this paper, we analyze the current state and future trends of interpretable technology in object detection and propose an effective object detection interpretable algorithm. This algorithm aims to explain the underlying logic of AI decision-making and provide support for the high performance and credibility of object detection algorithms based on deep neural networks through quantitative evaluation indicators.

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Prediction of Hybrid Asynchronous Frequency Hopping Pattern based on Deep Learning in Wideband Spectrum

Prediction of Hybrid Asynchronous Frequency Hopping Pattern ...

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Chinese Automation Congress (CAC)

作者： Ya Wang Jiaqi Wang Shuai Yuan Naijin Liu Yuanming Lu Qian Xuesen Laboratory of Space Technology China Academy of Space Technology Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China Unit 63893 of PLA Luoyang China

In non-cooperative scenarios, wideband frequency hopping (FH) communication reconnaissance including FH signal detection, parameter estimation, and network sorting under single-channel reception is challenging. The FH pattern contains the most information about FH signals. So it is the core of FH parameter estimation. Based on the task analysis, this paper proposes a blind prediction framework combining deep learning (DL) and clustering methods to improve the accuracy and efficiency of FH pattern estimation for mixed signals in the wideband spectrum. The unique advantage of this framework is that it requires no prior signal information and anchors but exploits the inherent time-frequency (TF) properties of asynchronous FH signals. It has a strong generalization ability and can adapt to signals of any shape. Moreover, a new comprehensive evaluation metric, normalized root mean square error including missed detection (NRMSE-MD), suitable for sequence data prediction is proposed to evaluate the level of missed detection and false detection in signal monitoring. Experimental results demonstrate the superiority of the proposed framework and the effectiveness of the proposed evaluation metric.

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Research on UAV Detection technology of Gm-APD Lidar Based on YOLO Model

Research on UAV Detection Technology of Gm-APD Lidar Based o...

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2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： DIng, Yuanxue Qu, Yanchen Zhang, Qing Tong, Jiahui Yang, Xianhui Sun, Jianfeng Harbin Institute of Technology National Key Laboratory of Science and Technology on Tunable Laser Institution of Opto-Electronics Harbin China Beijing Electromechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9780738146577

In recent years, unmanned aerial vehicle (UAV) technology has developed rapidly, which plays an important role in both military and civil fields. While it brings convenience to all walks of life, there are also a lot of security problems. Therefore, it is necessary to study anti-UAV technology, but the detection of UAV is an important basis of anti-UAV technology. In this paper, by combining the three-dimensional range profile collected by Gm-APD (Geiger mode Avalanche Photo Diode) lidar with the deep learning method, a UAV detection method based on the improved YOLOv3 (You Only Look Once v3) network is proposed. Firstly, the data of UAV in low altitude real scene is collected by Gm-APD lidar, and range profile information is generated. Then, the YOLOv3 network is improved, and the SPP module can be added to combine the local features of the target with the global features to improve the detection accuracy. It is suitable for the detection of UAVs. Finally, the trajectory of the UAV is drawn based on the distance information. The experimental results show that the improved method can effectively detect UAV targets, and is better than the previous method, YOLOv3-Tiny method and YOLOv4 method. The farthest detection distance is 238m, the detection speed is fast, and the purpose of real-time detection and positioning can be achieved. Therefore, this method can be applied to anti-UAV technology and has important research significance. © 2021 IEEE.

关键词： Optical radar

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A Hierarchical Graph Search Method for Path Planning of Unmanned Ground Vehicle for Freight Transportation

A Hierarchical Graph Search Method for Path Planning of Unma...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Jianing Hu Zhen Li Sen Guo Weiran Yao School of Astronautics Harbin Institute of Technology Harbin China Beijing Electro-Mechanical Engineering Institute Beijing China CRRC Nanjing Puzhen Co. Ltd Nanjing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

For the problem of collision volume change when forklift unmanned vehicles work in complex storage environments, a multi-level graph search path planning method is proposed. The first level is the path planning of the Unmanned Ground Vehicle (UGV) body, which uses the grid map and the A * algorithm to plan the path of the UGV transferring in the scene; the second level is the joint path planning of the UGV and the object being carried, to avoid overcomplicating this issue, the unmanned vehicle will be limited to pushing the cargo only forwards. The third level is the path planning when the unmanned vehicle carries multiple objects, which decomposes the whole scene into multiple sub-scenes, plans the paths of the unmanned vehicle in the sub-scenes separately, and searches for the optimal combination of sub-scenes. Higher level searches will invoke lower level algorithms and provide a virtual scene and target as input. The experimental results show that this multilevel path planning method is optimal and complete in solving the forklift unmanned vehicle for handling a single object, and can give a feasible solution for handling multiple objects.

关键词： Costs Transportation Search problems Path planning Land vehicles complexity theory Autonomous vehicles

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Distributed Finite-Time Cooperative Guidance Against a Moving Target: A Finite-Time Observer Approach

Distributed Finite-Time Cooperative Guidance Against a Movin...

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2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： Xiaofei, Dong Zhang, Ren School of Automation Science and Electrical Engineering Beihang University Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing China School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9780738146577

This paper investigates the cooperative guidance issue for multiple unmanned aerial vehicles (UAVs) for simultaneous attacks on maneuvering targets with a prescribed angle formation. Each UAV is accessible to the relative information with respect to the target while the absolute information of the target is unavailable. Also, each UAV just interacts with its neighbors locally. By introducing the integral sliding mode technique, a finite-time observer for the exact estimation of the absolute information of the target is designed. With the help of such an observer, a distributed cooperative guidance algorithm is developed such that both the time-to-go estimate consensus and angle formation objectives are achieved in finite time given that the undirected graph is connected. Finally, a simulation example is presented to validate the efficiency of the suggested guidance algorithm. © 2021 IEEE.

关键词： Antennas

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Research on Depth Estimation Method of Single Aerial Image

Research on Depth Estimation Method of Single Aerial Image

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IEEE Information technology, Networking, Electronic and Automation control Conference

作者： Wang Gao Lin Pu Lei Li Fei Deng Lingzhi Bie Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Institute of Mechanical and Electrical Engineering Beijing China School of Geodesy and Geomatics Wuhan University Wuhan China Wuhan Tianjihang Information Technology Co. Ltd Wuhan China

Aiming at the problem that the current depth estimation of single image mostly uses the ground public data set, and there is less research on aerial images, this paper uses the collected visible and infrared aerial image data sets to study the depth estimation. We used FCRN and LapDRN to extract the depth estimation results of visible aerial image and infrared aerial image under global and single object respectively, and compared the results extracted from the two types of networks by qualitative and quantitative methods. The results show that the depth estimation accuracy of visible aerial image is higher than that of infrared image, but the increase rate of infrared image accuracy index is higher than the increase rate of image depth range. The image depth estimation results extracted by LapDRN method are superior to FCRN in accuracy, structure consistency and edge clarity, which indicates that LapDRN is more effective in the estimation of aerial image depth information.

关键词： Automation Image edge detection Estimation Data mining Indexes

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