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2019 IEEE International Conference on Unmanned systems and Artificial Intelligence, ICUSAI 2019

作者： Zhou, Huan Su, Qian Fu, Wenxing Xu, Cheng Zheng, Meiyun Yang, Jingguang Aeronautical Engineering College Air Force Engineering University Xi'an China School of Astronautics Northwest Polytechnical University Xi'an China Unmanned System Research Institute Northwest Polytechnical University Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China School of Marine Science and Technology Northwest Polytechnical University Xi'an China Aviation Maintenance Sergeant School of Air Force Engineering University Xinyang China

ISBN: (纸本)9781728158594

In the process of formation cooperative autonomous flight and mission execution, multi-UAV systems have the characteristics of large disturbance, strong coupling of multi variables, high degree of uncertainty and complex cooperative factors, so there are many difficulties in the design of cooperative and intelligent control system. How to effectively develop the cooperative and intelligent technology of multi-UAV systems has become an urgent problem in the field of unmanned system and artificial intelligence. This paper first introduces the key technologies involved in UAV system at present, and then analyzes the challenges faced by the development of UAV system. Finally, it focuses on the development trend of multi-UAV systems cooperation and intelligent technology in the future. The research results have strong theoretical guidance significance for the cooperation and intelligent development of multi-UAV systems in China. © 2019 IEEE.

关键词： Flight control systems

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Meta-ZSDETR: Zero-shot DETR with Meta-learning

arXiv

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arXiv 2023年

作者： Zhang, Lu Zhang, Chenbo Zhao, Jiajia Guan, Jihong Zhou, Shuigeng Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China Department of Computer Science & Technology Tongji University China

Zero-shot object detection aims to localize and recognize objects of unseen classes. Most of existing works face two problems: the low recall of RPN in unseen classes and the confusion of unseen classes with background. In this paper, we present the first method that combines DETR and meta-learning to perform zero-shot object detection, named Meta-ZSDETR, where model training is formalized as an individual episode based meta-learning task. Different from Faster R-CNN based methods that firstly generate class-agnostic proposals, and then classify them with visual-semantic alignment module, Meta-ZSDETR directly predict class-specific boxes with class-specific queries and further filter them with the predicted accuracy from classification head. The model is optimized with meta-contrastive learning, which contains a regression head to generate the coordinates of class-specific boxes, a classification head to predict the accuracy of generated boxes, and a contrastive head that utilizes the proposed contrastive-reconstruction loss to further separate different classes in visual space. We conduct extensive experiments on two benchmark datasets MS COCO and PASCAL VOC. Experimental results show that our method outperforms the existing ZSD methods by a large margin. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

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Monocular visual based obstacle distance estimation method for ultra-low altitude flight

Monocular visual based obstacle distance estimation method f...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Jin Cheng Donghui Wei Wanchun Chen Wang Gao Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China School of Astronautics Beihang University Beijing China

ISBN: (纸本)9781728137933

This paper focuses on the problem of ultra-low-altitude flight obstacle distance estimation for monocular vision-assisted aircraft. First, the basic error model of distance estimation using sequence images is derived and the phenomenon of "epipole dead zone" is revealed. Then the distance estimation algorithm based on pairs of coplanar points is proposed as well as its error model. This algorithm is proved to be a solution of the "epipole dead zone" problem theoretically. Finally, numerical simulations show that the proposed distance estimation algorithm can effectively improve the accuracy of distance estimation in the "epipole dead zone".

关键词： Ultra-low altitude flight Monocular vision Distance estimation Monocular Vision error model flight altitude flight Death Dead

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A Method for Marine Ship Formation Intention Recognition based on BiConvLSTM-Attention

A Method for Marine Ship Formation Intention Recognition bas...

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Electronic Information Engineering and Computer science (EIECS), 2021 International Conference on

作者： Yunqiao Xi Junping Zhang Jian Liu Linlin Wang Hongfeng Xu Linxiu Chen Jixiang Jiang School of Electronics and Information Engineering Harbin Institute of Technology Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Institute of Electrical and Mechanical Engineering Beijing China

To solve the problem that current dynamic intention recognition methods fail to make full use of time domain variation information between multi-temporal group targets, which leads to low accuracy of intention recognition. This paper proposes a bidirectional convolutional long short term memory-attention network for marine formation target intention recognition. The network takes the multi-source trajectory data of the marine ship formation target as the input, extracts and uses the target change rule and time domain characteristics of the Marine formation data, and trains the model to have the ability to independently learn the weight of information in different time periods. The simulation results show that the method has good performance and can meet the needs of practical application.

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A Novel Relocating Recognition Algorithm in Overlapping Region for Multi-UAVs Cluster

A Novel Relocating Recognition Algorithm in Overlapping Regi...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Li, Chen Qi, Xuelei Zhao, Juntao Liao, Xuanhong Lin, Zitian Ma, Hongjun Liang, Xinkai College of Information Science and Engineering Northeastern University Shenyang China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong High School Attached to Northeast Normal University International Curriculum Center Changchun China School of Automation Science and Engineering South China University of Technology Guangzhou China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

How improve the mapping efficiency and location accuracy of the multi-UAV cluster based on the distributed SLAM technology is a significant problem in overlapping regions. Therefore, this paper mainly proposes a novel relocation recognition algorithm for the multi-UAV cluster. First, the autonomous localization algorithm based on visual-inertial fusion is proposed. Then, the algorithm for vocabulary updating and relocating is designed. Finally, practical testing is implemented to verify and improve the efficiency of exploration ability and the accuracy of the autonomous navigation and positioning in the complex overlapping regions. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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High precision test method and apparatus for photoelectric encoder

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Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of technology 2007年第11期27卷 977-980+1008页

作者： Deng, Fang Chen, Jie Chen, Wen-Jie Chi, Cheng Department of Automatic Control School of Information Science and Technology Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision School of Information Science and Technology Beijing Institute of Technology Beijing 100081 China

A new method and apparatus is proposed to improve the precision and reduce the cost of photoelectric encoder measurements. The method is based on highest resolution measurement and completely statistical analysis. The system includes a stepping motor, a high precision worm reduction gear, a high speed single chip microcomputer, a low cost incremental optical electric encoder and some multi interfaces of communication protocols. The single chip microcomputer as the lower system can test and collect the optical electric encoder. The PC computer as host-computer can deal with the test data. The precision of the system can reach 18 binary digits. Results of application in practice showed that the method and apparatus is efficient and effective, the cost of the apparatus is less than the some kind of system.

关键词： Photoelectric devices

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Credibility Evaluation of Aircraft HWIL Simulation Based on the Time-Varying Area Metric

Credibility Evaluation of Aircraft HWIL Simulation Based on ...

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High Performance and Smart Computing (HPSC), IEEE International Conference on

作者： Huapin Geng Ning Wang Jiahui Tong Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-mechanical Engineering Institute Beijing China Beijing Electro-mechanical Engineering Institute Beijing China

ISBN: (数字)9798350389463

ISBN: (纸本)9798350389470

Credibility evaluation of aircraft HWIL simulation is usually measured by the degree of consistency between simulation test data and the measured data. A new method for evaluating the credibility of aircraft HWIL simulation is established based on the idea of time-varying area measurement and uncertainty measurement Mainly for univariate, single simulation, multivariable and multi-simulation. The DTW distance measurement method is used to obtain the weight coefficients of correlated multiple response variables, and the effectiveness of uncertainty measurement method in obtaining the credibility of aircraft HWIL simulation at a certain level of confidence is verified through typical examples.

关键词： Weight measurement Uncertainty Correlation Area measurement Measurement uncertainty Distance measurement Indexes

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Model-free Based Reinforcement Learning control Strategy of Aircraft Attitude systems

Model-free Based Reinforcement Learning Control Strategy of ...

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Chinese Automation Congress (CAC)

作者： Dingcui Huang Jiangping Hu Zhinan Peng Bo Chen Mingrui Hao Bijoy Kumar Ghosh School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Texas Tech University Lubbock USA

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Traditional aircraft control algorithms have a strong dependence on system models, and are difficult to cope with the increasingly complex battlefield environment for intelligent aircrafts. In this paper, a model-free reinforcement learning is proposed to solve an attitude stabilization problem of an aircraft based online intelligent control strategy. The attitude control problem is firstly formulated as an optimal control problem, and then an adaptive dynamic programming (ADP) technology is applied to compute the corresponding nonlinear Hamilton-Jacobi-Bellman (HJB) equation. Then, an actor-critic neural network structure is established to learn the optimal controller online not requiring the information of the aircraft dynamics. The proposed intelligent control strategy enables the aircraft to adjust its attitude according to the actual mission targets and environments under the proposed online control strategy, so that autonomous learning and intelligent operation can be realized. Finally, simulation examples are presented to validate the proposed model-free based control strategy.

关键词： Atmospheric modeling Aircraft Adaptation models Mathematical model Aerodynamics Attitude control Vehicle dynamics

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SAR Image Registration Based on Feature Points Using Improved CSP-DenseNet

SAR Image Registration Based on Feature Points Using Improve...

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Pattern Recognition and Artificial Intelligence (PRAI), International Conference on

作者： Ziwei Wang Yanjiao Yang Guangzhou Qu Qingxi Chi Beijing Electro-Mechanical Engineering Institute Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

Synthetic aperture radar (SAR) image registration is widely used in integrated navigation system with development of guidance system in sensors and other applications. However, there exists some difficulty because of the quality and imaginary principle of SAR images. In this article, a brand-new method based on feature points using improved CSP-DenseNet is proposed to solve the problems of SAR image registration with weak and noisy texture. Deep features of interest points in SAR images are extracted using the proposed network from the crops of search image and template image respectively. The method has an advantage of preserving abundant feature information in SAR images under the influence of insufficient image information and noise of SAR images. The CSP-DenseNet architecture has a cross-stage construction optimizing fused by CSP-Net and DenseNet to extract matching features. The network is partially connected in specific convolutional layers for feature reusing and computation resources saving. Then, Brute Force Matcher and RANSAC voting are successively applied for a larger number of matching pairs and high-precise matching vertexes. Experimental results on various SAR image matching methods show that the proposed method provides better performance than other approaches compared.

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A strategy of multi-UAV cooperative path planning based on CCPSO

A strategy of multi-UAV cooperative path planning based on C...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Yuanna Liu Hao Lu dept. School of Electronics and Information Northwestern Polytechnical University Xi’an China dept. Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137933

Multi-UAV cooperative formation flying has significant advantages in broadening the scope of UAV operations and improving combat effectiveness. How to realize the cooperative path planning of multi-UAV is an open issue. In order to solve the search performance degradation as dimension increases, a strategy of multi-UAV cooperative path planning based on Cooperative Coevolution Particle Swarm Optimization (CCPSO) is proposed in this paper. Firstly, the initial Dubins path is generated for each UAV in the formation, of which the longest one is selected as the reference path. Intermediate waypoints are designed to modify the initial paths to avoid collisions with obstacles. Then, CCPSO algorithm is applied to optimize path parameters and adjust the path length to be equal to the reference path to ensure time coordination. Collision avoidance between UAVs is achieved in the collaborative evaluation phase. Finally, an formation rendezvous example and comparison with CCGA are given to explain the validity and excellent search ability of the proposed method.

关键词： Path planning Optimization Particle swarm optimization Safety Unmanned aerial vehicles Collision avoidance Planning

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