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42nd Chinese control Conference, CCC 2023

作者： Siting, Peng Lei, Li Zhu, Hongbo Jun, Ren Zhichao, Song Yang, Jiabing The Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beihang University School of Electronics and Information Engineering Beijing China

ISBN: (纸本)9789887581543

In the engineering field, there is a requirement for re recognition, including the identity recognition of cooperative and non-cooperative targets, that is, different sensors shoot targets in the same scene, and the identity recognition of targets from two perspectives is required, also known as target accurate retrieval. This method is widely used in fields such as automatic driving and military strikes. In the actual application scenario, deploying the re-recognition algorithm on the embedded processor needs to ensure the real-time computing speed and accuracy, so the complexity of the deep learning algorithm must be reduced, and pruning and lightweight processing are required. In the engineering field, when the image acquired by the sensor is subject to natural interference such as cloud and fog weather or fire and smoke, the difficulty of re-recognition increases. This paper adopts the lightweight improvement of ConvNeXt network model, and fine-tuned it on the basis of its original feature extraction function, so that it can successfully migrate to infrared image classification and also complete the extraction of infrared image target detail distinguishing features, and at the same time introduce the alignment of similar targets in infrared cross-view recognition. In the original similarity calculation, the average value is directly obtained from the spatial dimension of the output feature layer, which is replaced by the weight of the position in each space for estimation. The feature information of the multi-view marine ship target is extracted from the multi-sensor marine image, and its similarity is calculated, so as to determine the identity, thus reducing the support conditions and reconnaissance costs, and improving the accurate detection and tracking ability under the diverse dynamic reconnaissance conditions. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Feature extraction

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Tightly-Coupled Lidar-Visual-Inertial Odometry and Mapping in Real Time 42

Tightly-Coupled Lidar-Visual-Inertial Odometry and Mapping i...

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42nd Chinese control Conference, CCC 2023

作者： Ma, Wenyu Tian, Bailing Lu, Hanchen Shen, Hongming School of Electrical and Information Engineering Tianjin University Tianjin300072 China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

We proposed a tightly-coupled Lidar-visual-inertial odometry and mapping method, which takes advantage of measurement of Lidar, visual and inertial sensors to achieve highly accurate, real-time 6DoF state estimation and map-building in GNSS-denied environments. The proposed odometry is a tightly-coupled optimization-based method, obtains robust and low drift odometry by fusing pre-integrated IMU measurements, visual features from the image, and geometric features from Lidar data. Further, we adapt an online method to mitigate degeneracy in optimization problems to improve robustness in environmentally degenerate cases. Simulation and real-world experiments show that the proposed method exhibits similar or better robustness and accuracy with the state-of-the-art SLAM methods. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Optical radar

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Safe Tracker: A Robust Aerial system for Safe Tracking in Cluttered Environments 42

Safe Tracker: A Robust Aerial System for Safe Tracking in Cl...

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42nd Chinese control Conference, CCC 2023

作者： Hui, Yulin Tian, Bailing Zhang, Xuewei Lu, Hanchen Shen, Hongming School of Electrical and Information Engineering Tianjin University Tianjin300072 China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789887581543

This paper proposes Safe Tracker, an autonomous aerial tracking framework based on vision sensor that can deal with challenging tracking missions and guarantee safety and visibility. Firstly, a RGB-D sensor based segmentation method is employed to locate the target in real-time. Then target motion is predicted for a short time horizon, based on which a heuristic path searching method is applied to generate an occlusion-free path. Finally, particular formulations to balance visibility and safety are designed, and an effective non-linear trajectory optimization method enables to generate an optimal tracking trajectory. Autonomous aerial tracking experiments using a vision sensor are conducted to demonstrate the effectiveness of the proposed Safe Tracker in a challenging cluttered forest and a room full of sharp turns using Gazebo. Benchmark comparisons validate that our method tracks more safely and robustly than the state-of-art method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Trajectories

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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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2023 China Automation Congress, CAC 2023

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

ISBN: (纸本)9798350303759

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. © 2023 IEEE.

关键词： Forecasting

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An Optimized One-Stage Detector for Autonomous PV Defect Detection

An Optimized One-Stage Detector for Autonomous PV Defect Det...

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International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Huidi, Xiao Jiajia, Zhao Lihui, Wang Qiucheng, Shen Nongjie, Ma Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of Education School of Instrument Science and Engineering Southeast University Nanjing210096 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China School of Mechanical and Electronic Control Engineering Beijing Jiaotong University Beijing China

ISBN: (纸本)9789811694912

To realize the defect detection of Photovoltaic (PV) modules based on infrared images, a one-stage detector based on FPT and loss function optimization is proposed. Firstly, ResNet50 is selected as the backbone network for feature extraction, combining with the idea of migration learning to strengthen its feature extraction ability. Besides, replacing the traditional feature pyramid with FPT, using Transformer structure help realize the interaction of the same position between different pyramid layers as well as different positions of the same layer, improving the feature fusion capability of the model. Finally, to alleviate the problem of suppression of non-optimal predictions by NMS strategy, a bipartite graph matching algorithm based on loss function minimization is designed to enhance the learning of the distribution of ground truth targets by the network. The dataset is expanded by Mosaic data enhancement method for model training, so as to achieve infrared image-based PV defect detection. Results show that the improved one-stage target detection network has a promising detection effect on PV module defects under infrared images, with the average accuracy improving by 2.20% compared with the original algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Defects

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The Research on Simulation technology for multi-aircraft cooperative guidance

The Research on Simulation Technology for multi-aircraft coo...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Li Jing Shen Chao Tong JiaHui Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

In this paper, the composition and operation mechanism of a multi-aircraft cooperative simulation system is analyzed, with its formal architecture identified as a discrete event system & differential equation system specifications (DEV&DESS). Then, the operation and control problem of the cooperative simulation system is converted into the simulation control problem of a specific DEV&DESS system. A coordinator-based test method for cooperative simulation is proposed and validated by tests of real-time mathematical simulation.

关键词： aircraft control control system synthesis differential equations discrete event simulation discrete event systems Aircraft control discrete event systems control system synthesis discrete event simulation Differential equations Simulation systems Differentiation Test Method

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Practical Distance-Based Formation Stabilization and Tracking of Nonholonomic Multi-agent systems 7th

Practical Distance-Based Formation Stabilization and Tracki...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Tang, Xiangyu Yu, Jianglong Dong, Xiwang Yang, Xiangyu Ren, Zhang School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Institute of Artificial Intelligence Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9789819733279

This paper investigates practical distance-based formation stabilization and tracking issues for nonholonomic multi-agent systems (MASs). Firstly, the agent’s nonholonomic kinematics is represented as a left invariant system on a Lie group. Through the introduction of an auxiliary state and a virtual control guided by the transverse function method, the original system is effectively converted into a fully actuated one. Secondly, under the assumption of infinitesimal and minimal rigidity in the graph, a gradient-descent-based virtual controller is devised for the transformed MASs, facilitating practical rigid formation stabilization. Thirdly, a discontinuous distributed velocity estimator is designed for formation tracking. The nonholonomic MASs achieve the desired formation shape while effectively tracking the reference trajectory. Finally, the effectiveness of the proposed method is verified by numerical examples. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multi agent systems

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Multi-Source Dynamic Time Series Data Processing Method Based on Comprehensive Weighted Fusion 12

Multi-Source Dynamic Time Series Data Processing Method Base...

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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2022

作者： Geng, Huapin Yuan, Feimeng Suo, Bin Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Electro-mechanical Engineering Institute Beijing China School of Mathematics Southwest Jiaotong University Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9781839538360

Aiming at the fusion problem of multi-source heterogeneous dynamic data sources, based on the subjective and objective comprehensive weighting idea, an efficient multi-source dynamic data fusion algorithm is proposed. First, the outlier detection method based on linear regression model is used to preprocess the multi-source dynamic time series data. Then, determine the weight of the dynamic data. The prior weight of the data source is determined by the AHP method, cyclic scoring method, etc., and the posterior weight is determined according to the similarity between the time series data. Based on the Euclidean distance, a similarity measure between different data sources and a similarity measure between different dynamic data samples are constructed respectively. The former is used for the fusion of dynamic data standard deviation expectations, and the latter is used for the fusion of mean expectations. Finally, the comprehensive weight of each dynamic time series of each data source is obtained, and the comprehensive weighted fusion method is used to obtain the expected value and standard deviation of the dynamic response. The analysis of the calculation example shows that the proposed algorithm has higher computational efficiency than the method that treats dynamic data as several discrete static data. © 2022 IEEE.

关键词： Data fusion

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Muscle-Synergy-Based Planning and Neural-Adaptive control for a Prosthetic Arm

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2021年第5期2卷 424-436页

作者： Li, Guoxin Li, Zhijun Li, Junjun Liu, Yueyue Qiao, Hong The Department of Automation University of Science and Technology of China Hefei230026 China The Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei230026 China The School of Automation Science and Engineering South China University of Technology Guangzhou511442 China The State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The Center for Excellence in Brain Science and Intelligence Technology Institute of Neuroscience Chinese Academy of Science Shanghai200031 China

Upper limb loss has significant effects on the individual's quality of life. Artificial prosthetic limbs as an alternative to the lost limb are designed to allow amputees to regain motor function. Motion classification via extracted surface electromyogram (sEMG) signals is widely utilized to realize a friendly human-robot interface in the control of the prosthesis. However, limited classification of discrete motion patterns from sEMG prevents intuitive motor control. Thus, instead of using discrete patterns, decoding the human intention continuously from sEMG would significantly benefit the prosthesis control. In this article, we propose a muscle-synergy-based intention decoding and motion planning that can model a broad set of complex upper limb movements as a combination of motor primitives. A novel muscle activation-to-force mapping model is developed to detect muscular effort of the healthy side to drive the affected side. A neural-network-approximation-based controller is developed for the bionic neuroprosthetic arm to execute the movement. Operational experiments with prosthetic movement control were performed on four healthy participants and an upper limb amputee participant. Results of controlling prosthetic arm (0.94 ± 0.02 of R2 in the horizontal reaching tasks and 0.95 ± 0.01 in the vertical reaching tasks for the healthy subjects, 0.95 and 0.97 for the amputee) demonstrate that our control method could successfully capture human movement intention and effectively control the movement of prosthesis. Impact Statement-Powered robotic prostheses have enabled individuals with limb amputations to regain motor function via motion intention decoding from extracting surface electromyogram signals. Most research works have provided human-robot interaction through motion classification obtained from pattern recognition using surface electromyogram signals and simple movement control. However, decoding the human intent continuously from surface electromyogram is con

关键词： Matrix algebra

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Refined recognition and intelligent smart interference of radar signal

Refined recognition and intelligent smart interference of ra...

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2019 IEEE International Conference on Unmanned systems, ICUS 2019

作者： Yuan, Jianquan Bu, Yunong Yang, Shuyuan Chi, Qingxi Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electro-Mechanical Engineering Institute Beijing China Xidian University Xi'an China

ISBN: (纸本)9781728137926

Facing the complex electromagnetic environment on the battlefield, how to effectively identify important radar signals by jammers and how to implement strong and effective electromagnetic interference to the enemy's huge radar detection system under the condition of limited jamming resources will be the difficult problems that need to be solved continuously in the electronic warfare field. The solution of these problems will be the premise of effective interference for wartime jammers. In this paper, the technical gap of traditional jammers is analyzed. For radar signal perception, a refined perception and recognition method is proposed, forming the algorithm idea of multi-scale feature extraction and recognition based on radar fingerprint and multi-channel integrated multi-label recognition and classification based on radar radiation source. For interference implementation, the idea of smart interference based on deep GAN is put forward, laying the ground for further research on cognitive electronic warfare. © 2019 IEEE.

关键词： III-V semiconductors

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