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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Adiyana Putri Ferio Brahmana Endra Joelianto Herman Y. Sutarto Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Artificial Intelligence Control and Automation Laboratory Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Department of Intelligent System PT. Pusat Riset Energi (PRE) Bandung Indonesia

ISBN: (纸本)9781665476881

The increasing vehicle volume every year affects the prediction of the traffic system. The purpose of predicting traffic flow is to estimate the lost data caused by sensor malfunctions due to connection disruptions or ages. In estimating traffic flow, obtaining and explaining the historical data from the nearest segment sensor is necessary. The graph model can describe the spatial relationship between segments by connecting nodes with edges. Graph Neural Network (GNN) has been used as a learning method to predict the traffic flow in the segment sensor. GNN gets input in the form of spatial data built through a graph model, and the features are traffic density, average vehicle speed, and delay time on the road network. This paper shows that GNN's capability performs better in extracting spatial features and predicting the traffic flow by aggregating the features through connectivity nodes and edges.

关键词： Learning systems Roads Estimation Feature extraction Robot sensing systems Graph neural networks Spatial databases

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A Reduced-Order Protocol for Bipartite Consensus of Linear Multi-Agent systems

A Reduced-Order Protocol for Bipartite Consensus of Linear M...

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Chinese automation Congress (CAC)

作者： Zichen Li Xianwei Li Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

ISBN: (数字)9781665426473

ISBN: (纸本)9781665426480

This paper proposes a new reduced-order dynamic output-feedback protocol to solve the bipartite consensus problem of homogeneous linear multi-agent systems. Necessary and sufficient conditions for the solvability of the bipartite consensus problem are derived and the consensus state trajectories are obtained in an explicit form. Compared with existing results, the novelties of the proposed protocol are two-fold: Firstly, the protocol relies on relative output information of agents within each group and secondly, the protocol state ultimately converges to zero if bipartite consensus is reached. Furthermore, a numerical example is given to show the effectiveness of the proposed protocol.

关键词： Sufficient conditions Protocols Laplace equations automation Directed graphs Eigenvalues and eigenfunctions Trajectory

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S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles

arXiv

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arXiv 2024年

作者： Wang, Xiao Tang, Ke Dai, Xingyuan Xu, Jintao Du, Quancheng Ai, Rui Wang, Yuxiao Gu, Weihao Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei230031 China Haomo Technology Co. Ltd. Beijing100192 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Qingdao Academy of Intelligent Industries Qingdao266114 China The School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

In public roads, autonomous vehicles (AVs) face the challenge of frequent interactions with human-driven vehicles (HDVs), which render uncertain driving behavior due to varying social characteristics among humans. To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S4TP) framework. Specifically, S4TP integrates the Social-Aware Trajectory Prediction (SATP) and Social-Aware Driving Risk Field (SADRF) modules. SATP utilizes Transformers to effectively encode the driving scene and incorporates an AV’s planned trajectory during the prediction decoding process. SADRF assesses the expected surrounding risk degrees during AVs-HDVs interactions, each with different social characteristics, visualized as two-dimensional heat maps centered on the AV. SADRF models the driving intentions of the surrounding HDVs and predicts trajectories based on the representation of vehicular interactions. S4TP employs an optimization-based approach for motion planning, utilizing the predicted HDVs’ trajectories as input. With the integration of SADRF, S4TP executes real-time online optimization of the planned trajectory of AV within low-risk regions, thus improving the safety and the interpretability of the planned trajectory. We have conducted comprehensive tests of the proposed method using the SMARTS simulator. Experimental results in complex social scenarios, such as unprotected left-turn intersections, merging, cruising, and overtaking, validate the superiority of our proposed S4TP in terms of safety and rationality. S4TP achieves a pass rate of 100% across all scenarios, surpassing the current state-of-the-art methods Fanta of 98.25% and Predictive-Decision of 94.75%. Copyright © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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An Integrated Model Combining CNN-GRU with ARIMA for pressure prediction of water supply network

An Integrated Model Combining CNN-GRU with ARIMA for pressur...

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第40届中国控制会议

作者： Bo Wang Miaoshun Bai Jingcheng Wang Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Municipal Engineering Design Institute (Group) Co. Ltd

In the problem of time series prediction, the accuracy has always been an enduring research hotspot. In this paper,we proposed an integrated model named CNN-GRU-ARIMA to improve the accuracy of pressure prediction for water supply network. The proposed model is mainly comprised of the two parts, namely ARIMA and CNN-GRU. The ARIMA is usually used for the univariate prediction, and the CNN-GRU represents the multivariate prediction model. Also, several metrics including MAE, RRSE, RMSE are exploited to facilitate quantitative analysis of the accuracy differences between different models mentioned. The experiments show that our proposed scheme adopted in integrated model can achieve the better performance than some state-of-the-art approaches.

关键词： Time series prediction CNN GRU ARIMA

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Influence of Si buffer layer on the crystal quality of SiGe films in Ge/Si/SiGe heterostructures: A molecular dynamics investigation

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Surface Science 2025年 761卷

作者： Jianan Xie Tao Lin Cailin Wang College of Automation and Information Engineering Xi’an University of Technology Xi’an 710048 China Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an 710048 China

SiGe materials have become a research hotspot due to their important applications in semiconductor devices, especially in optoelectronic and high-speed electronic devices. In this study, based on molecular dynamics simulations, the influence of the Si buffer layer on the quality of films in Ge/Si/SiGe heterostructures is investigated. By simulating the growth process of the Ge/Si/SiGe heterostructure, a deposition model based on Ge(100) substrates is established. Inspired by the concept of reverse gradient buffer layers, Si buffer layers are directly grown on Ge substrates, followed by the deposition of SiGe films. This study primarily investigates the effects of the growth temperature and deposition thickness of the Si buffer layer on the quality of SiGe films. Based on the deposition parameters identified as suitable under the current simulation conditions (620 °C, 9.7 nm), the influence of the buffer layer on SiGe films with varying Ge compositions is further analyzed. The results show that the dislocations and stacking faults formed in the Si buffer layer effectively relieve the stress caused by lattice mismatch, thus improving the crystal quality of the subsequent SiGe films. This study provides theoretical insights into the Ge/Si/SiGe heterostructure film growth process, which helps enhance the quality of SiGe films and expands their applications in semiconductor devices.

关键词： Lattice mismatch

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Spatial-nonlocality-induced non-Markovian electromagnetically induced transparency in a single giant atom

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Physical Review A 2022年第4期106卷 043710-043710页

作者： Y. T. Zhu S. Xue R. B. Wu W. L. Li Z. H. Peng M. Jiang Department of Automation Shanghai Jiao Tong University Shanghai 200240 People's Republic of China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 People's Republic of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 People's Republic of China Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing 100084 People's Republic of China Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Key Laboratory for Matter Microstructure and Function of Hunan Province Department of Physics and Synergetic Innovation Center for Quantum Effects and Applications Hunan Normal University Changsha 410081 People's Republic of China School of Electronics and Information Engineering Soochow University Suzhou 215006 People's Republic of China

The nonlocal waveguide coupling of giant atoms can bring up novel physics and applications. In this paper, we find unconventional electromagnetically induced transparency in giant atoms that has not been reported so far. We present a consistent theory for describing the unconventional EIT which includes a real-space scattering method and a time-delayed master equation. Our analysis shows this phenomenon is a full quantum effect led by a quantized interaction between the atom and the waveguide. Our theory shows that it can be observed when the time delay between two neighboring coupling points is comparable to the relaxation time of the atom. This phenomenon results from the inherent nonlocality of the giant atom, which physically forces propagating fields to be standing waves in space and the atom exhibiting retardations in time.

关键词： Quantum optics with artificial atoms Scattering theory Quantum master equation

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An enhanced algorithm for cell-level anomaly segmentation in photovoltaic solar panels using electroluminescence imaging

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Energy 2025年 331卷

作者： Ruiyao Duan Yongjian Wang Xisong Chen Shihua Li School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing 210096 PR China Institute for Automatic Control and Complex System University of Duisburg–Essen Duisburg 47057 Germany

Electroluminescence imaging is a crucial diagnostic tool for assessing the quality and performance of photovoltaic (PV) modules. However, current research often focuses on defect detection in PV modules, neglecting the need for detailed segmentation at the individual cell level. To address the limitations of existing methods in recognizing complex defects and suppressing background noise, this paper proposes a novel semantic segmentation algorithm (CAAK-Net), capable of identifying anomalies at the cell level of photovoltaic panels. To enhance network performance, CAAK-Net uses K-Net as a baseline and incorporates the Convolutional Block Attention Module (CBAM), Attention Refinement Module (ARM), and Atrous Spatial Pyramid Pooling (ASPP) modules. Experimental results comparing CAAK-Net with mainstream segmentation networks demonstrate its superior segmentation performance, particularly in recognizing defect edges and small-area attached defects. Additionally, we establish a quantitative correlation model between detection errors and PV system efficiency losses, pioneering the translation of pixel-level segmentation accuracy into measurable operational costs, thereby providing an economic assessment framework for industrial PV inspection. Furthermore, the network exhibits a certain degree of robustness in noisy environments, showcasing its segmentation advantages in diverse defect scenarios.

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Sliding Mode Observation and control for Overhead Cranes with Varying Rope Length

Sliding Mode Observation and Control for Overhead Cranes wit...

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2021 China automation Congress, CAC 2021

作者： Huan, Xuwei Niu, Dan Li, Qi Yang, Jun Liu, Guoyao Chen, Xisong Xiao, Xi Key Laboratory of Measurement and Control of CSE Ministry of Education Southeast University Nanjing China Department of Aeronautical and Automotive Engineering Loughborough University LoughboroughLE11 3TU United Kingdom Nanjing Sciyon Automation Group Co. Ltd Nanjing China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing China

ISBN: (纸本)9781665426473

This paper proposes a state observer and controller based on the second-order sliding mode scheme for underactuated overhead cranes with load hoisting and lowering. The designed state observer can effectively estimate the uncertainly and unmodeled dynamics of crane systems, and provide appropriate driving force compensations for the sliding mode controller designed by coupling the load swing angle. This guarantees an accurate load positioning and residual swing elimination. Based on the Lyapunov stability criterion, the asymptotic stability of the control system is proved Several simulations are implemented to verify the effectiveness and robustness of the proposed controller for anti-sway and positioning controls. © 2021 IEEE

关键词： Asymptotic stability

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SUNet: Scale-aware Unified Network for Panoptic Segmentation

arXiv

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arXiv 2022年

作者： Yan, Weihao Qian, Yeqiang Wang, Chunxiang Yang, Ming The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China

Panoptic segmentation combines the advantages of semantic and instance segmentation, which can provide both pixel-level and instance-level environmental perception information for intelligent vehicles. However, it is challenged with segmenting objects of various scales, especially on extremely large and small ones. In this work, we propose two lightweight modules to mitigate this problem. First, Pixel-relation Block is designed to model global context information for large-scale things, which is based on a query-independent formulation and brings small parameter increments. Then, Convectional Network is constructed to collect extra high-resolution information for small-scale stuff, supplying more appropriate semantic features for the downstream segmentation branches. Based on these two modules, we present an end-to-end Scale-aware Unified Network (SUNet), which is more adaptable to multi-scale objects. Extensive experiments on Cityscapes and COCO demonstrate the effectiveness of the proposed methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

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Milestones in Autonomous Driving and Intelligent Vehicles Part I: control, Computing system Design, Communication, HD Map, Testing, and Human Behaviors

arXiv

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arXiv 2023年

作者： Chen, Long Li, Yuchen Huang, Chao Xing, Yang Tian, Daxin Li, Li Hu, Zhongxu Teng, Siyu Lv, Chen Wang, Jinjun Cao, Dongpu Zheng, Nanning Wang, Fei-Yue The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Waytous Ltd. China BNU-HKBU United International College Zhuhai519087 China Hong Kong Baptist University Kowloon999077 Hong Kong The Department of Industrial and System Engineering Hong Kong Polytechnical University Hong Kong The School of Aerospace Transport and Manufacturing Cranfield University United Kingdom The School of Transportation Science and Engineering Beihang University China The Department of Automation Tsinghua University China The Department of Mechanical and Aerospace Engineering Nanyang Technological University Singapore The College of Artificial Intelligence Xi'an Jiaotong University China The School of Mechanical Engineering Tsinghua University China

Interest in autonomous driving (AD) and intelligent vehicles (IVs) is growing at a rapid pace due to the convenience, safety, and economic benefits. Although a number of surveys have reviewed research achievements in this field, they are still limited in specific tasks and lack systematic summaries and research directions in the future. Our work is divided into 3 independent articles and the first part is a Survey of Surveys (SoS) for total technologies of AD and IVs that involves the history, summarizes the milestones, and provides the perspectives, ethics, and future research directions. This is the second part (Part I for this technical survey) to review the development of control, computing system design, communication, High Definition map (HD map), testing, and human behaviors in IVs. In addition, the third part (Part II for this technical survey) is to review the perception and planning sections. The objective of this paper is to involve all the sections of AD, summarize the latest technical milestones, and guide abecedarians to quickly understand the development of AD and IVs. Combining the SoS and Part II, we anticipate that this work will bring novel and diverse insights to researchers and abecedarians, and serve as a bridge between past and future. Copyright © 2023, The Authors. All rights reserved.

关键词： Autonomous vehicles

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