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第41届中国控制会议

作者： Mohan Jia Zhongjian Dai Yaping Dai Zhiyang Jia School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In one-stage methods for video moment retrieval,the common representations indirectly supervised by boundary prediction fail to fully preserve the inherent characteristic of the video and query,which limits the retrieval *** solve this problem,an Adversarial Video Moment Retrieval(AVMR) algorithm is proposed to learn the common representations with modality invariance and cross-modal *** is implemented through the process of adversarial learning between a feature projector and a modality *** feature projector tries to generate a modality-invariant common representation and to confuse the modality *** modality classifier tries to discriminate between different modalities based on the generated representation by the feature *** triplet constraints are further imposed on the feature projector to preserve the underlying cross-modal semantic structure of *** experimental results show that AVMR surpasses the baseline Attentive Cross-modal Relevance Matching(ACRM) by 1.10% and 1.73% in the "mIoU" metric on two public datasets Charades-STA and TACoS,respectively.

关键词： Video Moment Retrieval Cross-modal Retrieval Deep learning Adversarial Learning

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AI4S Based on DeSci: Reference Model and Research Issues

AI4S Based on DeSci: Reference Model and Research Issues

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2023 IEEE International Conference on systems, Man, and cybernetics, SMC 2023

作者： Ding, Wenwen Li, Juanjuan Qin, Rui Guan, Sangtian Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Macau University of Science and Technology Faculty of Innovation Engineering Macau China Institute of Automation The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350337020

The rise of Artificial Intelligence for Science (AI4S) has highlighted the importance and urgency of ensuring open-ness, fairness, impartiality, diversity, and sustainability in scientific systems. Existing scientific systems, referred to as Centralized Science (CeSci), are built on centralized organizational structures and top-down institutional frameworks, which are lagging behind the development and practical requirements of AI4S. To address these limitations, AI4S needs to embrace a new scientific organizational and operational paradigm, namely Decentralized Science (DeSci). It can provide strong support to AI4S via effectively addressing issues such as information silos, biases, unfair distribution, and monopolies and promoting multidisciplinary, interdisciplinary, and trans disciplinary cooperation in science. Based on these considerations, this paper presents the framework of AI4S based on DeSci and explores its potential application scenarios and research issues. The research can provide effective guidance for the development of scientific systems. © 2023 IEEE.

关键词： Artificial Intelligence for Science (AI4S) ChatGPT Decentralized Autonomous Organizations and Operations (DAOs) Decentralized Science (De-Sci) Generative Artificial Intelligence (GAI) Intelligent Science

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Non-fragile H∞ Filtering for Fuzzy Discrete-time systems with Markovian Jump and Data Loss 10

Non-fragile H∞ Filtering for Fuzzy Discrete-time Systems wi...

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10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Liang, Lun State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang Hangzhou310027 China

ISBN: (纸本)9781665424233

This paper focuses on the design of the non-fragile H∞ filtering of fuzzy discrete-time systems with Markovian jump and data loss. The system is represented by Takagi and Sugeno (T-S) fuzzy model. The imperfect information transmission from the factory to the filter is modeled by a Bernoulli random binary distribution. A non-fragile and full-order H∞ filter with additive gain variations is constructed. The sufficient conditions are derived based on mode-dependent and fuzzy-basis-dependent Lyapunov functional methods, which ensure the developed filtering error system is stochastically stable with given H∞ performance index. The usefulness and effectiveness of the filter design method is certified by a numerical case. © 2021 IEEE.

关键词： Numerical methods

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Heterogeneous Image Knowledge Driven Visual Perception

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 255-257页

作者： Lan Yan Wenbo Zheng Fei-Yue Wang IEEE the College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China the School of Computer Science and Artificial Intelligence Wuhan University of TechnologyWuhan 430070China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous *** the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

关键词： Visual visual knowledge

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Decomposing Visual and Semantic Correlations for Both Fully Supervised and Few-Shot Image Classification

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1658-1668页

作者： Zhang, Chunjie Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Most image classification methods are designed to either boost the classification accuracies with abundant supervision, or cope with the shortage of supervision information. This is often achieved by using the visual and semantic information of other sources. However, these methods use the visual and semantic information within the same class independently, leaving their intrinsic correlations unconsidered. Objects and disturbing components as well as noise exist on the same image. Besides, semantic representations also contain noisy information. To solve the problems mentioned above, we propose a novel method for both fully supervised image classification and few-shot image classification by decomposing visual and semantic correlations. We jointly explore the intrinsic correlations of visual and semantic information of images within the same class. For each class, we decompose its visual and semantic correlations using low-rank and sparse constraint respectively. The decomposed low-rank parts character the intrinsic correlations of images can be used in a linear transformation way. Using the decomposed parts of each class, Classification can be achieved by reconstruction error minimization. We conduct experiments on several datasets for both fully supervised image classification and few-shot image classification. Experimental results well show the effectiveness of the proposed method. © 2020 IEEE.

关键词： Semantics

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Obstacle Avoidance for Unicycle-Modelled Mobile Robots with Time-varying control Barrier Functions

arXiv

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arXiv 2023年

作者： Huang, Jihao Liu, Zhitao Zeng, Jun Chi, Xuemin Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Cruise LLC United States

In this paper, we propose a safety-critical controller based on time-varying control barrier functions (CBFs) for a robot with an unicycle model in the continuous-time domain to achieve navigation and dynamic collision avoidance. Unlike previous works, our proposed approach can control both linear and angular velocity to avoid collision with obstacles, overcoming the limitation of confined control performance due to the lack of control variable. To ensure that the robot reaches its destination, we also design a control Lyapunov function (CLF). Our safety-critical controller is formulated as a quadratic program (QP) optimization problem that incorporates CLF and CBFs as constraints, enabling real-time application for navigation and dynamic collision avoidance. Numerical simulations are conducted to verify the effectiveness of our proposed approach. Copyright © 2023, The Authors. All rights reserved.

关键词： controllers

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A Multi-stage Quantitative Resilience Optimization Model of Power systems Subjected to Hurricane Hazards 9

A Multi-stage Quantitative Resilience Optimization Model of ...

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9th International Symposium on System Security, Safety, and Reliability, ISSSR 2023

作者： Wang, Feng Shi, Chenli Ling, Jiamu Xu, Zhengguo Zhejiang University The State Key Laboratory of Industrial Control Technology Hangzhou310027 China The Huzhou Institute of Zhejiang University Huzhou313000 China

ISBN: (纸本)9798350302479

Power systems are essential to national security, economic prosperity, public health, and safety. However, as the frequency of extreme events and man-made attacks has increased dramatically in recent years, making resilience theory has become a new direction for responding to low-probability high-impact events. In power systems, resilience is essential in maintaining functionality, reducing losses, and speeding up recovery when encountering a disruptive event. This study develops a resource optimization allocation framework based on multiple resilience objectives by understanding the relationship between resilience performance and dynamic decisions. A multi-resilience-objective mixed-integer linear programming (MROMILP) model is formulated to optimize the resource allocation scheme for each resilience stage under limited internal resources of power systems under hurricane hazards. The IEEE 30-bus test system is used to validate the usability of the model. © 2023 IEEE.

关键词： Hurricanes

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DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition

DeepRING: Learning Roto-translation Invariant Representation...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Sha Lu Xuecheng Xu Li Tang Rong Xiong Yue Wang State Key Laboratory of Industrial Control and Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Alibaba Group Hangzhou China

LiDAR based place recognition is popular for loop closure detection and re-localization. In recent years, deep learning brings improvements to place recognition by learnable feature extraction. However, these methods degenerate when the robot re-visits previous places with a large perspective difference. To address the challenge, we propose DeepRING to learn the roto-translation invariant representation from LiDAR scan, so that robot visiting the same place with a different perspective can have similar representations. There are two keys in DeepRING: the feature is extracted from sinogram, and the feature is aggregated by magnitude spectrum. The two steps keep the final representation with both discrimination and roto-translation invariance. Moreover, we state place recognition as a one-shot learning problem with each place being a class, leveraging relation learning to build representation similarity. Substantial experiments are carried out on public datasets, validating the effectiveness of each proposed component, and showing that DeepRING outperforms the comparative methods, especially in dataset level generalization.

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Accurate and straightforward symplectic approach for fracture analysis of fractional viscoelastic media

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Applied Mathematics and Mechanics(English Edition) 2022年第3期43卷 403-416页

作者： Chenghui XU Sen LENG Zhenhuan ZHOU Xinsheng XU Zichen DENG MIIT Key Laboratory of Dynamics and Control of Complex Systems Department of Engineering MechanicsNorthwestern Polytechnical UniversityXi'an 710072China State Key Laboratory of Structure Analysis of Industrial Equipment Department of Engineering MechanicsDalian University of TechnologyDalian 116024Liaoning ProvinceChina

An accurate and straightforward symplectic method is presented for the fracture analysis of fractional two-dimensional(2D)viscoelastic *** fractional Kelvin-Zener constitutive model is used to describe the time-dependent behavior of viscoelastic *** the framework of symplectic elasticity,the governing equations in the Hamiltonian form for the frequency domain(s-domain)can be directly and rigorously *** the s-domain,the analytical solutions of the displacement and stress fields are constructed by superposing the symplectic eigensolutions without any trial function,and the explicit expressions of the intensity factors and J-integral are derived *** studies are provided to validate the accuracy and effectiveness of the present solutions.A detailed analysis is made to reveal the effects of viscoelastic parameters and applied loads on the intensity factors and J-integral.

关键词： symplectic approach viscoelastic material fractional Kelvin-Zener model crack fracture parameter

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Design of Gravity Compensation Scheme for Passive Lifting Method of Multi-degree Freedom Robotic Arm 18

Design of Gravity Compensation Scheme for Passive Lifting Me...

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18th IEEE Conference on industrial Electronics and Applications, ICIEA 2023

作者： Sun, Jing Wei, Chaoran Chen, Haotai Wang, Bin Li, Xingguang Zhang, Qiang Beijing Institute of Control Engineering Space Drive and Manipulation Mechanism Laboratory Beijing China State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350312201

Before launching a spacecraft, it is necessary to undergo micro low gravity simulations on the ground to test its reliability. The lifting method is not limited by movement time and space, and can simulate long-term low gravity environments. However, the degree of freedom of spatial mechanisms is gradually increasing, and the motion is becoming increasingly complex, making traditional lifting methods unable to meet the needs. In response to the above issues, a lifting gravity simulation scheme for a multi degree of freedom robotic arm that can achieve complex motion is proposed. The design adopts a single sling combined with a hanger to avoid interference during the motion process. Finally, simulation and experiments have proven the feasibility of the scheme - it can achieve efficient unloading without affecting the normal movement of the equipment. © 2023 IEEE.

关键词： Robotic arms

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