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IEEE JOURNAL OF RADIO FREQUENCY IDENTIFICATION 2022年 6卷 688-692页

作者： Wang, Yutong Wang, Jiangong Tian, Yonglin Wang, Xiao Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100080 Peoples R China Qingdao Acad Intelligent Ind Parallel Intelligence Res Ctr Qingdao 266000 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Peoples R China Macau Univ Sci & Technol Inst Syst Engn Macau Peoples R China

With the rapid development of smart manufacturing technologies, machines as primary productivity have come into intelligent era. In current industrialization, workers play an significant role in PCB manufacturing and gradually become the bottleneck of the whole manufacturing process. However, the workers in factories have been ignored for a long time. There are not any intelligent method to organize, coordinate and manage them efficiently. In this paper, based on CPSS and ACP theory, we propose a digital worker system to facilitate biological workers to perform human resource management, largely reducing workload, improving working performance, and taking care of physical and mental health of human workers. In this CPSS system, we leverage ACP method to construct a super brain between digital workers, implementing descriptive intelligence, predictive intelligence, and prescriptive intelligence, thus providing personal guidance and management strategies for each biological worker. Consequently we could relieve job burnout and reduce turnover rate for PCB manufacturers.

关键词： Cyber-physical-social systems PCB manufacturing digital humans

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A New Recursive Composite Adaptive controller for Robot Manipulators

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Space(Science & Technology) 2021年第1期2021卷 77-83页

作者： Jianfei Li Yaobing Wang Zhiyong Liu Xin Jing Chengwei Hu The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Beijing Key Laboratory of Intelligent Space Robotic System Technology and Applications Beijing Institute of Spacecraft System EngineeringBeijing 100094China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

In this paper,a new recursive implementation of composite adaptive control for robot manipulators is *** investigate the recursive composite adaptive algorithm and prove the stability directly based on the Newton-Euler equations in matrix form,which,to our knowledge,is the first result on this point in the *** proposed algorithm has an amount of computation O(n),which is less than any existing similar algorithms and can satisfy the computation need of the complicated multidegree *** manipulator of the Chinese Space Station is employed as a simulation example,and the results verify the effectiveness of this proposed recursive algorithm.

关键词： Robot manipulators robot

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Computational knowledge vision: paradigmatic knowledge based prescriptive learning and reasoning for perception and vision

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ARTIFICIAL INTELLIGENCE REVIEW 2022年第8期55卷 5917-5952页

作者： Zheng, Wenbo Yan, Lan Gou, Chao Wang, Fei-Yue Wuhan Univ Technol Sch Comp & Artificial Intelligence Wuhan Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Sun Yat Sen Univ Sch Intelligent Syst Engn Guangzhou Peoples R China

This paper outlines a novel advanced framework that combines structurized knowledge and visual models-Computational Knowledge Vision. In advanced studies of image and visual perception, a visual model's understanding and reasoning ability often determines whether it works well in complex scenarios. This paper presents the state-of-the-art mainstream of vision models for visual perception. This paper then proposes a concept and basic framework of Computational Knowledge Vision that extends the knowledge engineering methodology to the computer vision field. In this paper, we first retrospect prior work related to Computational Knowledge Vision in the light of the connectionist and symbolist streams. We discuss neural network models, meta-learning models, graph models, and Transformer models in detail. We then illustrate a basic framework for Computational Knowledge Vision, whose essential techniques include structurized knowledge, knowledge projection, and conditional feedback. The goal of the framework is to enable visual models to gain the ability of representation, understanding, and reasoning. We also describe in-depth works in Computational Knowledge Vision and its extensions in other fields.

关键词： Computer vision Knowledge engineering Deep learning Graph learning Meta-learning Transformer Artificial intelligence (AI)

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Process Monitoring, Diagnosis and control of Additive Manufacturing

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2024年第1期21卷 1041-1067页

作者： Fang, Qihang Xiong, Gang Zhou, MengChu Tamir, Tariku Sinshaw Yan, Chao-Bo Wu, Huaiyu Shen, Zhen Wang, Fei-Yue Chinese Acad Sci Inst Automat Beijing Engn Res Ctr Intelligent Syst & Technol State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Guangdong Engn Res Ctr 3D Printing & Intelligent M Cloud Comp Ctr Dongguan 523808 Peoples R China New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA Macau Univ Sci & Technol Inst Syst Engn Macau 999078 Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Fac Elect & Informat Engn Sch Automation Sci & Engn Xian 710049 Shaanxi Peoples R China

Additive manufacturing (AM) can build up complex parts in a layer-by-layer manner, which is a kind of novel and flexible production technology. The special manufacturing capability of AM shows great application potential in various fields. However, an open-loop control method cannot guarantee the reliability and repeatability of an AM process. Defects often occur to deteriorate product quality and lead to material and time waste, which hinders the development of AM industry. In this regard, a lot of efforts have been made to make an AM process more controllable. This work proposes an AM control framework that divides the related studies into three feedback loops, including the in-situ monitoring of process defects, fault diagnosis of 3-D printers, and closed-loop control of an AM process. These three loops constitute the inspection and control of AM from the machine level to product level. Specifically, the measurement requirements for monitoring techniques, defect detection, fault diagnosis, and closed-loop control are summarized. The challenges and future trends in realizing a more reliable and repeatable AM process are discussed. Note to Practitioners-This survey is motivated by urgent need to solve product quality problems in additive manufacturing (AM) caused by open-loop control. Three feedback loops can be established to solve them. The first one is defect detection that inspects part quality during fabrication. The second one is the fault diagnosis of a 3-D printer that monitors the health and operation conditions of its actuators. The last one is closed-loop control that improves AM process reliability and repeatability by regulating process variables in real time. These three loops are all based on the feedback signals of in-situ monitoring systems. This paper reviews the related studies and provides guidance for establishing the monitoring systems, performing defect detection and fault diagnosis, and designing closed-loop control systems, which helps real

关键词： Additive manufacturing (AM) in-situ monitoring defect detection fault diagnosis closed-loop control

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Design and Performance Analysis of a Series-Parallel Self-Aligning Index Finger Exoskeleton

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IEEE Robotics and Automation Letters 2025年第6期10卷 6456-6463页

作者： Sun, Ning Wang, Zelong Cheng, Long Li, Houcheng Niu, Ben Sun, Xijin Li, Ke Shandong Normal University School of Information Science and Engineering Jinan China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing China Shandong University Institute of Intelligent Medical Engineering School of Control Science and Engineering Jinan China

Hand exoskeletons have become increasingly crucial for the rehabilitation of hand function, as relevant studies have shown that using the exoskeletons to assist in rehabilitation training can improve hand motor function. However, developing a human-robot kinematic compatibility exoskeleton while providing sufficient assistance torque is still a challenge. This paper develops a series-parallel self-aligning index finger exoskeleton to assist the index finger in flexion/extension and adduction/abduction training. A series-parallel mechanism driven by two motors simultaneously was proposed for the metacarpophalangeal (MCP) joint, which can ensure human-robot joint axes self-alignment and increase the joint assistance torque. A kinematic compatibility analysis method was proposed, and the kinematic compatibility of the series-parallel mechanism was analyzed. The degrees of freedom and forward kinematics of the proposed mechanism were analyzed, and its workspace was calculated, which results show that the motion range of the MCP joint can meet the grasping training requirements. Preliminary experiments were carried out, and the results indicate that the motion trajectory coefficients of the marker points at the MCP, PIP, and DIP joints averaged for all subjects with and without the proposed exoskeleton are 0.993, 0.956, and 0.939, respectively, which can verify the kinematic transparency of the proposed mechanism. The assistance torque generated by the proposed mechanism on the MCP joint can meet the joint assistance torque requirements. In a word, the proposed exoskeleton can achieve flexion/extension and adduction/abduction training, human-robot joint axes self-alignment, and provide sufficient assistance torque. © 2016 IEEE.

关键词： Exoskeleton (Robotics)

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Multipattern Integrated Networks With Contrastive Pretraining for Graph Anomaly Detection

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2024年第5期11卷 5619-5630页

作者： Yang, Manzhi Zhang, Jian Lin, Liyuan Han, Jinpeng Chen, Xiaoguang Wang, Zhen Wang, Fei-Yue Macau Univ Sci & Technol Macau Inst Syst Engn Macau 999078 Peoples R China Hangzhou Dianzi Univ Sch Cyberspace Hangzhou 310000 Peoples R China Xi An Jiao Tong Univ Sch Software Engn Xian 710049 Peoples R China Hangzhou Dianzi Univ Expt Ctr Data Sci & Intelligent Decis Making Hangzhou 310000 Peoples R China Beijing Engn Res Ctr State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beijing Engn Res Ctr Beijing Engn Res Ctr Intelligent Syst & Technol Beijing 100190 Peoples R China Beijing Huairou Acad Parallel Sensing Beijing 101407 Peoples R China

As a challenge of practical significance, fraud detection has great potential for telecom fraud prevention, economic crime prevention, and personal property preservation. Fraudulent activities are always buried in massive regular transactions, making it hard to find them. Traditional rule-based approaches need multiple domain-specific rules and multistep verification, which limits their transferability and efficiency. Machine learning-based methods might ignore the intricate interactions or the temporal relations among accounts. Meanwhile, the lack of sufficient manual labels restricts their performance. To overcome the above limitations, we present a multipattern integrated network (MPIN) in this article to identify fraudulent accounts in transaction networks. Specifically, MPIN considers the interactions among nodes from three perspectives: inflows, outflows, and their mutual influences. To learn the behavior pattern of each node, MPIN first applies an attention mechanism to integrate the short-term information and then learns the long-term patterns by aggregating multiple short-term patterns. Behavior patterns from different perspectives together with long short-term modeling enable the model to precisely distinguish fraudulent accounts from the normal ones. Moreover, contrastive pretraining with temporal consistency and local tightness guarantee is adopted to alleviate the label sparsity issue and provide the model with low-variance performance. We conducted experiments on two real-world transaction networks, and the results showed the effectiveness of MPIN compared with five state-of-the-art baselines.

关键词： Fraud Contrastive learning Representation learning Telecommunications Credit cards Collaboration Task analysis Anomaly detection contrastive learning graph neural network network representation learning

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TAO-Based Data Governance in intelligent Transportation systems 26

TAO-Based Data Governance in Intelligent Transportation Syst...

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IEEE 26th International Conference on intelligent Transportation systems (ITSC)

作者： Liang, Xiaolong Li, Juanjuan Qin, Rui Ding, Wenwen Wang, Fei-Yue Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China Chinese Acad Sci State Key Lab Multimodal Artificial Intelligence Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China Collaborat Lab Intelligent Sci & Syst Beijing 100190 Peoples R China

ISBN: (纸本)9798350399462

intelligent Transportation systems (ITS) are heavily dependent on private user data. However, most ITS fails to harness the potential of this invaluable data due to the absence of effective data governance mechanisms promoting users' contributions. Moreover, data contributors face security risks such as privacy preservation, data leakage, etc., as well as high costs in data sharing, while benefits are disproportionately reaped by system operators and interaction. This systemic imbalance could indirectly incentivize a surge in inactions and even malicious actions. In response to these challenges, we propose the design of a True Autonomous Organization (TAO) for ITS, namely ITS TAO. Utilizing the newly designed decision models with decentralized organization structures and the three-power structure, ITS TAO aims to realize the fair distribution of rights and benefits for ITS data contributors. Furthermore, we design a real-time evaluation system based on parallel intelligence capable of identifying potential hazards.

关键词： intelligent Transportation systems True Autonomous Organization Parallel intelligent Mechanism Design Parallel Governance

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Deep Domain Adaptation Regression for Force Calibration of Optical Tactile Sensors

Deep Domain Adaptation Regression for Force Calibration of O...

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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Zhuo Chen Ni Ou Jiaqi Jiang Shan Luo Department of Engineering Robot Perception Lab Centre for Robotics Research King’s College London London United Kingdom State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Optical tactile sensors provide robots with rich force information for robot grasping in unstructured environments. The fast and accurate calibration of three-dimensional contact forces holds significance for new sensors and existing tactile sensors which may have incurred damage or aging. However, the conventional neural-network-based force calibration method necessitates a large volume of force-labeled tactile images to minimize force prediction errors, with the need for accurate Force/Torque measurement tools as well as a time-consuming data collection process. To address this challenge, we propose a novel deep domain-adaptation force calibration method, designed to transfer the force prediction ability from a calibrated optical tactile sensor to uncalibrated ones with various combinations of domain gaps, including marker presence, illumination condition, and elastomer modulus. Experimental results show the effectiveness of the proposed unsupervised force calibration method, with lowest force prediction errors of 0.102N (3.4% in full force range) for normal force, and 0.095N (6.3%) and 0.062N (4.1%) for shear forces along the x-axis and y-axis, respectively. This study presents a promising, general force calibration methodology for optical tactile sensors.

关键词： Accuracy Force Tactile sensors Lighting Elastomers Data collection Optical imaging Adaptive optics Calibration Optical sensors

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Advanced Air Mobility: An Innovation for Future Diversified Transportation and Society

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON intelligent VEHICLES 2024年第2期9卷 3106-3110页

作者： Guo, Jingqiu Chen, Long Li, Lingxi Na, Xiaoxiang Vlacic, Ljubo Wang, Fei-Yue Tongji Univ Minist Educ Key Lab Rd & Traff Engn Shanghai 201804 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Indiana Univ Purdue Univ Purdue Sch Engn & Technol Dept Elect & Comp Engn Indianapolis IN 46202 USA Univ Cambridge Dept Engn Cambridge CB2 1TN England Griffith Univ Inst Intelligent & Integrated Syst Nathan Qld 4111 Australia Griffith Univ Sch Engn & Built Environm Nathan Qld 4111 Australia Macau Univ Sci & Technol Inst Engn Macau 999078 Peoples R China

Advanced Air Mobility (AAM) is an innovative transportation system that will provide safe and efficient mobility of cargo, passenger and emergency services in low-altitude airspace. This paper highlights AAM's vision and addresses fundamental research challenges and opportunities, e.g., vertical lift aircraft technologies, infrastructure and operation, unmanned traffic management and system security. The overall structure of the AAM ecosystem is discussed from a technology and service perspective. The SEEDS evaluation criteria for the AAM system are explored in terms of promoting safety, sustainability and service quality during the development, verification and validation, and operation phases. As a key sector of the Mobility 5.0 paradigm, new air mobility needs to be integrated into multimodal transport and logistics systems to deliver diverse, sustainable and trustworthy solutions in the near future.

关键词： Active appearance model Aircraft Transportation Air traffic control Batteries Industries Regulation Advanced air mobility low-altitude VTOL unmanned aircraft transportation

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A New Perspective for Computational Social systems: Fuzzy Modeling and Reasoning for Social Computing in CPSS

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2024年第1期11卷 101-116页

作者： Wang, Tan Zhu, Yifan Ye, Peijun Gong, Weichao Lu, Hao Mo, Hong Wang, Fei-Yue Macau Univ Sci & Technol Fac Innovat Engn Dept Engn Sci Macau Peoples R China Chinese Acad Sci Inst Automat Chinese Assoc Automat Beijing 100190 Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing 100084 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 10086 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Peoples R China Changsha Univ Sci & Technol Coll Elect & Informat Engn Changsha 410114 Peoples R China

The evolution of modern mobile terminals, social networks, and other intelligent services makes everyone become a ubiquitous information perceiver, producer, and propagator. Also known as "social sensor" and "social IoT", these individuals and communities generate a huge volume of social signals, which has shown prominent value for mining. These unstructured social signals provide a new perspective in the research of complex systems, which makes the traditional cyber-physical system (CPS)-oriented information computing sublimate to the cyber-physical-social system (CPSS)-oriented knowledge computing. However, there still exist great uncertainties, ambiguities, and complexities in modeling behaviors of social individuals or groups. Especially when we apply big-data-driven learning-based models in specific fields and scenarios, the lack of domain expert knowledge and characteristics of system uncertainty severely limits the performance and accuracy of these models. The introduction of fuzzy system modeling integrates data and knowledge in the social computing area, which has shown its unique advantages in solving the above issues and has drawn more attention to this topic. In this article, we conduct a review of recent advances in social computing with fuzzy technologies in CPSS. First, we briefly review the development of social computing, and analyze the characteristics and advantages of social computing through fuzzy methods. Second, we refine core fuzzy system methods for social computing and elaborate on existing fuzzy-technology-empowered social computing methodologies. As in a range of social spaces, we also review and analyze related advances in human-in-the-loop systems. We also reveal the trend of decentralized, autonomous, and organized computing in cyber-physical-social space with fuzzy-based methods and proposed a framework to categorize related studies in CPSS. Finally, we conclude the research trends and hotspots based on current studies, and discuss th

关键词： Social computing Computational modeling Fuzzy systems Uncertainty complex systems Analytical models Human in the loop Computational systems cyber-physical-social systems (CPSSs) fuzzy paradigm parallel society social computing

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