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2023 IEEE International Conference on Industrial technology, ICIT 2023

作者： Wang, Longqiang Wang, Ruohan Wu, Haiteng Yang, Geng School of Mechanical Engineering Zhejiang University State Key Laboratory of Fluid Power & Mechanical Systems Hangzhou China Hangzhou Shenhao Technology Co. LTD. Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou China

ISBN: (纸本)9798350336504

In conventional high-voltage live work, operators are required to work near high-voltage cables, which poses risks such as falling and getting an electric shock. To promise the worker's safety, regional breakout of power is one of the common methods that the power sector would deploy. However, with the development of society, a lot of trouble will be brought about due to the economic loss and social impact caused by regional power outages, which pose higher requirements for the power sector. Hence, it is demanding to carry out a safe and effective method for high-voltage live work without power failure. In such a context, we have developed a dual-arm collaborative robotic system for high-voltage live work. The system includes a human-computer interaction interface and a pair of Omega handles, which allow workers to operate remotely at the control center. In laboratory experiments, the system can accurately complete stripping, trimming, and wiring operations. Also, some actions are pre-programmed inside the control system to realize simple operations automatically. This dual-arm robot collaboration system with a teleoperation function can greatly reduce the labor intensity of workers and ensure their safety. © 2023 IEEE.

关键词： Remote control

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2024 China Automation Congress, CAC 2024

作者： Lang, Yumin Wu, Jiande Lang, Xun Yu, Wanke Yang, Chuanyan Su, Hongye Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9798350368604

Oscillation is a significant indication of the deterioration of control system performance and needs to be carefully monitored to ensure safe and stable process operations. However, industrial processes are often prone to noisy artifacts and nonstationary trends, resulting in low signal-to-noise ratios. In order to tackle this problem, this study introduces a novel framework for enhanced trend removal and noise reduction, which is featured by the following steps:(i) The circulant singular spectrum analysis (CiSSA) is used to decompose oscillation data into several reconstructed components (RCs). (ii) The estimated power spectral density (PSD) ofthese RCs is then smoothed using the Savitzky-Golay filter (SGF) to eliminate noise and identify the RCs corresponding to oscillatory components. (iii) These identified RCs are subsequently reconstructed to produce purified oscillatory data. The effectiveness of the suggested approach is validated using simulations and real-world industrial case studies. The findings indicate that the method notably enhances the quality of oscillatory data. © 2024 IEEE.

关键词： Power spectral density

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An Adaptive Control Method for Ship Speed in Restricted Waters

An Adaptive Control Method for Ship Speed in Restricted Wate...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Wu, Fanglie Wu, Bing Xiong, Mai Su, Xin Jiang, Jinhui State Key Laboratory of Maritime Technology and Safety Wuhan University of Technology Wuhan430063 China Wuhan University of Technology Wuhan430056 China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan430056 China School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan430063 China Academician Workstation of China COSCOSHIPPINGCO Ltd. Wuhan China

ISBN: (纸本)9789819639687

In inland waterway transportation, ships often experience incidents such as groundings and other navigational accidents as a result of failing to adhere to safe sailing speed. An adaptive controller for ship speed is designed under the dual constraints of water depth and tidal time when entering the port by tide. First, the factors are identified that affect the safe speed of ships and the Barrass II formula is introduced to determine the relationship between ship subsidence and maximum safe speed. Second, a 4-DOF ship motion model is established, and a dynamic safety speed constraint framework is constructed based on requirements such as ship speed, ship posture, Under Keel Clearance (UKC) and tidal time. Finally, dynamic constraints and nonlinear model predictive control (MPC) methods are combined, safety speed constraints and minimum speed constraints are designed, and a speed adaptive control model is established. The experiment shows that the controller can effectively track the target trajectory under the constraint of safe speed, the objective of safe navigation is achieved. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Inland waterways

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A Multi-Agent Based Simulation Modeling Method for UAV Swarm Collaborative Combat

A Multi-Agent Based Simulation Modeling Method for UAV Swarm...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Linpeng Jia Lingda Wang Wei Quan Enjun Qiao Zhao Zhang Chen Chen School of Automation Beijing Institute of Technology The National Key Lab of Autonomous Intelligent Unmanned Systems Beijing China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

Unmanned Aerial Vehicle (UAV) swarm collaborative combat is increasingly becoming a vital component in modern warfare systems. As an important part of swarm warfare research, the modeling and full process simulation systems for collaborative operations have become a challenging topic. Considering the characteristics of swarm combat, this paper constructs a simulation modeling design for UAV swarm collaborative combat simulations. Based on multi-agent modeling technology, UAV swarms are modeled as multiple intelligent agents with behavior models and strategy models. In the behavior model, the movement, formation, communication, detection, and strike behaviors of UAV swarm are fully considered. To further characterize the collaborative characteristics, emergency network formation strategies, collaborative search strategies based on stepwise predictive control, and collaborative strike strategies responsive to situational changes are designed in the strategy model. A simulation scenario is designed and simulated, which validates the feasibility and effectiveness of the simulation model. The impact of swarm size, task complexity, environmental interferenceˈ and strategic selection on combat effectiveness is verified by the simulation system. This simulation model can fully show the validation for collaborative operations and provide guidance for decision optimization.

关键词： Evaluation models Collaboration Predictive models Autonomous aerial vehicles Search problems systems simulation intelligent agents

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Can Digital Intelligence and Cyber-Physical-Social systems Achieve Global Food Security and Sustainability?

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IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2070-2080页

作者： Yanfen Wang Mengzhen Kang Yali Liu Juanjuan Li Kai Xue Xiujuan Wang Jianqing Du Yonglin Tian Qinghua Ni Fei-Yue Wang College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049 Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408 State Key Laboratory of Tibetan Plateau Earth System Environment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Grassland Science Beijing Forestry UniversityBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXining 810016 Key Laboratory of Adaptation and Evolution of Plateau Biota Northwest Institute of Plateau BiologyChinese Academy of SciencesXining 810001 Binzhou Institute of Technology Weiqiao-UCAS Science and Technology ParkBinzhou 256606China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078 State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078 Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China IEEE

Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration *** the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the

关键词： Carbon-water balance decision-support digital intelligence(DI) foundation models planning

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Data-driven Modeling of Nonlinear Joints in Space Structures 41

Data-driven Modeling of Nonlinear Joints in Space Structures

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第41届中国控制会议

作者： Yonglei Zhang Xiaoyu Wang Xinyuan Li Hao Wen Shidong Xu State Key Laboratory of Mechanics and Control of Mechanical Structures Nanjing University of Aeronautics and Astronautics Beijing Key Laboratory of Intelligent Space Robotic Systems Technology and Applications Beijing Institute of Spacecraft System Engineering

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

The existence of nonlinear joints has a great influence on the dynamics of large flexible sapce *** a prerequisite of attitude control and vibration suppression of flexible spacecraft,it is of great importance to establish highconfidence models of joints to predict its dynamic characteristics ***,a single-degree-of-freedom model of the nonlinear joint is established based on the describing function method and harmonic balance method(HBM).In particular,the dynamic funtions of the joints with cubic stiffness and freeplay nonlinearity are derived,and the response and external excitation data are used to train surrogate models by a multi-step DNN *** validity of the data-driven modeling approach is further verified by response prediction under a different excition ***,the characteristic of an unknown nonlinearjoint is revealed by the data-driven modeling approach based on the experimental data.

关键词： Nonlinear joints space structures data-driven modeling response prediction

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Dual-Layer Collaborative Hunting Algorithm Using Virtual Wolf Pack

Dual-Layer Collaborative Hunting Algorithm Using Virtual Wol...

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第43届中国控制会议

作者： Zhiqiang Miao Jianlei Zhang Chunyan Zhang Chen Wang Guangming Xie State Key Laboratory for Turbulence and Complex Systems Intelligent Biomimetic Design LabCollege of EngineeringPeking University

Collaborative hunting,also known as Multi-Agent Pursuit Evasion(MAPE),is a crucial aspect of swarm *** main obstacles in MAPE research involve making real-time decisions in dynamic environments,efficient task allocation,collision avoidance among multiple agents,planning and tracking prey in unknown environments,and information sharing under communication *** paper presents the Dual-Layer Collaborative Hunting Algorithm Using Virtual Wolf Pack(DLCH-VWP),which utilizes biomimetic principles,specifically leveraging the advantages and hunting strategies of wolf packs,to enhance collaborative efficiency and adaptability in complex environments within *** algorithm employs a two-tier strategy,with the strategy planning center using biomimetic wolf pack algorithm to manage environment perception,state assessment,prey movement prediction,and inter-robot *** local response center treats each wolf as an independently operating sub-pack,utilizing a combination of Grey Wolf Optimizer(GWO) and the local A-star algorithm to provide each wolf with individual *** allows for efficient dynamic path planning by determining the path for each wolf based on joint decision-making of the group and *** experiments have confirmed the effectiveness and feasibility of this algorithm for collaborative hunting in multi-agent systems,presenting a novel strategy for addressing MAPE challenges.

关键词： Virtual wolf pack Swarm intelligence Collaborative hunting

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GazeSwipe: Enhancing Mobile Touchscreen Reachability through Seamless Gaze and Finger-Swipe Integration

arXiv

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arXiv 2025年

作者： Cai, Zhuojiang Hong, Jingkai Wang, Zhimin Lu, Feng State Key Lab. of VR Technology and Systems Beihang University Beijing China

Smartphones with large screens provide users with increased display and interaction space but pose challenges in reaching certain areas with the thumb when using the device with one hand. To address this, we introduce GazeSwipe, a multimodal interaction technique that combines eye gaze with finger-swipe gestures, enabling intuitive and low-friction reach on mobile touchscreens. Specifically, we design a gaze estimation method that eliminates the need for explicit gaze calibration. Our approach also avoids the use of additional eye-tracking hardware by leveraging the smartphone’s built-in front-facing camera. Considering the potential decrease in gaze accuracy without dedicated eye trackers, we use finger-swipe gestures to compensate for any inaccuracies in gaze estimation. Additionally, we introduce a user-unaware auto-calibration method that improves gaze accuracy during interaction. Through extensive experiments on smartphones and tablets, we compare our technique with various methods for touchscreen reachability and evaluate the performance of our auto-calibration strategy. The results demonstrate that our method achieves high success rates and is preferred by users. The findings also validate the effectiveness of the auto-calibration strategy. © 2025, CC BY.

关键词： Smartphones

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Recent advances in photoelectrochemical sensors for detection of ions in water

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Chinese Chemical Letters 2023年第6期34卷 37-48页

作者： Linyang Li Junlian Chen Chuanbao Xiao Yihao Luo Nianbing Zhong Quanhua Xie Haixing Chang Dengjie Zhong Yunlan Xu Mingfu Zhao Qiang Liao Intelligent Fiber Sensing Technology of Chongqing Municipal Engineering Research Center of Institutions of Higher Education Chongqing Key Laboratory of Modern Photoelectric Detection Technology and InstrumentChongqing Key Laboratory of Fiber Optic Sensor and PhotodetectorChongqing University of TechnologyChongqing 400054China Biodesign Swette Center for Environmental Biotechnology Arizona State UniversityTempeAZ 85271-5701United States College of Chemistry and Chemical Engineering Chongqing University of TechnologyChongqing 400054China Key Laboratory of Low-grade Energy Utilization Technologies and Systems(Chongqing University) Ministry of EducationChongqing 400030China

Over the last 50 years,the explosive adoption of modern agricultural practices has led to an enormous increase in the emission of non-biodegradable and highly biotoxic ions into the *** intake of such ions,even essential trace elements such as Cu^(2+)and F^(-),can have serious consequences on human ***,to ensure safe drinking water and regulate wastewater discharge,photoelectrochemical(PEC)online sensors were developed,with advantages such as low energy consumption,inherent miniaturization,simple instrumentation,and fast ***,there is no publicly available systematic review of the recent advances in PEC ion sensors available in the literature since January ***,this review covers the various strategies that have been used to enhance the sensitivity,selectivity,and limit of detection for PEC ion *** photoelectrochemically active materials,conductive substrates,electronic transfer,and performance of various PEC sensors are discussed in detail and divided into sections based on the measurement principle and detected ion *** conclude this review by highlighting the challenges and potential future avenues of research associated with the development of novel high-performance PEC sensors.

关键词： Photoelectrochemical sensor Ion detection Working principle Electronic transfer Sensitivity and selectivity Limit of detection

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Multi-objective Feature Attribution Explanation for Explainable Machine Learning

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ACM Transactions on Evolutionary Learning and Optimization 2024年第1期4卷 1-32页

作者： Wang, Ziming Huang, Changwu Li, Yun Yao, Xin Research Institute of Trustworthy Autonomous Systems Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation Departmentof Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China The Advanced Cognitive Technology Lab Huawei Technologies Co. Ltd Shanghai201206 China School of Computer Science University of Birmingham BirminghamB15 2TT United Kingdom

The feature attribution-based explanation (FAE) methods, which indicate how much each input feature contributes to the model's output for a given data point, are one of the most popular categories of explainable machine learning techniques. Although various metrics have been proposed to evaluate the explanation quality, no single metric could capture different aspects of the explanations. Different conclusions might be drawn using different metrics. Moreover, during the processes of generating explanations, existing FAE methods either do not consider any evaluation metric or only consider the faithfulness of the explanation, failing to consider multiple metrics simultaneously. To address this issue, we formulate the problem of creating FAE explainable models as a multi-objective learning problem that considers multiple explanation quality metrics simultaneously. We first reveal conflicts between various explanation quality metrics, including faithfulness, sensitivity, and complexity. Then, we define the considered multi-objective explanation problem and propose a multi-objective feature attribution explanation (MOFAE) framework to address this newly defined problem. Subsequently, we instantiate the framework by simultaneously considering the explanation's faithfulness, sensitivity, and complexity. Experimental results comparing with six state-of-The-Art FAE methods on eight datasets demonstrate that our method can optimize multiple conflicting metrics simultaneously and can provide explanations with higher faithfulness, lower sensitivity, and lower complexity than the compared methods. Moreover, the results have shown that our method has better diversity, i.e., it provides various explanations that achieve different tradeoffs between multiple conflicting explanation quality metrics. Therefore, it can provide tailored explanations to different stakeholders based on their specific requirements. © 2024 Copyright held by the owner/author(s). Publication rights licensed

关键词： Machine learning

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