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When Embodied AI Meets Industry 5.0:Human-Centered smart Manufacturing

IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 485-501页

作者： Jing Xu Qiyu Sun Qing-Long Han Yang Tang IEEE the Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology the School of Science Computing and Engineering Technologies Swinburne University of Technology

As embodied intelligence(EI), large language models(LLMs), and cloud computing continue to advance, Industry5.0 facilitates the development of industrial artificial intelligence(Ind AI) through cyber-physical-social systems(CPSSs) with a human-centric focus. These technologies are organized by the system-wide approach of Industry 5.0, in order to empower the manufacturing industry to achieve broader societal goals of job creation, economic growth, and green production. This survey first provides a general framework of smart manufacturing in the context of Industry 5.0. Wherein, the embodied agents, like robots, sensors, and actuators, are the carriers for Ind AI, facilitating the development of the self-learning intelligence in individual entities, the collaborative intelligence in production lines and factories(smart systems), and the swarm intelligence within industrial clusters(systems of smart systems). Through the framework of CPSSs, the key technologies and their possible applications for supporting the single-agent, multi-agent and swarm-agent embodied Ind AI have been reviewed, such as the embodied perception, interaction, scheduling, multi-mode large language models, and collaborative training. Finally, to stimulate future research in this area, the open challenges and opportunities of applying Industry 5.0 to smart manufacturing are identified and discussed. The perspective of Industry 5.0-driven manufacturing industry aims to enhance operational productivity and efficiency by seamlessly integrating the virtual and physical worlds in a human-centered manner, thereby fostering an intelligent, sustainable, and resilient industrial landscape.

关键词： Embodied AI human-centered manufacturing Industry 5.0 internet of things large multi-mode language models

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Multi-UAV trajectory planning with field-of-view sharing mechanism in cluttered environments:application to target tracking

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science China(Information sciences) 2025年第5期68卷 89-102页

作者： Kai RAO Huaicheng YAN Penghui YANG Meng WANG Yunkai LV Key Laboratory of Smart Manufacturing in Energy Chemical Process of the Ministry of Education East China University of Science and Technology College of Machinery and Automation Weifang University

Multi-unmanned aerial vehicle(multi-UAV) target tracking requires coordinated trajectory planning that simultaneously ensures formation safety, target visibility, and motion smoothness. To address this challenge, we propose a distributed framework integrating heuristic-guided path search with spatiotemporal trajectory optimization. In the front end, each UAV constructs a safe area that accounts for both tracking distance and visibility considerations, and selects feasible expansion points for path search based on the desired tracking position. Subsequently, a unified trajectory optimizer is employed to derive an executable trajectory that complies with extensive constraints, predicated on the initial path configurations. Considering that UAVs may lose visibility of the target due to cluttered obstacles, a field-of-view sharing mechanism is proposed, enabling occluded UAVs to leverage teammates' visual data for robust collaborative planning in cluttered environments. Finally, simulations and comparative results are conducted through a visualization platform to validate the superior performance of the proposed multi-UAV trajectory planning framework for target tracking.

关键词： multi-UAV target tracking trajectory planning field-of-view sharing mechanism

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BESTAnP: Bi-Step Efficient and Statistically Optimal Estimator for Acoustic-n-Point Problem

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IEEE Robotics and Automation Letters 2025年第6期10卷 5313-5320页

作者： Sheng, Wenliang Zhao, Hongxu Chen, Lingpeng Zeng, Guangyang Shao, Yunling Hong, Yuze Yang, Chao Hong, Ziyang Wu, Junfeng East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Department of Automation Shanghai200237 China Chinese University of Hong Kong School of Data Science Shenzhen518172 China

We consider the acoustic-n-point (AnP) problem, which estimates the pose of a 2D forward-looking sonar (FLS) according to n 3D-2D point correspondences. We explore the nature of the measured partial spherical coordinates and reveal their inherent relationships to translation and orientation. Based on this, we propose a bi-step efficient and statistically optimal AnP (BESTAnP) algorithm that decouples the estimation of translation and orientation. Specifically, in the first step, the translation estimation is formulated as the range-based localization problem based on distance-only measurements. In the second step, the rotation is estimated via eigendecomposition based on azimuth-only measurements and the estimated translation. BESTAnP is the first AnP algorithm that gives a closed-form solution for the full 6 °-of-freedom (DoF) pose. In addition, we conduct bias elimination for BESTAnP such that it owns the statistical property of consistency. Through simulation and real-world experiments, we demonstrate that compared with the state-of-the-art (SOTA) methods, BESTAnP is over ten times faster and features real-time capacity in resource-constrained platforms while exhibiting comparable accuracy. Moreover, we embed BESTAnP into a single sonar-based odometry which shows its effectiveness for trajectory estimation. © 2016 IEEE.

关键词： Sonar

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Physically-consistent-WGAN based small sample fault diagnosis for industrial processes

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Chinese Journal of Chemical Engineering 2025年 78卷 163-174页

作者： Tang, Siyu Shi, Hongbo Song, Bing Tao, Yang Tan, Shuai Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

In real industrial scenarios, equipment cannot be operated in a faulty state for a long time, resulting in a very limited number of available fault samples, and the method of data augmentation using generative adversarial networks for smallsample data has achieved a wide range of applications. However, the current generative adversarial networks applied in industrial processes do not impose realistic physical constraints on the generation of data, resulting in the generation of data that do not have realistic physical consistency. To address this problem, this paper proposes a physical consistency-based WGAN, designs a loss function containing physical constraints for industrial processes, and validates the effectiveness of the method using a common dataset in the field of industrial process fault diagnosis. The experimental results show that the proposed method not only makes the generated data consistent with the physical constraints of the industrial process, but also has better fault diagnosis performance than the existing GAN-based methods. © 2025 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press Co., Ltd. (CIP)

关键词： Chemical equipment

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A data representation method using distance correlation

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Frontiers of Computer science 2025年第1期19卷 1-14页

作者： Xinyan LIANG Yuhua QIAN Qian GUO keyin ZHENG Institute of Big Data Science and Industry Shanxi UniversityTaiyuan 030006China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi UniversityTaiyuan 030006China School of Computer Science and Technology Taiyuan University of Science and TechnologyTaiyuan 030024China Shanxi Key Laboratory of Big Data Analysis and Parallel Computing Taiyuan University of Science and TechnologyTaiyuan 030024China

Association in-between features has been demonstrated to improve the representation ability of data. However, the original association data reconstruction method may face two issues: the dimension of reconstructed data is undoubtedly higher than that of original data, and adopted association measure method does not well balance effectiveness and efficiency. To address above two issues, this paper proposes a novel association-based representation improvement method, named as AssoRep. AssoRep first obtains the association between features via distance correlation method that has some advantages than Pearson’s correlation coefficient. Then an improved matrix is formed via stacking the association value of any two features. Next, an improved feature representation is obtained by aggregating the original feature with the enhancement matrix. Finally, the improved feature representation is mapped to a low-dimensional space via principal component analysis. The effectiveness of AssoRep is validated on 120 datasets and the fruits further prefect our previous work on the association data reconstruction.

关键词： association representation distance correlation classification

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On construction of strong orthogonal arrays and column-orthogonal strong orthogonal arrays of strength two plus

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science China Mathematics 2025年第5期68卷 1219-1242页

作者： Bochuan Jiang Yaping Wang Fasheng Sun School of Mathematics and Statistics Beijing Jiaotong University Key Laboratory of Advanced Theory and Application in Statistics and Data Science Ministry of EducationSchool of Statistics East China Normal University Key Laboratory for Applied Statistics of Ministry of Education and School of Mathematics and Statistics Northeast Normal University

Computer experiments require space-filling designs with good low-dimensional projection *** orthogonal arrays are a type of space-filling design that provides better stratifications in low dimensions than ordinary orthogonal arrays. In this paper, we address the problem of constructing strong orthogonal arrays and column-orthogonal strong orthogonal arrays of strength two plus. Existing methods typically rely on regular designs or specific nonregular designs as base orthogonal arrays, limiting the sizes of the final ***, we propose two general methods that are easy to implement and applicable to a wide range of base orthogonal arrays. These methods produce space-filling designs that can accommodate a large number of factors,provide significant flexibility in terms of run sizes, and possess appealing low-dimensional projection ***, these designs are ideal for computer experiments.

关键词： computer experiment difference scheme strong orthogonal array column-orthogonality space-filling property

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Distributed asynchronous double accelerated optimization for ethylene plant considering delays

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Chinese Journal of Chemical Engineering 2025年 78卷 245-250页

作者： Wang, Ting Li, Zhongmei Du, Wenli State Key Laboratory of Industrial Control Technology East China University of Science and Technology Shanghai200237 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

Considering the complexity of plant-wide optimization for large-scale industries, a distributed optimization framework to solve the profit optimization problem in ethylene whole process is proposed. To tackle the delays arising from the residence time for materials passing through production units during the process with guaranteed constraint satisfaction, an asynchronous distributed parameter projection algorithm with gradient tracking method is introduced. Besides, the heavy ball momentum and Nesterov momentum are incorporated into the proposed algorithm in order to achieve double acceleration properties. The experimental results show that the proposed asynchronous algorithm can achieve a faster convergence compared with the synchronous algorithm. © 2024 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press Co., Ltd. (CIP)

关键词： Optimization algorithms

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Formation control and path planning of multi-robot systems via large language models

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science China(Information sciences) 2025年第5期68卷 72-88页

作者： Dong XUE Xuanjie ZHOU Ming WANG Fangzhou LIU Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and Technology Research Institute of Intelligent Control and Systems School of Astronautics Harbin Institute of Technology

Existing path planning and coordination control methods for multi-robot systems(MRS) typically rely on predefined rules and rudimentary algorithms. However, these methods often struggle to adapt flexibly to complex environments and to adjust motion targets appropriately. To address this challenge, this study presents a large language model(LLM)-assisted framework. By integrating textual descriptions of complex motion constraints, robot information, and local environmental data as inputs, LLMs generate motion objectives and translate them into executable control commands for the robots, thereby achieving coordinated control and path planning. This framework facilitates the generation, maintenance, and reshaping of formations in MRSs during path planning, applicable to both obstacle-free and obstacle-avoidance environments. Simulation results demonstrate that LLM-based control strategies enhance the autonomy, adaptability, flexibility, and robustness of MRS by processing complex information, making intelligent decisions, adapting to environmental changes, and handling disturbances and uncertainties.

关键词： multi-robot systems formation control path planning obstacle avoidance large language models

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Two efficient beamforming methods for hybrid IRS-aided AF relay wireless networks

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science China(Information sciences) 2025年第4期68卷 363-379页

作者： Xuehui WANG Qingbo LI Wen ZHU Feng SHU Mengxing HUANG Fuhui ZHOU Riqing CHEN Cunhua PAN Yongpeng WU Jiangzhou WANG School of Mathematics and Statistics Hainan Normal University Key Laboratory of Data Science and Smart Education Ministry of Education Hainan Normal University School of Information and Communication Engineering Hainan University Collaborative Innovation Center of Information Technology Hainan University School of Electronic and Optical Engineering Nanjing University of Science and Technology College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Digital Fujian Institute of Big Data for Agriculture Fujian Agriculture and Forestry University National Mobile Communications Research Laboratory Southeast University Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Jiao Tong University School of Engineering University of Kent

Owing to its ability to mitigate the double-fading effect by amplifying the reflected signal, the active intelligent reflecting surface(IRS) has garnered significant attention. In this paper, an amplify-and-forward(AF) relay network assisted by a hybrid IRS consisting of both passive and active units is developed. A signal-to-noise ratio(SNR) maximization problem is formulated, where the AF relay beamforming matrix and the hybrid IRS reflecting coefficient matrices for two-time slots need to be optimized. To address the SNR maximization problem, this paper proposes both a high-performance(HP) method and a low-complexity(LC) method. The HP method is based on the semidefinite relaxation and fractional programming(SDR-FP)algorithm, with rank-1 solutions obtained through Gaussian randomization. For the LC method, the amplification coefficient of each active IRS element is assumed to be equal. The SNR maximization problem is then addressed using the whitening filter,generalized power iteration, and generalized Rayleigh-Ritz(WF-GPI-GRR) approach. Simulation results show that compared with the benchmarks, such as the passive IRS-aided AF relay network, the proposed HP-SDR-FP and WF-GPI-GRR methods achieve significant rate improvements. In particular, the HP-SDR-FP and WF-GPI-GRR methods yield more than a 135.0%rate gain when the transmit power Ps of the source is 10 dBm. Furthermore, the proposed HP-SDR-FP method outperforms the WF-GPI-GRR method in terms of rate performance.

关键词： double-fading intelligent reflecting surface active elements passive elements hybrid IRS AF relay

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In an Ocean or a River:Bilinear Auto-Backlund Transformations and Similarity Reductions on an Extended Time-Dependent(3+1)-Dimensional Shallow Water Wave Equation

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China Ocean Engineering 2025年第1期39卷 160-165页

作者： GAO Xin-yi College of Science and Beijing Key Laboratory on Integration and Analysis of Large-Scale Stream DataNorth China University of TechnologyBeijing 100144China Beijing Laboratory of New Energy Storage Technology Beijing Municipal Education CommissionBeijing 102206China

With respect to oceanic fluid dynamics,certain models have appeared,e.g.,an extended time-dependent(3+1)-dimensional shallow water wave equation in an ocean or a river,which we investigate in this *** symbolic computation,we find out,on one hand,a set of bilinear auto-Backlund transformations,which could connect certain solutions of that equation with other solutions of that equation itself,and on the other hand,a set of similarity reductions,which could go from that equation to a known ordinary differential *** results in this paper depend on all the oceanic variable coefficients in that equation.

关键词： ocean river extended time-dependent(3+1)-dimensional shallow water wave equation bilinear auto-Bäcklund transformation similarity reduction symbolic computation

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