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Learning latent causal factors from the intricate sensor feedback of contact-rich robotic assembly tasks

ROBOTICS AND AUTONOMOUS systems 2025年 183卷

作者： Chen, Yurou Yu, Jiyang Lin, Zhenyang Shen, Liancheng Liu, Zhiyong 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 Chinese Acad Sci Ctr Excellence Brain Sci & Intelligence Technol Shanghai Peoples R China China Acad Space Technol Beijing Inst Spacecraft Syst Engn Beijing Peoples R China

Achieving precise robotic assembly is paramount for safety and performance in industrial settings. Conventional assembly methods require tedious manual adjustment of many parameters, and it is challenging to meet the assembly requirements with tight clearance. Robot learning has been at the forefront of research, showing potential for automation and intelligence in robotic operations. However, intricate information such as force feedback is indispensable for high-precision robot assembly tasks, and current learning methods grapple with processing this complex observation data due to discontinuous force changes during operation and the inherent noise from the force sensor. To enhance learning efficiency amidst challenging observations, this paper proposes introducing the concept of latent causal factors that drive sensor observations and hold paramount significance in assembly tasks. This paper analyses the impact of discontinuous and noisy observations and offers two ways to infer causal factors. Based on the implied latent factors, we propose a method that learns high- precision assembly policies from interacting with the environment. The algorithm's performance is evaluated in simulated and real-world nut insertion environments, demonstrating significant improvements over the previous methods. This research also underscores the promise of causal inference in addressing industrial challenges.

关键词： Causal inference Reinforcement learning Robotic manipulation Nut insertion

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Vision-Based Road Segmentation With Active Gaze control for Autonomous Vehicles

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IEEE-ASME TRANSACTIONS ON MECHATRONICS 2025年

作者： Xuan, Yuwen Chen, Jicheng Liu, Bin Wan, Xin Wen, Kai Chen, Long Zhang, Hui China Univ Petr Coll Mech & Transportat Engn Beijing 102249 Peoples R China Beihang Univ Sch Transportat Sci & Engn Beijing 102206 Peoples R China Beijing Inst Petrochem Technol Sch Informat Engn Beijing 102617 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

In this article, we aim to enhance the accuracy and usefulness of vision-based road segmentation for autonomous vehicles across various scenarios by actively controlling the gaze of the camera. The camera is mounted on a pan-tilt with two degrees of freedom as azimuth and elevation. The control of the azimuth is a follow-up PID control method mimicking the preview mechanism of human drivers. It is mainly used to improve the usefulness of the road segmentation in turning conditions. The control of the elevation is mainly used to improve the accuracy of the road segmentation in extreme external conditions, at the same time, taking into consideration of the usefulness. The elevation control method is inspired by the saccade-fixation mechanism of human eyes that scans the surrounding environment in the saccade mode and focuses on the object of interesting in the fixation mode. Similarly, the active camera will capture images of the current scene at different candidate elevations and select the optimal elevation. Experimental results demonstrate that the proposed active gaze control method effectively improves the performance of various road segmentation techniques under challenging conditions such as toward-light scenarios, U-turns, and low-speed situations.

关键词： Active vision bird's-eye-view (BEV) features preview point road segmentation

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Cardiovascular Outcomes in Patients with complex Type 2 Diabetes Mellitus Treated with the Dual SGLT Inhibitor Sotagliflozin: A Meta-analysis

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DIABETES THERAPY 2025年第3期16卷 485-498页

作者： Wang, Hong Zu, Quannan Lu, Ming Chen, Rongfa Tang, Zhangui Yang, Zhiren Peoples Hosp Guangxi Zhuang Autonomous Reg Dept Cardiol Nanning 530021 Guangxi Peoples R China Tianjin Univ Coll Management & Econ Tianjin 300072 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Huazhong Univ Sci & Technol Inst Cardiovasc Dis Tongji Med Coll Dept Endocrinol Wuhan 430032 Hubei Peoples R China

IntroductionScientific publications have shown sodium-glucose co-transporter-2 (SGLT2) inhibitors to have several beneficial effects in patients with complex type 2 diabetes mellitus (T2DM). However, sodium-glucose co-transporter-1 (SGLT-1) inhibitor is still under investigation in clinical trials. Recently, a dual inhibitor of sodium-glucose co-transporter (SGLT1/2), sotagliflozin, has been approved for use in patients with T2DM. In this analysis, we aimed to systematically compare the cardiovascular outcomes in patients with complex T2DM who were treated with the newly approved dual (SGLT 1 and 2) inhibitor *** databases, including Embase, MEDLINE, http://***, Web of Science, Google Scholar, the Cochrane database, and reference lists of relevant publications, were searched for publications comparing the novel SGLT1/2 inhibitor versus placebo for the treatment of patients with complex T2DM. The primary endpoint, including total number of deaths from cardiovascular causes, hospitalization for heart failure, and urgent visits for heart failure, death from cardiovascular causes, cardiac mortality, hospitalization for heart failure, non-fatal myocardial infarction, and total number of cardiac events, were considered as the endpoints in this analysis. The RevMan software version 5.4 was used to carry out the statistical analysis. Risk ratios (RR) with 95% confidence intervals (CI) were used to represent the data following *** total of 13,054 participants enrolled between 2017 and 2020 were included in this analysis, with 6734 participants assigned to sotagliflozin and 6320 assigned to placebo. The results of this analysis showed that the primary endpoint was significantly in favor of sotagliflozin with (RR: 0.73, 95% CI 0.67-0.80;P = 0.00001). Hospitalization for heart failure (RR: 0.67, 95% CI 0.60-0.75;P = 0.00001) and the total number of cardiac events (RR: 0.73, 95% CI 0.67-0.79;P = 0.00001) were also sign

关键词： Dual SGLT inhibitor Sotagliflozin Diabetes mellitus Heart failure Cardiovascular mortality Chronic kidney disease

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Coordinated Adaptive Impedance control of Redundantly Actuated Parallel Manipulators

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IEEE TRANSACTIONS ON HUMAN-MACHINE systems 2025年

作者： Ma, Nan Cheneler, David He, Guangping Yuan, Junjie Bian, Gui-Bin Northwestern Polytech Univ Sch Mech & Elect Engn Xian 710072 Peoples R China Univ Lancaster Sch Engn Lancaster LA1 4YW England North China Univ Technol Dept Mech & Elect Engn Beijing 100144 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Redundantly actuated parallel mechanisms (RAPMs) have been widely adopted in advanced robotic systems and precision machine tools. It has been demonstrated that redundant actuation can improve the performance of mechatronic systems but introduce challenges with respect to control. One main difficulty is in establishing an accurate dynamic model of the RAPM system. With an inaccurate dynamic model, the torque applied by the actuators will be incorrect, leading to increased antagonistic forces in the system. To solve this problem, a novel coordinated adaptive impedance control approach based on a new adaptive impedance control law is presented here, along with proof of the stability of the closed-loop system. The control algorithm has been validated experimentally by a prototype cable-driven parallel manipulator. It can be seen from the experimental results that the proposed control method is an effective way to correct the antagonistic forces of the system, thus facilitating the improvement of its dynamic performance and its efficacy in different applications.

关键词： Impedance Robots Adaptation models Robot kinematics Actuators Stability analysis Kinematics Wires Steel Manipulator dynamics Actuation redundancy adaptive impedance control coordination control parallel manipulators uncertain model

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Completed Interaction Networks for Pedestrian Trajectory Prediction

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IEEE Transactions on Multimedia 2025年

作者： Zhang, Zhong Zhou, Jianglin Liu, Shuang Xiao, Baihua Tianjin Normal University Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission Tianjin300387 China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing100190 China

The social and environmental interactions, as well as the pedestrian goal are crucial for pedestrian trajectory prediction. This is because they could learn both complex interactions in the scenes and the intentions of the pedestrians. However, most existing methods either learn the one-moment social interactions, or supervise the pedestrian trajectories using long-term goal, resulting in suboptimal prediction performances. In this paper, we propose a novel network named Completed Interaction Network (CINet) to simultaneously consider the social interactions in all moments, the environmental interactions and the short-term goal of pedestrians in a unified framework for pedestrian trajectory prediction. Specifically, we propose the Spatio-Temporal Transformer Layer (STTL) to fully mine the spatio-temporal information among historical trajectories of all pedestrians in order to obtain the social interactions in all moments. Additionally, we present the Gradual Goal Module (GGM) to capture the environmental interactions under the supervision of the short-term goal, which is beneficial to understanding the intentions of the pedestrian. Afterwards, we employ the cross-attention to effectively integrate the all-moment social and environmental interactions. The experimental results on three standard pedestrian datasets, i.e., ETH/UCY, SDD and inD demonstrate that our method achieves a new state-of-the-art performance. Furthermore, the visualization results indicate that our method could predict trajectories more reasonably in complex scenarios such as sharp turns, infeasible areas and so on. © 1999-2012 IEEE.

关键词： Prediction models

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Probabilistic Data-Driven Modeling of a Melt Pool in Laser Powder Bed Fusion Additive Manufacturing

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 4908-4925页

作者： Fang, Qihang Xiong, Gang Zhao, Meihua Tamir, Tariku Sinshaw Shen, Zhen Yan, Chao-Bo Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat Beijing Engn Res Ctr Intelligent Syst & Technol State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Chinese Acad Sci Guangdong Engn Res Ctr Printing & Intelligent Mfg Cloud Comp Ctr Dongguan 523808 Peoples R China Guangdong Univ Technol State Key Lab Precis Elect Mfg Technol & Equipment Guangzhou Peoples R China Debre Markos Univ Inst Technol Debre Markos 269 Ethiopia Xi An Jiao Tong Univ Fac Elect & Informat Engn State Key Lab Mfg Syst Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Fac Elect & Informat Engn Sch Automat Sci & Engn Xian 710049 Shaanxi Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

The widespread adoption of laser powder bed fusion (LPBF) additive manufacturing is hampered by process unreliability problems. Modeling the melt pool behavior in LPBF is crucial to develop process control methods. While data-driven models linking melt pool dynamics to specific process parameters have shown appreciable advancements, existing models often oversimplify these relationships as deterministic, failing to account for the inherent instability of LPBF processes. Such simplifications can lead to overconfident and unreliable predictions, potentially resulting in erroneous process decisions. To address this critical issue, we propose a probabilistic data-driven approach to melt pool modeling that incorporates process noise and uncertainty. Our framework formulates a problem that includes distribution approximation and uncertainty quantification. Specifically, the Gaussian distribution with higher order priors, aided with variational inference and importance sampling, is used to approximate the probability distribution of melt pool characteristics. The uncertainty inherent in both LPBF process data and the modeling approach itself are then decomposed and approximated by using Monte Carlo sampling. The melt pool model is improved further by using a novel grid-based representation for the neighborhood of a fusion point, and a neural network architecture designed for effective feature fusion. This approach not only refines the accuracy of the model but also quantifies the uncertainty of the predictions, thereby enabling more informed decision-making with reduced risk. Two potential applications, including LPBF process planning and anomaly detection, are discussed. The implementation of our model is available at https://***/qihangGH/probabilistic_melt_pool_model. Note to Practitioners-Modeling the melt pool behavior in laser powder bed fusion (LPBF) processes is pivotal for enhancing its quality control. However, a problem is that most existing data-driven me

关键词： Laser powder bed fusion (LPBF) additive manufacturing melt pool uncertainty quantification quality control process planning anomaly detection Laser powder bed fusion (LPBF) additive manufacturing melt pool uncertainty quantification quality control process planning anomaly detection

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A Railway Traffic management Advisory System for High-Speed Trains in Case of Emergencies

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IEEE INTELLIGENT TRANSPORTATION systems MAGAZINE 2025年

作者： Zhou, Min Yuan, Zhilu Wu, Xingtang Dong, Hairong Wang, Fei-Yue Beijing Jiaotong Univ Sch Automat & Intelligence Beijing 100044 Peoples R China Shenzhen Univ Sch Architecture & Urban Planning Shenzhen 518060 Peoples R China North China Elect Power Univ Sch Control & Comp Engn Beijing 100096 Peoples R China Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China Chinese Acad Sci CASIA Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macau Inst Syst Engn Macau 999078 Peoples R China

The timetable is vulnerable to the impact of emergencies such as severe weather and equipment faults, potentially disrupting train services. Swift and efficient timetable adjustments are crucial for maintaining the operational efficiency of high-speed railways (HSRs). This study introduces a railway traffic management advisory system (RTMAS) tailored for high-speed trains, aiding dispatchers in the rapid rescheduling of timetables during emergencies. The RTMAS's structure and its emergency handling protocols are designed with an emphasis on human-in-the-loop and user-friendly principles. The core modules, including risk event scenarios, delay time prediction, expert systems, rescheduling scheme generation, and strategy evaluation systems, and their functions are given from the whole process of the dispatchers' emergency responses. The system employs metaheuristic algorithms and deep reinforcement learning (DRL) for predicting delays and generating rescheduling plans. A practical examination of the Beijing-Shanghai HSR Line validates the effectiveness of the RTMAS. The results indicate that the system not only furnishes dispatchers with near-optimal rescheduling solutions but also markedly diminishes total delays and the number of trains impacted by emergencies.

关键词： Railroads

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Generalized Discrete-Time Variable Gain ADRC for Nonlinear systems and Its Application to Parallel Teleoperated Manipulators

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IEEE TRANSACTIONS ON CIRCUITS AND systems I-REGULAR PAPERS 2025年第6期72卷 2868-2877页

作者： Gu, Shaomeng Zhang, Jinhui Cheng, Long Wu, Yuanqing Yanshan Univ Inst Elect Engn Qinhuangdao 066004 Peoples R China Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat Beijing 100190 Peoples R China Sun Yat Sen Univ Sch Intelligent Syst Engn Shenzhen 518107 Peoples R China

In this paper, we propose a novel generalized discrete-time variable gain active disturbance rejection control (DTVGADRC) method for the n-th order discrete-time nonlinear systems. The error-driven generalized DTVGADRC can dynamically improve the control performances, including generalized discrete-time variable gain tracking differentiator (DTVGTD), generalized discrete-time variable gain extended state observer (DTVGESO), and generalized discrete-time variable gain controller (DTVGC). Furthermore, the stability analysis of generalized DTVGADRC is performed, and the parameters in the variable gain functions are determined by the theoretical analysis. Finally, the generalized DTVGADRC method is applied to parallel teleoperated manipulators, and the experiment results are presented to illustrate effectiveness of the proposed method.

关键词： Digital TV Gain Nonlinear dynamical systems Transient analysis Sufficient conditions Stability analysis Convergence state estimation Manipulator dynamics Automation Nonlinear systems active disturbance rejection control tracking differentiator extended state observer variable gain parallel teleoperated manipulators

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Adaptive Fuzzy Nonsingular Fixed-Time Bipartite Consensus Tracking Using Adding Power Integration Technique for Stochastic Nonlinear Constrained MASs

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IEEE TRANSACTIONS ON FUZZY systems 2025年第3期33卷 947-958页

作者： Niu, Ben Zhu, Yan Liu, Yingying Shang, Zihao Wang, Ding Wang, Huanqing Wang, Wencheng Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Bohai Univ Dept Math Sci Jinzhou 121000 Peoples R China Bohai Univ Automatizat Inst Jinzhou 121000 Peoples R China Weifang Univ Coll Machinery & Automat Weifang 261061 Peoples R China

In this article, the adaptive fuzzy fixed-time bipartite consensus tracking control problem is studied for stochastic nonlinear multi-agent systems with unknown control gains and time-varying output constraints. First, in order to address the difficulties arising from the unknown control gains, the Nussbaum technique is employed. In the meantime, the $tan$-type nonlinear mapping function is introduced, which guarantees the predefined output constraints are not violated. Then, different from the previous control strategies in which they only focused on the balanced directed topology, the classification optimization algorithm is presented to accomplish the bipartite consensus tracking control according to the structurally unbalanced directed topology. Besides, by combining the adaptive backstepping technique with the adding power integration methodology, the nonsingular fixed-time control strategy is proposed. The proposed adaptive fuzzy fixed-time control strategy ensures that the bipartite consensus tracking errors converge to a region near zero in fixed time and all the signals in the closed-loop system are bounded in probability. Last, the effectiveness of the presented control scheme is demonstrated with a simulation example.

关键词： Adding power integration technique bipartite consensus control fixed-time fixed-time stochastic nonlinear multi-agent systems (MASs) stochastic nonlinear multi-agent systems (MASs) time-varying output constraints time-varying output constraints time-varying output constraints

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Federated Services: A Smart Service Ecology with Federated Security for Aligned Data Supply and Scenario-Oriented Demands

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IEEE/CAA Journal of Automatica Sinica 2025年第5期12卷 925-936页

作者： Jia, Xiaofeng Li, Juanjuan Wang, Shouwen Qi, Hongwei Wang, Fei-Yue Qin, Rui Zhang, Min Liang, Xiaolong Beijing Big Data Centre Beijing100101 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Technology Company Ltd. Beijing100190 China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Macao999078 China

This paper introduces federated services as a smart service ecology with federated security to align distributed data supply with diversified service demands spanning digital and societal contexts. It presents the comprehensive researches on the theoretical foundation and technical system of federated services, aiming at advancing our understanding and implementation of this novel service paradigm. First, a thorough examination of the characteristics of federated security within federated services is conducted. Then, a five-layer technical framework is formulated under a decentralized intelligent architecture, ensuring secure, agile, and adaptable service provision. On this basis, the operational mechanisms underlying data federation and service confederation is analyzed, with emphasis on the smart supply-demand matching model. Furthermore, a scenario-oriented taxonomy of federated services accompanied by illustrative examples is proposed. Our work offers actionable insights and roadmap for realizing and advancing federated services, contributing to the refinement and wider adoption of this transformative service paradigm in the digital era. © 2014 Chinese Association of Automation.

关键词： Decentralized autonomous organizations and operations decentralized physical infrastructure networks federated security federated services multimodal large language models smart contracts

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