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Soft Resource Slicing for Industrial Mixed Traffic in 5G Networks

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 463-465页

作者： Jingfang Ding Meng Zheng Haibin Yu the State Key Laboratory of Robotics and the Key Laboratory of Networked Control Systems Chinese Academy of Sciences the Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences the University of Chinese Academy of Sciences IEEE

Dear Editor,This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.

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Joint Probabilistic Scheduling and Resource Allocation for Wireless Networked control Systems

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 258-260页

作者： Meng Zheng Lei Zhang Wei Liang IEEE the State Key Laboratory of Robotics and the Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences the University of Chinese Academy of Sciences

Dear Editor,This letter presents a joint probabilistic scheduling and resource allocation method(PSRA) for 5G-based wireless networked control systems(WNCSs). As a control-aware optimization method, PSRA minimizes the linear quadratic Gaussian(LQG) control cost of WNCSs by optimizing the activation probability of subsystems, the number of uplink repetitions, and the durations of uplink and downlink phases. Simulation results show that PSRA achieves smaller LQG control costs than existing works.

关键词： Networked control systems

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Characteristic model-based control of aerial manipulator for improved interaction stability

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Science China(Technological Sciences) 2025年第4期68卷 166-178页

作者： Bingkai XIU Zhan LI Yipeng YANG Huijun GAO Research Institute of Intelligent Control and Systems Harbin Institute of TechnologyHarbin150001China State Key Laboratory of Robotics and Systems(HIT) Harbin Institute of TechnologyHarbin150001China

Maintaining contact stability is crucial when the aerial manipulator interacts with the surrounding environment. In this paper, a novel output feedback framework based on a characteristic model is proposed to improve the contact stability of the aerial manipulator. First, only position measurements of the aerial manipulator are introduced to design the practical finite-time command filter-based force observer. Second, an attitude control architecture including characteristic modeling and controller design is presented. In the modeling part, input-output data is utilized to build the characteristic model with fewer parameters and a simpler structure than the traditional dynamic model. Different from conventional control methods, fewer feedback values,namely only angle information, are required for designing the controller in the controller part. In addition, the convergence of force estimation and the stability of the attitude control system are proved by the Lyapunov analysis. Numerical simulation comparisons are conducted to validate the effectiveness of the attitude controller and force observer. The comparative results demonstrate that the tracking error of x and θ channels decreases at least 10.62% and 10.53% under disturbances and the force estimation precision increases at least 45.19% in the different environmental stiffness. Finally, physical flight experiments are conducted to validate the effectiveness of the proposed framework by a self-built aerial manipulator platform.

关键词： aerial manipulator interaction stability contact force observer characteristic model

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Aggressive and robust low-level control and trajectory tracking for quadrotors with deep reinforcement learning

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Neural Computing and Applications 2025年第3期37卷 1223-1240页

作者： Chen, Shiyu Li, Yanjie Lou, Yunjiang Lin, Ke Department of Control Science and Engineering Harbin Institute of Technology Shenzhen Shenzhen518055 China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China

Executing accurate trajectory tracking tasks using a high-performance low-level controller is crucial for quadrotors to be applied in various scenarios, especially those involving uncertain disturbances. However, due to the uncertainties in disturbed environments, developing effective low-level controllers with traditional model-based control schemes is challenging. This paper presents an aggressive and robust reinforcement learning (RL)-based low-level control policy for quadrotors. The policy maps the observed quadrotor state directly to motor thrust commands, without requiring the quadrotor dynamics. Additionally, a trajectory generation pipeline is developed to improve the accuracy of trajectory tracking tasks based on differential flatness. With the learned low-level control policy, extensive simulations and real-world experiments are implemented to validate the performance of the policy. The results indicate that our RL-based low-level control policy outperforms traditional proportional–integral–derivative (PID) control methods and related learning-based policies in terms of accuracy and robustness, particularly in environments with uncertain disturbances. Furthermore, the proposed RL-based control policy exhibits an aggressive response in trajectory tracking, even when the speed of the desired trajectory is increased to 6 m/s. Moreover, the learned policy demonstrates strong vibration suppression capabilities and enables the quadrotor to recover to a hovering state from random initial conditions with shorter response time. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Deep reinforcement learning

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MATD3-Based End-Edge Collaborative Resource Optimization for NOMA-Assisted Industrial Wireless Networks

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Computers, Materials & Continua 2025年第2期82卷 3203-3222页

作者： Ru Hao Chi Xu Jing Liu College of Information Engineering Shenyang University of Chemical TechnologyShenyang110142China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang110016China

Non-orthogonal multiple access (NOMA) technology has recently been widely integrated into multi-access edge computing (MEC) to support task offloading in industrial wireless networks (IWNs) with limited radio resources. This paper minimizes the system overhead regarding task processing delay and energy consumption for the IWN with hybrid NOMA and orthogonal multiple access (OMA) schemes. Specifically, we formulate the system overhead minimization (SOM) problem by considering the limited computation and communication resources and NOMA efficiency. To solve the complex mixed-integer nonconvex problem, we combine the multi-agent twin delayed deep deterministic policy gradient (MATD3) and convex optimization, namely MATD3-CO, for iterative optimization. Specifically, we first decouple SOM into two sub-problems, i.e., joint sub-channel allocation and task offloading sub-problem, and computation resource allocation sub-problem. Then, we propose MATD3 to optimize the sub-channel allocation and task offloading ratio, and employ the convex optimization to allocate the computation resource with a closed-form expression derived by the Karush-Kuhn-Tucker (KKT) conditions. The solution is obtained by iteratively solving these two sub-problems. The experimental results indicate that the MATD3-CO scheme, when compared to the benchmark schemes, significantly decreases system overhead with respect to both delay and energy consumption.

关键词： Industrial wireless networks(IWNs) multi-access edge computing(MEC) non-orthogonal multiple access(NOMA) task offloading resource allocation

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Real-Time Multi-object Tracking Using YOLOv8 and SORT on a SoC FPGA 21st

Real-Time Multi-object Tracking Using YOLOv8 and SORT on a...

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21st International Symposium on Applied Reconfigurable Computing, ARC 2025

作者： Danilowicz, Michal Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Krakow Poland

ISBN: (纸本)9783031879944

Multi-object tracking (MOT) is one of the most important problems in computer vision and a key component of any vision-based perception system used in advanced autonomous mobile robotics. Therefore, its implementation on low-power and real-time embedded platforms is highly desirable. Modern MOT algorithms should be able to track objects of a given class (e.g. people or vehicles). In addition, the number of objects to be tracked is not known in advance, and they may appear and disappear at any time, as well as be obscured. For these reasons, the most popular and successful approaches have recently been based on the tracking paradigm. Therefore, the presence of a high quality object detector is essential, which in practice accounts for the vast majority of the computational and memory complexity of the whole MOT system. In this paper, we propose an FPGA (Field-Programmable Gate Array) implementation of an embedded MOT system based on a quantized YOLOv8 detector and the SORT (Simple Online Realtime Tracker) tracker. We use a modified version of the FINN framework to utilize external memory for model parameters and to support operations necessary required by YOLOv8. We discuss the evaluation of detection and tracking performance using the COCO and MOT15 datasets, where we achieve 0.21 mAP and 38.9 MOTA respectively. As the computational platform, we use an MPSoC system (Zynq UltraScale+ device from AMD/Xilinx) where the detector is deployed in reprogrammable logic and the tracking algorithm is implemented in the processor system. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： System-on-chip

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An intelligent matching method for the equivalent circuit of electrochemical impedance spectroscopy based on Random Forest

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材料科学技术（英文版） 2025年第6期209卷 300-310页

作者： Wenbo Chen Bingjun Yan Aidong Xu Xin Mu Xiufang Zhou Maowei Jiang Changgang Wang Rui Li Jie Huang Junhua Dong Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110169China Shenyang Institute of Automation Chinese Academy of SciencesShenyang 110169China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110169China Shenyang Institute of Automation Chinese Academy of SciencesShenyang 110169China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China General Research Institute China Oil & Gas Pipeline Network CorporationLangfang 065000China

One of the core works of analyzing Electrochemical Impedance Spectroscopy(EIS)data is to select an appropriate equivalent circuit model to quantify the parameters of the electrochemical reaction ***,this process often relies on human experience and judgment,which will introduce subjectivity and *** this paper,an intelligent approach is proposed for matching EIS data to their equivalent circuits based on the Random Forest *** can automatically select the most suitable equivalent circuit model based on the characteristics and patterns of EIS *** the typical scenario of metal corrosion,an atmospheric corrosion EIS dataset of low-carbon steel is constructed in this paper,which includes five different corrosion *** dataset was used to validate and evaluate the pro-posed method in this *** contributions of this paper can be summarized in three aspects:(1)This paper proposes a method for selecting equivalent circuit models for EIS data based on the Random Forest algorithm.(2)Using authentic EIS data collected from metal atmospheric corrosion,the paper es-tablishes a dataset encompassing five categories of metal corrosion scenarios.(3)The superiority of the proposed method is validated through the utilization of the established authentic EIS *** ex-periment results demonstrate that,in terms of equivalent circuit matching,this method surpasses other machine learning algorithms in both precision and ***,it shows strong applicability in the analysis of EIS data.

关键词： Electrochemical impedance spectroscopy Random forest Corrosion Equivalent circuit model

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Semi-Autonomous Navigation Based on Local Semantic Map for Mobile Robot

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Journal of Shanghai Jiaotong university(Science) 2025年第1期30卷 27-33页

作者： ZHAO Yanfei XIAO Peng WANG Jingchuan GUO Rui Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai200240China State Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240China State Grid Intelligence Technology Co. Ltd.Jinan250013China

Mobile robots represented by smart wheelchairs can assist elderly people with mobility *** paper proposes a multi-mode semi-autonomous navigation system based on a local semantic map for mobile robots,which can assist users to implement accurate navigation(e.g.,docking)in the environment without prior *** order to overcome the problem of repeated oscillations during the docking of traditional local path planning algorithms,this paper adopts a mode-switching method and uses feedback control to perform docking when approaching semantic *** last,comparative experiments were carried out in the real *** show that our method is superior in terms of safety,comfort and docking accuracy.

关键词： semi-autonomous navigation mobile robot semantic map voice interaction

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Distributed Adaptive Tracking control for Fuzzy Nonlinear MASs Under Round-Robin Protocol

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IEEE Transactions on Fuzzy Systems 2025年第5期33卷 1488-1498页

作者： Fan, Sha Meng, Min Fu, Yukai Deng, Chao Nanjing University of Posts and Telecommunications College of Automation College of Artificial Intelligence Nanjing210023 China Tongji University Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai200070 China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Nanjing University of Posts and Telecommunications Institute of Advanced Technology Nanjing210049 China

In this article, the cooperative fuzzy tracking control problem for a type of high-order nonlinear multi-agent systems under the Round-Robin (RR) communication protocol is solved. To effectively reduce the communication among agents, an RR communication protocol is first proposed, where each agent can communicate with only one neighbor at any given time. Based on the developed communication protocol, a hierarchical control approach is introduced, consisting of a distributed observer layer that utilizes information from both local and neighboring agents, and a decentralized control layer that operates solely based on local agent information. Specifically, a distributed observer is designed in the distributed observer layer to achieve the distributed observation objective by introducing a time-varying gain in the observer input. Furthermore, an improved distributed observer with the upper triangular form is constructed to produce a signal with high-order derivatives. In the decentralized control layer, fuzzy adaptive controllers are designed for all agents by using the backstepping technique. By using the Lyapunov stability theory, rigorous stability analysis shows that the cooperative fuzzy tracking control problem is solved under the developed hierarchical control approach. In the end, a simulation example is presented to demonstrate the validity of our proposed method. © 1993-2012 IEEE.

关键词： Protocols Observers Stability analysis Decentralized control Backstepping Vectors Symmetric matrices Network topology Telecommunications System dynamics

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Risk Assessment Based Time-adjusted Optimization for Safe and Fast Flight of Quadrotor UAVs

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IEEE Transactions on Vehicular Technology 2025年

作者： Zhu, Hai Li, Baoquan Yin, Haolin Zhang, Xuebo Tiangong University School of Control Science and Engineering The Tianjin Key Laboratory of Intelligent Control of Electrical Equipment Tianjin300387 China Nankai University Institute of Robotics and Automatic Information Systems The Tianjin Key Laboratory of Intelligent Robotics Tianjin300071 China

Generating an executable reference trajectory in realtime is a core of autonomous navigation for a quadrotor unmanned aerial vehicle (UAV). In the paper, a timeadjusted optimization method is proposed for UAV motion planning to achieve safe and fast flight. Firstly, based on parameterization for uniform B-spline trajectories, relationship of knot spans and UAV speeds is analyzed, and an iterative velocity restrict algorithm is introduced to tackle nonexecutable flight. Subsequently, combining start and target points in local planning, an evaluation criterion function is designed with control points of the above trajectory and directions of collision avoidance. On this basis, risk assessment is conducted according to surrounding environments, where four phases of passing obstacles is constructed by considering risk level variation. Then, the weight function in each phase is determined by relationship of obstacle and planned local trajectory. Moreover, time intervals of B-spline trajectories are adjusted to obtain nonuniform trajectories, so as to affect UAV speeds. Simulation and experiment are conducted with comparison to verify performance of the proposed method. © 2025 IEEE.

关键词： Risk assessment

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