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Multiscale Skeleton-Based Temporal Action Segmentation Using Hierarchical Temporal Modeling and Prediction Ensemble

IEEE Transactions on Cybernetics 2025年第6期55卷 2779-2791页

作者： Chen, Bowen Nie, Wei Ji, Haoyu Ren, Weihong Tong, Qiyi Wang, Zhiyong Liu, Honghai State Key Laboratory of Robotics and Systems Shenzhen518055 China School of Biomedical Engineering Shenzhen518055 China State Key Laboratory of Robotics and Systems School of Biomedical Engineering Shenzhen518055 China

Skeleton-based temporal action segmentation (TAS) decomposes untrimmed skeleton sequence into meaningful segments. The variance in temporal scale challenges the skeleton modeling network to seek a balance between over-segmentation and under-segmentation. Current methods often rely on parallel multiscale feature extractors and additional refinement modules to mitigate the multiscale issue, which brings significant computations and complexity. To address these issues, this article proposes multiscale skeleton-based TAS (MSTAS), consisting of temporal probability pyramid (TPP) and smoothed multiscale ensemble (SME). TPP represents each action as a collection of multiscale probability distributions using a U-shape hierarchical temporal pyramid. Subsequently, SME takes the average of distributions instead of deploying additional refinement stages to achieve action segmentation. Considering the over-confident issue that exists in each scale, SME incorporates a novel label smoothing phase to improve the probability distributions by dynamically calibrating the confidence of each scale. Experimental results on four public datasets show that the MSTAS achieves state-of-the-art performance with less computation overheads, such as +1.1% accuracy and +2.8% F1@0.5 on the challenging LARa dataset with 70% fewer parameters and 80% fewer GFLOPS. Benefiting from confidence calibration, the MSTAS efficiently utilizes more temporal scales while keeping better calibration for ambiguous action instances. Additionally, the U-shape pyramid demonstrates a strong compatibility with classical refinement module, enabling the efficient extraction of multiscale motion representations. © 2013 IEEE.

关键词： Musculoskeletal system

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Understanding the Machining Process of Hierarchical Micro/Nanograting Structures Used for Optical Variable Device

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Chinese Journal of Mechanical engineering 2025年第1期38卷 161-185页

作者： Yanquan Geng Wenhan Zhu Xiaosong Zhang Aoxiang Zhang Yongda Yan Hailong Cui Bo Xue Jiqiang Wang TState Key Laboratory of Robotics and Systems Robotics InstituteHarbin Institute of TechnologyHarbin 150080China Sichuan Precision and Ultra-Precision Machining Engineering Technology Center Chengdu 610200China College of Mechanical and Electrical Engineering Northeast Forestry UniversityHarbin 150040China

Hierarchical micro/nanograting structures have attracted increasing attention owing to their significant applications in the fields of structural coloring,anti-counterfeiting,and ***,the fabrication of hierarchical micro/nanograting structures is important for these *** this study,a strategy for machining hierarchical micro/nanograting structures is developed by controlling the tool movement trajectory.A coupling Euler-Lagrange finite element model is established to simulate the machining *** effect of the machining methods on the nanograting formation is demonstrated,and a suitable machining method for reducing the cutting force is *** height of the nanograting decreases with an increase in the tool edge ***,optical variable devices(OVDs)are machined using an array overlap machining *** schemes for the parallel column unit crossover and column unit in the groove crossover are designed to achieve high-quality machining of *** coloring of the logo of the Harbin Institute of Technology and the logo of the centennial anniversary of the Harbin Institute of Technology on the surface of metal samples,such as aluminum alloys,is *** findings of this study provide a method for the fabrication of hierarchical micro/nanograting structures that can be used to prepare OVDs.

关键词： Hierarchical micro/nanograting structures Optical variable devices Finite element simulation Tool trajectory controlling

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Leader-follower:Human-centered intention-guided controller for novel SuperLimb with application to load-carrying scenarios

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Science China(Technological Sciences) 2025年第1期68卷 321-334页

作者： Qinghua ZHANG Xianglong LI Hongwei JING Kerui SUN Yuancheng LI Sikai ZHAO Lele LI Haotian JU Ziqi WANG Rui WU Tianjiao ZHENG Jie ZHAO Yanhe ZHU The State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China The Learning Algorithms and Systems Laboratory School of EngineeringÉcole Polytechnique Fédérale de LausanneLausanne CH 101510587Switzerland

Supernumerary robotic arms(SuperLimb)are a new type of wearable robot that works closely with humans as a third hand to augment human operation *** conveyance of wearers'intentions,allocation of roles,and humancentered interaction considerations are the key points in the process of human-SuperLimb *** paper proposes a human-centered intention-guided leader-follower controller that relies on the dynamic modeling of SuperLimb with application to load-carrying *** proposed leader-follower controller takes the human as the leader and the SuperLimb as the follower,achieving effective information communication,autonomous coordination,and good force compliance between SuperLimb,humans,and the environment under human safety ***,the human-SuperLimb dynamic system is modeled to achieve force interaction with the environment and ***,to achieve the precise intention extraction of humans,pose data from five visual odometry sensors are fused to capture the human state,the generalized position,the velocity of hands,and the surface electromyography signals from two myoelectric bracelets sensors are processed to recognize the natural hand gestures during load-carrying scenarios by a designed Swin transformer ***,based on the real-time distance detection between human and mechanical limbs,the security assurance and force-compliant interaction of the human-SuperLimb system are ***,the human hand muscle intention recognition,human-robot safety strategy verification,and comparative load-carrying experiments with and without the proposed method are conducted on the SuperLimb *** showed that the task parameters are well estimated to produce more reasonable planning trajectories,and SuperLimb could well understand the wearer's intentions to switch different SuperLimb *** proposed sensor-based human-robot communication framework motivates future studies of other collaboration scenes fo

关键词： SuperLimb leader-follower human intention estimation human-robot safety human-robot communication

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Bioinspired Sensing of Undulatory Flow Fields Generated by Leg Kicks in Swimming

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IEEE Transactions on Automation Science and engineering 2025年 22卷 13895-13906页

作者： Wang, Jun Shen, Tongsheng Zhao, Dexin Zhang, Feitian Peking University State Key Laboratory of Turbulence and Complex Systems College of Engineering Department of Advanced Manufacturing and Robotics Beijing100871 China National Innovation Institute of Defense Technology Beijing100071 China

The artificial lateral line (ALL) is a bioinspired flow sensing system for underwater robots, comprising of distributed flow sensors. The ALL has been successfully applied to detect the undulatory flow fields generated by body undulation and tail-flapping of bioinspired robotic fish. However, its feasibility and performance in sensing the undulatory flow fields produced by human leg kicks during swimming have not been systematically tested and studied. This paper presents a novel sensing framework to investigate the undulatory flow field generated by swimmer’s leg kicks, leveraging bioinspired ALL sensing. To evaluate the feasibility of using the ALL system for sensing the undulatory flow fields generated by swimmer leg kicks, this paper designs an experimental platform integrating an ALL system and a lab-fabricated human leg model. To enhance the accuracy of flow sensing, this paper proposes a feature extraction method that dynamically fuses time-domain and time-frequency characteristics. Specifically, time-domain features are extracted using one-dimensional convolutional neural networks and bidirectional long short-term memory networks (1DCNN-BiLSTM), while time-frequency features are extracted using short-term Fourier transform and two-dimensional convolutional neural networks (STFT-2DCNN). These features are then dynamically fused based on attention mechanisms to achieve accurate sensing of the undulatory flow field. Furthermore, extensive experiments are conducted to test various scenarios inspired by human swimming, such as leg kick pattern recognition and kicking leg localization, achieving satisfactory results. © 2004-2012 IEEE.

关键词： Long short-term memory

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A Novel Technology for Semiautomatic and Automatic Stem–Stake Coupling of Seedlings and Plants

IEEE Transactions on AgriFood Electronics

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IEEE Transactions on AgriFood Electronics 2025年第1期3卷 254-262页

作者： Shirzi, Moteaal Asadi Kermani, Mehrdad R. Western University Advanced Robotics and Mechatronic Systems Laboratory Electrical and Computer Engineering Department LondonN6A 5B9 Canada Western University Department of Electrical and Computer Engineering LondonN6A 3K7 Canada Advanced Robotics and Mechatronic Systems Laboratory LondonN6A 5B9 Canada

This article introduces a novel mechatronic system for coupling the stems of seedlings and plants to wooden stakes or ropes, a crucial process for supporting them during growth, transportation, and fruiting in plant propagation facilities and greenhouses. The stem–stake coupling device utilizes interconnected mechanisms and an impedance control method to adjust motor torque and speed, shaping metallic wire into clips of various shapes and dimensions, effectively securing plant stems to stakes or ropes. In a robotic system, a claw-shaped arm mechanism, a stereo camera, and real-time vision techniques are integrated into the stem–stake coupling device to identify the optimal coupling point and automate the coupling task. This innovation addresses the labor-intensive task of manual coupling, offering a scalable solution for growers through handheld devices or fully automated robotic systems. In the context of increasing labor shortages and rising costs, the technology offers a sustainable and efficient alternative with significant potential to enhance operational efficiency in greenhouses and propagation facilities. © 2023 IEEE.

关键词： Seed

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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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Adaptive Closed-Loop Functional Electrical Stimulation System with Visual Feedback for Enhanced Grasping in Neurological Impairments

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical robotics and Bionics 2025年第2期7卷 678-686页

作者： Lin, Chengyu Cheng, Kong Hoi Pan, Wei Sun, Jinxin Gou, Guotao Fu, Junyun Leng, Yuquan Fu, Chenglong Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Department of Mechanical and Energy Engineering Shenzhen518055 China Guilin University of Electronic Technology Guangxi Human Physiological Information Non Invasive Detection Engineering Technology Research Center School of Life and Environmental Sciences Guilin541004 China

Grasping is a critical motor skill essential for daily activities, but it is often compromised in individuals with neural impairments. Functional Electrical Stimulation (FES) has emerged as a promising intervention, utilizing electrical pulses to stimulate muscles and thereby restore impaired motor functions. However, existing closed-loop FES systems depend on pre-calibrated angles or forces specific to individual objects, which limits their practicality in dynamic, real-world environments with varying object *** paper presents a novel closed-loop FES (CLFES) system with visual feedback, designed to dynamically adjust stimulation parameters based on real-time interaction states without requiring object-specific calibration. The system employs a finite state machine to manage sequential grasp-release tasks and integrates a visual perception module for slip detection and intent recognition. The system was tested with two individuals with disabilities on five common household objects. Experimental results demonstrate significant improvements, including a 42.6% increase in success rate and a 45.9% reduction in task completion time compared to tasks performed without the system. These results underscore the system’s potential to improve daily task performance for individuals with neural impairments. © 2018 IEEE.

关键词： Visual servoing

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A Three-Step Optimization Framework With Hybrid Models for a Humanoid Robot’s Jump Motion

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IEEE Transactions on Automation Science and engineering 2025年 22卷 14120-14132页

作者： Qi, Haoxiang Yu, Zhangguo Chen, Xuechao Li, Qingqing Liu, Yaliang Yi, Chuanku Dong, Chencheng Meng, Fei Huang, Qiang Beijing Institute of Technology Intelligent Robotics Institute School of Mechatronical Engineering Beijing100081 China International Joint Research Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing100081 China National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing100081 China Qiyuan Laboratory Beijing100029 China

High dynamic jump motions are challenging tasks for humanoid robots to achieve environment adaptation and obstacle crossing. The trajectory optimization is a practical method to achieve high-dynamic and explosive jumping. This paper proposes a 3-step trajectory optimization framework for generating a jump motion for a humanoid robot. To improve iteration speed and achieve ideal performance, the framework comprises three sub-optimizations. The first optimization incorporates momentum, inertia, and center of pressure (CoP), treating the robot as a static reaction momentum pendulum (SRMP) model to generate corresponding trajectories. The second optimization maps these trajectories to joint space using effective Quadratic Programming (QP) solvers. Finally, the third optimization generates whole-body joint trajectories utilizing trajectories generated by previous parts. With the combined consideration of momentum and inertia, the robot achieves agile forward jump motions. A simulation and experiments of forward jump with a distance of 1.0 m and 0.5 m height are presented in this paper, validating the applicability of the proposed framework. © 2004-2012 IEEE.

关键词： Anthropomorphic robots

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OFDM-structure based waveform designs for integrated sensing and communication

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Science China(Information Sciences) 2025年第5期68卷 267-284页

作者： Jiaqi LIU Ping YANG Ke JIANG Jiarong ZHAO Wei XIANG Jianping WEI Ruixiang DUAN Saviour ZAMMIT Tony Q.S.QUEK National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China School of Computing Engineering and Mathematical Sciences La Trobe University Meituan Academy of Robotics Department of Communications and Computer Engineering University of Malta Information Systems Technology and Design Pillar Singapore University of Technology and Design

The future sixth-generation(6G) paradigm aims to seamlessly integrate communication and environmental sensing capabilities into a single radio signal, promising improved efficiency and cost-effectiveness through simultaneous data communications and environmental perception. At the core of this evolution, orthogonal frequency division multiplexing(OFDM) and its advanced waveforms emerge as pivotal for integrated sensing and communications(ISAC). This study introduces a concise and unified ISAC waveform design framework based on orthogonal multicarriers. This framework supports versatile applications of OFDM and its derivative waveforms within a generalized ISAC system, marking a significant leap in integrating communication and sensing capabilities. A distinguishing feature of this framework is its adaptability,allowing users to intelligently select modulation strategies based on their specific environmental needs. This adaptability optimizes performance across diverse scenarios. Central to our innovations is the proposal of discrete Fourier transformspread OFDM with index modulation(DFT-S-OFDM-IM). This framework is paired with newly proposed signal processing methods for single-input single-output and multiple-input multiple-output(MIMO) systems. Extensive evaluations highlight DFT-S-OFDM-IM's superiority, including dramatically reduced peak-to-average power ratios(PAPRs), competitive communication performance, and exceptional sensing capabilities, striking an elegant balance between communication capacity and environmental sensing precision.

关键词： DFT-S-OFDM-IM index modulation integrated sensing and communication OFDM

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Adaptive Robust Control Integrated With Gaussian Processes for Quadrotors: Enhanced Accuracy, Fault Tolerance and Anti-Disturbance

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3235-3248页

作者： Liang, Weisheng Amer, Abdelhakim Mehndiratta, Mohit Chen, Zheng Yao, Bin Kayacan, Erdal Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310027 China Aarhus University Artificial Intelligence in Robotics Laboratory Department of Electrical and Computer Engineering Aarhus8000 Denmark GIM Robotics Espoo02650 Finland Zhejiang University Ocean College Ocean Research Center of Zhoushan Zhoushan316021 China Purdue University School of Mechanical Engineering West Lafayette47907 United States Department of Electrical Engineering and Information Technology Paderborn33098 Germany

With increasingly challenging applications for quadrotors, higher requirements are emerging for tracking accuracy and safety. While high accuracy is a prerequisite for complex tasks, safety is ensured through tolerance to actuator faults and resistance to external disturbances. In this article, adaptive robust control (ARC) integrated with Gaussian processes (GPs), i.e., ARC-GP, is proposed to achieve enhanced accuracy, fault tolerance, and anti-disturbance. These three requirements are interrelated and affected by uncertainties. The primary idea of this article is to categorize uncertainties into parametric and nonparametric types, which are then addressed through parameter adaptation and GP, respectively. First, a detailed dynamic model is established, including actuator models that reflect different types of faults corresponding to changes in different physical parameters. Then, parameter adaptation is designed, with direct and indirect methods adopted for different parameters. In particular, the actuator parameters are effectively estimated to achieve targeted fault compensation. Regarding GP for nonparametric uncertainties, its model parameters are also updated via parameter adaptation. The GP thereby also learns parameter estimation errors along with external disturbances. Accordingly, ARC controllers are designed, for which robust feedback terms are constructed to further mitigate uncertainties on the basis of the covariances predicted by GP. The experiments demonstrate that the proposed ARC-GP can actively tolerate various types of actuator faults and better resist wind disturbances. © 2013 IEEE.

关键词： Robust control

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