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IEEE International Conference on robotics and Automation (ICRA)

作者： Wenshuo Li Wenfu Xu Peisheng Huang Boyang Lin Bin Liang School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Department of Automation Tsinghua University Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

In recent years, there has been a growing demand for robotic manipulators to perform tasks in various unstructured environments and situations requiring precision and force control. However, traditional robotic arms have limitations in fully leveraging their advantages in such scenarios. To address this demand, we have designed a cable-driven serpentine manipulator (CDSM) that combines force and precision motion control. This control method allows for precise manipulation of forces and torques at the end-effector, particularly in applications like electric vehicle charging and narrow-space exploration. It also enables independent control in multiple configurations. We achieve force-position hybrid control in task space, ensuring accurate control of end-effector force while achieving precise position control in other directions. Additionally, we implement joint angle closed-loop control in joint space to reduce the impact of cable elasticity deformation and friction on joint motion accuracy. Finally, servo control is applied at the lowest motor level. This paper investigates the modeling, sensing, and control of CDSM within a unified framework of hybrid motion/force control. Through experiments and simulations, we demonstrate the high accuracy and practicality of this control method in various scenarios.

关键词： Accuracy Force Aerospace electronics Arms End effectors Sensors Task analysis

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Language-Assisted Human Part Motion Learning for Skeleton-Based Temporal Action Segmentation

arXiv

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arXiv 2024年

作者： Chen, Bowen Ji, Haoyu Wang, Zhiyong Filtjens, Benjamin Wang, Chunzhuo Ren, Weihong Vanrumste, Bart Liu, Honghai State Key Laboratory of Robotics and Systems Harbin Institute of Technology Shenzhen Shenzhen518055 China KU Leuven Leuven Belgium e-Media Research Lab KU Leuven Leuven Belgium Peng Cheng Laboratory Shenzhen518000 China

Skeleton-based Temporal Action Segmentation involves the dense action classification of variable-length skeleton sequences. Current approaches primarily apply graph-based networks to extract framewise, whole-body-level motion representations, and use one-hot encoded labels for model optimization. However, whole-body motion representations do not capture finegrained part-level motion representations and the one-hot encoded labels neglect the intrinsic semantic relationships within the language-based action definitions. To address these limitations, we propose a novel method named Language-assisted Human Part Motion Representation Learning (LPL), which contains a Disentangled Part Motion Encoder (DPE) to extract duallevel (i.e., part and whole-body) motion representations and a Language-assisted Distribution Alignment (LDA) strategy for optimizing spatial relations within representations. Specifically, after part-aware skeleton encoding via DPE, LDA generates dual-level action descriptions to construct a textual embedding space with the help of a large-scale language model. Then, LDA motivates the alignment of the embedding space between text descriptions and motions. This alignment allows LDA not only to enhance intra-class compactness but also to transfer the language-encoded semantic correlations among actions to skeleton-based motion learning. Moreover, we propose a simple yet efficient Semantic Offset Adapter to smooth the cross-domain misalignment. Our experiments indicate that LPL achieves stateof- the-art performance across various datasets (e.g., +4.4% Accuracy, +5.6% F1 on the PKU-MMD dataset). Moreover, LDA is compatible with existing methods and improves their performance (e.g., +4.8% Accuracy, +4.3% F1 on the LARa dataset) without additional inference costs. Copyright © 2024, The Authors. All rights reserved.

关键词： Musculoskeletal system

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Construction and Analysis of Deep Functional Corticomuscular Coupling Effect

Construction and Analysis of Deep Functional Corticomuscular...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Liu, Jinbiao Li, Xinhang Wang, Lijie Luo, Manli Feng, Linqing Tang, Tao Liu, Honghai Wei, Yina Research Center for Augmented Intelligence Zhejiang Lab Hangzhou311100 China Zhejiang University Zhejiang Prov. Key Lab. of Cardio-Cerebr. Vasc. Detection Technol. and Med. Effectiveness Appraisal Hangzhou310027 China Harbin Institute of Technology Key Laboratory of Robotics and Systems Shenzhen518055 China

ISBN: (纸本)9798350337020

Based on electroencephalogram (EEG) and electromyogram (EMG) signals, the function coupling between the cerebral cortex and muscles has been widely studied to evaluate the motor function and reveal various motor control and pathological mechanisms in healthy individuals or patients with movement disorders. However, the effect of the different signal sources on the functional corticomuscular coupling remains unclear. In this study, four different signal source combinations were constructed by EEG and high-density surface EMG (HD-sEMG) signals as well as their reconstructed source signals to analyze the corticomuscular coupling during isometric index finger contraction tasks at different levels of maximum voluntary contraction. A nonparametric coupling model was used to study the effect of deep source signals on changing the coherence magnitude indicators of corticomuscular coupling related to hand movements. The results showed that the reconstruction of EEG and HD-sEMG signals significantly improved the coherence peak and coherence strength under low-level force. However, as the force level increased, only the reconstructed brain source signals demonstrated a more substantial effect. In addition, the coherence peak was positively correlated with the finger force level. This study demonstrated the importance and positive impact of the reconstructed EEG and EMG signals for estimating corticomuscular coherence. © 2023 IEEE.

关键词： brain source localization decomposition Electroencephalogram functional corticomuscular coupling high-density surface electromyogram

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Iterative Control Decoupling Tuning by Feedforward Compensation for Precision Motion Stage

Iterative Control Decoupling Tuning by Feedforward Compensat...

引用

Data Driven Control and Learning systems (DDCLS)

作者： Hongyang Zhao Li Li Yang Liu Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and Information Technology Harbin Institute of Technology Harbin China State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan China

In multi-input multi-output (MIMO) ultra-precision motion control system, high-performance decoupling method is the key to reduce the interactions between different degree of freedoms (DOFs). However, the manufacturing and assembling errors will greatly affect the decoupling performance. Some non-negligible factors, such as the center of gravity (CoG) and actuator positions, cannot be accurately determined, which will deteriorate the control accuracy. To tackle this problem, an iterative control decoupling tuning method by feedforward compensation is proposed in this paper. The proposed strategy using feedback signal to tune the parameters of feedforward compensator iteratively and further compensate for the closed-loop dynamics. The simulation results show that the proposed method is more effective, including the convergence accuracy, convergence speed and the improvement of the tracking error caused by the coupling.

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Intelligent Fault Diagnosis Using Limited Data Under Different Working Conditions Based on SEflow Model and Data Augmentation 16th

Intelligent Fault Diagnosis Using Limited Data Under Differe...

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16th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2020 in conjunction with the 13th International Conference on Frontiers of Information technology, Applications and Tools, FITAT 2020

作者： Li, Sijue Peng, Gaoliang Mao, Daoyong Zhu, Zhiyu Ji, Mengyu Chen, Yuanhang State Key Laboratory of Robotics and System Harbin Institute of Technology No. 92 Xidazhi Street Harbin Heilongjiang Province150001 China China Electronics Technology Group Corporation no. 38 Research Institute Hefei Anhui Province China Department of Computer Science City University of Hong Kong Hong Kong

ISBN: (纸本)9789813364196

Accurate fault diagnosis of machine components is quite important for normal operation of equipment. Nowadays, artificial intelligent methods have been widely researched in fault diagnosis of rolling element bearings (REB). However, due to the variation of machine working conditions, the diagnosis accuracy always degrade seriously. Besides, as it is really hard to achieve large amounts of labeled health condition signals from real equipment, data deficiency is another trouble. Both issues impede the practical application of data-driven fault diagnosis. So as to solve the problems, a data augmentation method SEflow based on squeeze-and-excitation networks (SEnet) and flow-generative model is proposed. Proposed SEflow can learn the data distributions from limited data, then generate augmented signals among different machine working conditions. The experiments applied on bearing datasets and ball screw signals verify the effectiveness of proposed method on solving domain adaption and data deficiency. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Failure analysis

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Orbital angular momentum-enhanced phase estimation using non-Gaussian state with photon loss

arXiv

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arXiv 2023年

作者： Chen, Yong-Jian Gao, Jin-Wei Han, Jin-Xuan Yuan, Zhong-Hui Li, Ruo-Qi Jiang, Yong-Yuan Song, Jie School of Physics Harbin Institute of Technology Harbin150001 China School of Electronic Information Engineering China West Normal University Sichuan Nanchong637002 China Key Laboratory of Micro-Nano Optoelectronic Information System Ministry of Industry and Information Technology Harbin150001 China Key Laboratory of Micro-Optics and Photonic Technology of Heilongjiang Province Harbin Institute of Technology Harbin150001 China Collaborative Innovation Center of Extreme Optics Shanxi University Shanxi Taiyuan030006 China

This study investigates the use of orbital angular momentum (OAM) to enhance phase estimation in Mach-Zehnder interferometers (MZIs) by employing non-Gaussian states as input resources in the presence of noise. Our research demonstrates that non-Gaussian states, particularly the photon-subtraction-then-addition (PSA) state, exhibit the best sensitivity in the presence of symmetric noise. Additionally, higher-order of Bose operator of non-Gaussian states provide better sensitivity for symmetric noise. OAM can mitigate the deterioration of noise, making it possible to estimate small phase shifts θ → 0. OAM enhances the resolution and sensitivity of all input states and mitigating the deterioration caused by photon loss. Additionally, OAM enhances the resolution and sensitivity of all input states, enabling the sensitivity to approach the 1/N limit even under significant photon loss (e.g.,50% symmetric photon loss). These results hold promise for enhancing the sensitivity and robustness of quantum metrology, particularly in the presence of significant photon loss. © 2023, CC BY.

关键词： Deterioration

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Data-driven Rational Feedforward Tuning Algorithm Based on Self-adaptive Hybrid Self-learning TLBO

Data-driven Rational Feedforward Tuning Algorithm Based on S...

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Data Driven Control and Learning systems (DDCLS)

作者： Siwen Chen Yang Liu Fazhi Song Key Laboratory of Ultra-Precision Intelligent Instrumentation Ministry of Industry and InformationTechnology Harbin Institute of Technology Harbin China State Key Lab of Digital Manufacturing Equipment & Technology Huazhong University of Science and Technology wuhan China

Data-driven feedforward tuning algorithm, extensively used in ultra-precision motion stage, can significantly compensate tracking errors and optimize task adaptability. However, the rational basis based feedforward optimization usually faces non-convex optimization, numerical stability and initial value problems. The purpose of this paper is to propose a feedforward tuning algorithm based on the heuristic method self-adaptive hybrid self-learning TLBO. The algorithm can converge to the ideal feedforward parameter, so that the system can achieve high tracking accuracy, and has good numerical properties and low initial value requirements. The effectiveness and superiority of the proposed method are verified by simulation.

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Numerical Simulation of Melt Jet Breakup Under Non Solidification Conditions

SSRN

引用

SSRN 2023年

作者： Guo, Zehua Xu, Xinsheng Qiu, Fengrong Ding, Ming Heilongjiang Provincial Key Laboratory of Nuclear Power System and Equipment Harbin Engineering University Harbin150001 China Institute of Nuclear and New Energy Technology Tsinghua University Beijing100084 China

The nuclear reactor core melting accident causes the leakage of radioactive materials, resulting serious harm to the surrounding environment and the safety of the public. For modern PWR, if the core structure was melted in a severe accident, the melt generated will move downward and interact with the remaining coolant at the lower head, resulting a series of physical phenomena. In this paper, the numerical model based on the VOF to DPM method is presented to analyze physical processes of the interaction between melt jet and coolant. The influence of coolant phase change on the jet breakup length, degree of fragmentation, and particle diameter of melt debris are analyzed under different conditions. This paper analyzes the impact of the incident velocity of melt, the incident diameter, the density ratio of melt and coolant on the jet breakup length based on Saito's empirical formula, and compares the simulation results with the empirical formula. The working condition of Yutaka experiment is simulated in this paper and the diameter distribution of the broken fragments is analyzed, as well as the influence of the incident temperature, incident mass and incident velocity of the melt on the average mass diameter of the generated particles. The numerical results reach a good agreement with the experimental data. This work provides a feasible numerical scheme for the analysis of melt jet entering the lower head coolant under accident conditions. © 2023, The Authors. All rights reserved.

关键词： Coolants

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Agricultural Fire Impacts on Brown Carbon During Different Seasons in Northeast China

SSRN

引用

SSRN 2023年

作者： Cheng, Yuan Cao, Xu-Bing Liu, Jiu-Meng Yu, Qin-Qin Zhang, Qiang He, Ke-Bin State Key Laboratory of Urban Water Resource and Environment School of Environment Harbin Institute of Technology Harbin150090 China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System Science Tsinghua University Beijing100084 China State Key Joint Laboratory of Environment Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China

Brown carbon (BrC) represents not only a major component of haze pollution but also a non-negligible contributor to positive radiative forcing, making it a key species for coordinating air quality and climate policies. In China, field observations on BrC remain limited given the highly variable emission sources and meteorological conditions across different regions. Here we focused on the optical properties of BrC in a distinct but largely unexplored megacity in Northeast China, which is within a major agricultural region and experiences extremely cold winter. Agricultural fires were evident in April of 2021 and the fall of 2020, despite a toughest-ever policy on open burning. Such emissions enhanced BrC's mass absorption efficiency at 365 nm (MAE365), more efficiently by the fall fires which were inferred to have relatively high combustion efficiencies (CE). After taking CE into consideration, the relationships between MAE365 and the levoglucosan to organic carbon ratio (a measure of the significance of agricultural fire influence) roughly converged for the fire episodes of different seasons, including those identified in February and March of 2019 by a previous campaign. Agricultural fires also influenced the determination of absorption Ångström exponent (AAE), by resulting in non-linearity for BrC's absorption spectra shown on ln-ln scale. Based on three indicators developed by this study, the non-linearity was inferred to be caused by similar chromophores although the fires were characterized by various CE levels in different seasons. In addition, for the samples without significant influence of open burning, coal combustion emissions were identified as the dominant influencing factor for MAE365, whereas none solid link was found between the solution-based AAE and aerosol source. © 2023, The Authors. All rights reserved.

关键词： Light absorption

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Read Pointer Meters in complex environments based on a Human-like Alignment and Recognition Algorithm

arXiv

引用

arXiv 2023年

作者： Shu, Yan Liu, Shaohui Xu, Honglei Jiang, Feng State Key Laboratory of Communication Content Cognition People's Daily Online Beijing100733 China Computer Science and Technology Department Harbin Institute of Technology Harbin150001 China

Recently, developing an automatic reading system for analog measuring instruments has gained increased attention, as it enables the collection of numerous types of equipment. Nonetheless, two major obstacles still obstruct its deployment to real-world applications. The first issue is that they rarely take the entire pipeline's speed into account. The second is that they are incapable of dealing with some low-quality images (i.e., meter breakage, blur, and uneven scale). In this paper, we propose a human-like alignment and recognition algorithm to overcome these problems. More specifically, a spatial transformed module (STM) is proposed to obtain the front view of images in a self-autonomous way based on an improved spatial transformer network (STN). Meanwhile, a value acquisition module (VAM) is proposed to infer accurate meter values by an end-to-end trained framework. In contrast to previous research, our model aligns and recognizes meters totally implemented by learnable processing, which mimics human behaviors and thus achieves higher performance. Extensive results verify the robustness of the proposed model in terms of accuracy and efficiency. The code and the dataset is available in https://***/shuyansy/Detect-and-read-meters. © 2023, CC BY.

关键词： Image enhancement

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