检索结果-内蒙古大学图书馆

Radiative thermal switch via metamaterials made of vanadium dioxide-coated nanoparticles

学校读者我要写书评

暂无评论

arXiv 2023年

作者： He, Ming-Jian Guo, Xue Qi, Hong Lu, Lu Tan, He-Ping School of Energy Science and Engineering Harbin Institute of Technology Harbin150001 China Key Laboratory of Aerospace Thermophysics Ministry of Industry and Information Technology Harbin150001 China Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System Hubei University of Technology Wuhan430068 China

In this work, a thermal switch is proposed based on the phase-change material vanadium dioxide (VO2) within the framework of near-field radiative heat transfer (NFRHT). The radiative thermal switch consists of two metamaterials filled with core-shell nanoparticles, with the shell made of VO2. Compared to traditional VO2 slabs, the proposed switch exhibits a more than 2-times increase in the switching ratio, reaching as high as 90.29% with a 100 nm vacuum gap. The improved switching effect is attributed to the capability of the VO2 shell to couple with the core, greatly enhancing heat transfer with the insulating VO2, while blocking the motivation of the core in the metallic state of VO2. As a result, this efficiently enlarges the difference in photonic characteristics between the insulating and metallic states of the structure, thereby improving the ability to rectify the NFRHT. The proposed switch opens pathways for active control of NFRHT and holds practical significance for developing thermal photon-based logic circuits. © 2023, CC BY.

关键词： Vanadium dioxide

TDCNet: Transparent Objects Depth Completion with CNN-Transformer Dual-Branch Parallel Network

学校读者我要写书评

暂无评论

arXiv 2024年

作者： Fan, Xianghui Ye, Chao Deng, Anping Wu, Xiaotian Pan, Mengyang Yang, Hang Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun130033 China University of Chinese Academy of Sciences Beijing101408 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin Institute of Technology Harbin150001 China College of Physics Northeast Normal University Changchun130024 China

The sensing and manipulation of transparent objects present a critical challenge in industrial and laboratory robotics. Conventional sensors face challenges in obtaining the full depth of transparent objects due to the refraction and reflection of light on their surfaces and their lack of visible texture. Previous research has attempted to obtain complete depth maps of transparent objects from RGB and damaged depth maps (collected by depth sensor) using deep learning models. However, existing methods fail to fully utilize the original depth map, resulting in limited accuracy for deep completion. To solve this problem, we propose TDCNet, a novel dual-branch CNN-Transformer parallel network for transparent object depth completion. The proposed framework consists of two different branches: one extracts features from partial depth maps, while the other processes RGB-D images. Experimental results demonstrate that our model achieves state-of-the-art performance across multiple public datasets. Our code and the pre-trained model are publicly available at https://***/XianghuiFan/TDCNet. Copyright © 2024, The Authors. All rights reserved.

关键词： HTTP

Wheel-Terrain Contact Geometry Estimation using the Aside-Wheel RGB-D Sensor over Soft Terrain

学校读者我要写书评

暂无评论

Wheel-Terrain Contact Geometry Estimation using the Aside-Wh...

robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Pengxuan Zhana Chen Yao Longteng Hu Feng Xue Peichen Wang Zheng Zhu Zhenzhong Jia Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen China Department of Mechanical and Energy Engineering Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Southern University of Science and Technology (SUSTech) Shenzhen China SUSTech Guang-dong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen China Harbin of Institute of Technology (HIT) Harbin China College of Engineering University of Michigan Ann Arbor Michigan USA School of Electronics Harbin Institute of Technology Harbin China

ISBN: (数字)9798350307566

ISBN: (纸本)9798350307573

Wheeled mobile robots (WMRs) have exhibited notable competitiveness in various applications, including geo-graphic and planetary exploration. Nonetheless, when traversing on soft terrains, their wheels might encounter sinkage and slippage, leading to mission failure. Consequently, real-time estimation of contact parameters such as sinkage and slip ratio holds significant importance for rover operations. In this paper, we introduce a novel algorithm that employs only one aside-wheel RGB-D camera for the simultaneous detection of wheel sinkage and slip ratio on deformable terrains in real-time. We estimate sinkage through the depth module by processing point cloud data, and we estimate slip ratio through the color module with a sequence of image processing steps. Utilizing only one single camera reduces errors arising from sensor signal alignment and enhances detection accuracy. With a single-wheel testbed, we simulate wheel motion under different slip ratios and carry out numerous experiments to validate the effectiveness of the proposed algorithm. Our algorithm attains a detection frequency of up to 20Hz and exhibits outstanding precision. The relative sinkage error remains below 4%, while the relative slippage error is confined within 0.8%.

关键词： Accuracy Image color analysis Robot vision systems Wheels Estimation Cameras Real-time systems

Stiffness-Based Hybrid Motion/ Force Control for Cable-Driven Serpentine Manipulator*

学校读者我要写书评

暂无评论

Stiffness-Based Hybrid Motion/ Force Control for Cable-Drive...

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

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

学校读者我要写书评

暂无评论

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

Construction and Analysis of Deep Functional Corticomuscular Coupling Effect

学校读者我要写书评

暂无评论

Construction and Analysis of Deep Functional Corticomuscular...

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

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

学校读者我要写书评

暂无评论

Intelligent Fault Diagnosis Using Limited Data Under Differe...

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

Iterative Control Decoupling Tuning by Feedforward Compensation for Precision Motion Stage

学校读者我要写书评

暂无评论

Iterative Control Decoupling Tuning by Feedforward Compensat...

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.

关键词：

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

学校读者我要写书评

暂无评论

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