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IEEE International Conference on Robotics and Biomimetics

作者： Jiaju Tan Xin Zhao Xuemei Guo Guoli Wang School of Mathematics and Computational Science Wuyi University Jiangmen China Tianjin Key Laboratory of Intelligent Robotic (tjKLIR) Institute of Robotics and Automatic Information System (IRAIS) Nankai University Tianjin China Key Laboratory of Machine Intelligence and Advanced Computing Ministry of Education School of Data and Computer Science Sun Yat-sen University Guangzhou China

ISBN: (纸本)9781665405362

Device-Free Localization (DFL) realized by the Radio Frequency (RF) signal sensing, is an emerging technology to obtain the target’s position without needing the target carrying any electronic devices or tags. Due to its through-wall detectability and privacy protection, the RF-based DFL is becoming a promising research topic in the Location-based Services (LBS) applications based on Internet of Things (IoT). Among the RF-based DFL approaches, Radio Tomographic Imaging (RTI) is a low-cost and novel computational imaging method to reconstruct the target-induced shadowing effect in the RF monitored area and then estimate the target’s position. However, the multipath interference in the RF sensing network often induces the reconstruction degradation in the RTI system and leads to the position misestimation in DFL applications. Addressing this problem, considering that the target’s shadowing may occupy a small spatial range and then express some spatial structure, this aricle focuses on the spatial correlation of the target’s shadowing. Then an RTI reconstruction methods based on the Block Sparse Bayesian Learning is proposed to explore the spatial correlation in the sparse target’s shadowing. Moreover, the actual localization experiments are conducted to validate the spatial correlation in shadowing is an important property to improve the RTI reconstruction performance and DFL accuracy.

关键词： Performance evaluation Location awareness Radio frequency Correlation Robot sensing systems Bayes methods Sensors

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In-Situ Biaxial Cyclic Loading Behavior of Articular Cartilage and its Microstructure Analysis

SSRN

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SSRN 2022年

作者： Gao, Lilan Feng, Luming Tan, Yansong Liu, Gang Li, Ruixin Gao, Hong Zhang, Chunqiu Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China Tianjin Stomatological Hospital Tianjin300041 China School of Chemical Engineering and Technology Tianjin University Tianjin300350 China

Altered cyclic loading may change the mechanical properties, further inducing damage to articular cartilage. In this study, we studied the biaxial cyclic loading behavior of knee articular cartilage and analyzed the changes of microstructure at fibril level. Firstly, the in-plane biaxial cyclic behaviors of cartilage were investigated with an emphasis on the effects of loading paths to account for complicated loading states in daily activities. The results show that the strain evolution in X-direction is obviously affected by the constraints in Y-direction (orthogonal direction). The loading path has a great influence on the biaxial mean strain, while due to no constraint and the largest stress constraint in Y direction, proportional loading path and uniaxial loading path show the highest and lowest mean strain in X-direction, respectively. Subsequently, the effects of stress amplitude and stress peak holding time on mean strain were probed under square path. It was found that the mean strain of cartilage increases with the increase of stress amplitude or peak stress holding time. In addition, to reveal the inherent deformation mechanism, the collagen fibrils networks before and after biaxial cyclic loading were analyzed. The rearrangement of collagen fibrils networks is related to the stress state of cartilage. Larger stress leads to severer fiber damage in cartilage. © 2022, The Authors. All rights reserved.

关键词： Cartilage

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Dynamic analysis of a mobile parallel manipulator with imperfect revolute joints

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Robotica 2025年

作者： Yang, Yuwei Lv, Xingchang Li, Zhaotong Yin, Jiapeng Wang, Haoyu Li, Shuo Wang, Jutao Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China

Due to the effects of tolerance, design, and manufacturing deviations, there are clearances in the revolute joints of mechanical arms. These clearances can easily lead to system impacts and vibrations, resulting in a decrease in dynamic performance and affecting the trajectory tracking accuracy of the end effector. The existing dynamic models of mechanisms with clearance in revolute joints lack comprehensiveness, universality, and systematicity, and have not addressed the impact of joint reaction forces within clearance revolute joints on the system. The impact collision problem of the revolute joints with clearance was systematically, accurately, and comprehensively modeled and simulated in this study based on multibody dynamics theory. Based on Hertz's elastic theory, the LuGre friction model, and joint reaction forces, this paper constructs constraint and mechanical models of revolute joints with clearance based on the theory of multibody dynamics. To facilitate multibody dynamics analysis, the collision impact direction matrix is proposed and used for the first time to transform the mechanical model of revolute joints with clearance into external forces. The dynamic models of mobile parallel and double serial manipulators are then constructed. Through numerical simulations on different clearance amounts, tracking trajectories, and load parameters, the impact of revolute joint clearances on system dynamic performance is analyzed. The engineering significance of this research in dynamic analysis of mobile parallel manipulators under imperfect revolute joint conditions is also discussed. © The Author(s), 2025.

关键词： Vibration analysis

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On Modeling of Extruded Thin-Walled Multi-Cell Structures Incorporating Anisotropy Yielding, Strain Hardening and Damage Failure

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Thin-Walled Structures 2025年

作者： Ruyang Yao Bei Zhang Qiang Niu Qing Li Guangyong Sun State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha 410082 China Zhejiang Key Laboratory of Intelligent Vehicle Comprehensive Safety Geely Automobile Research Institute (Ningbo) Co. Ltd. Ningbo 315336 China School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney Sydney NSW 2006 Australia

Thin-walled multi-cell structures (TWMCS) have been extensively utilized in a range of transportation facilities, including automobiles, railways, aircraft, and marine vessels, due to their exceptional lightweight and energy absorption capabilities. However, current numerical models often oversimplify the material behaviors, significantly limiting their reliable applications in engineering practice. This study aims at developing a systematic modeling framework to address this issue, through simulating the extruded AA6063-T6 TWMCS against axial crushing process. Comprehensive experimental characterization of the base material AA6063-T6 was conducted first to investigate its yielding, strain hardening, and damage fracture behaviors under complex stress states. Constitutive models for the base material were established by incorporating the Hill 90 anisotropic yield, Voce strain hardening, and GISSMO damage failure models. The material parameters of these models were precisely calibrated through an in-house inverse identification approach. Based on this, a reliable numerical model was then developed to achieve good correlation with the experimental results. The influence of constitutive models on numerical results at a structural-scale was thoroughly investigated, highlighting the importance of understanding the intrinsic mechanical properties of materials and making rational constitutive models in engineering design. Finally, this study provides perspectives for future research to further enhance the safety and lightweight performance of protective structures.

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CIR-Net: Cross-modality Interaction and Refinement for RGB-D Salient Object Detection

arXiv

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arXiv 2022年

作者： Cong, Runmin Lin, Qinwei Zhang, Chen Li, Chongyi Cao, Xiaochun Huang, Qingming Zhao, Yao Institute of Information Science Beijing Jiaotong University Beijing100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China School of Computer Science and Engineering Nanyang Technological University Singapore School of Cyber Science and Technology Shenzhen Campus Sun Yat-sen University 518107 China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing101408 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing100190 China Peng Cheng Laboratory Shenzhen518055 China

Focusing on the issue of how to effectively capture and utilize cross-modality information in RGB-D salient object detection (SOD) task, we present a convolutional neural network (CNN) model, named CIR-Net, based on the novel cross-modality interaction and refinement. For the cross-modality interaction, 1) a progressive attention guided integration unit is proposed to sufficiently integrate RGB-D feature representations in the encoder stage, and 2) a convergence aggregation structure is proposed, which flows the RGB and depth decoding features into the corresponding RGB-D decoding streams via an importance gated fusion unit in the decoder stage. For the cross-modality refinement, we insert a refinement middleware structure between the encoder and the decoder, in which the RGB, depth, and RGB-D encoder features are further refined by successively using a self-modality attention refinement unit and a cross-modality weighting refinement unit. At last, with the gradually refined features, we predict the saliency map in the decoder stage. Extensive experiments on six popular RGB-D SOD benchmarks demonstrate that our network outperforms the state-of-the-art saliency detectors both qualitatively and quantitatively. The code and results can be found from the link of https://***. io/proj_***. © 2022, CC BY-NC-SA.

关键词： Object detection

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Implementation of Hodgkin-Huxley Spiking Neuron Model Using FPGA 19

Implementation of Hodgkin-Huxley Spiking Neuron Model Using ...

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19th IEEE International Conference on Communication Technology, ICCT 2019

作者： Yi, Zexuan Fu, Wenlong Cao, Lihong Neuroscience and Intelligent Media Institute Communication University of China Beijing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China

ISBN: (纸本)9781728105352

For the study of new computer architecture inspired by brain, implementing neuron function on hardware has become an emerging research direction. To study the feasibility of biological neuron implementation and acceleration characteristics on the hardware platform, the basic Hodgkin-Huxley (HH) neuron model and a small scale of synapse connection model is implemented on Xilinx Zynq7 Zedboard FPGA, high-level-synthesis method is used to reduce the burden of hardware design. The Hodgkin-Huxley model simulation result of FPGA are validated through high level software simulation tool in Brian2, furthermore, resource utilization and calculation time cost are provided in this paper, finally, a pipeline design of HH neuron model is used to accelerate calculations and reduce resource utilization, the result proves that this design is suitable for HH model simulation. © 2019 IEEE.

关键词： Neurons

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Training-free image style alignment for self-adapting domain shift on handheld ultrasound devices

arXiv

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arXiv 2024年

作者： Zeng, Hongye Zou, Ke Chen, Zhihao Gao, Yuchong Chen, Hongbo Zhang, Haibin Zhou, Kang Wang, Meng Goh, Rick Siow Mong Liu, Yong Jiang, Chang Zheng, Rui Fu, Huazhu School of Information Science and Technology ShanghaiTech University Shanghai China Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China University of Chinese Academy of Sciences Beijing China National Key Laboratory of Fundamental Science on Synthetic Vision College of Computer Science Sichuan University Chengdu China College of Intelligence and Computing Tianjin University Tianjin China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Beth Israel Deaconess Medical Center Harvard Medical School Boston United States Institute of High Performance Computing Agency for Science Technology and Research Singapore Singapore Department of Orthopedics Zhongshan Hospital Fudan University Shanghai China Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai China

Handheld ultrasound devices face usage limitations due to user inexperience and cannot benefit from supervised deep learning without extensive expert annotations. Moreover, the models trained on standard ultrasound device data are constrained by training data distribution and perform poorly when directly applied to handheld device data. In this study, we propose the Training-free Image Style Alignment (TISA) framework to align the style of handheld device data to those of standard devices. The proposed TISA can directly infer handheld device images without extra training and is suited for clinical applications. We show that TISA performs better and more stably in medical detection and segmentation tasks for handheld device data. We further validate TISA as the clinical model for automatic measurements of spinal curvature and carotid intima-media thickness. The automatic measurements agree well with manual measurements made by human experts and the measurement errors remain within clinically acceptable ranges. We demonstrate the potential for TISA to facilitate automatic diagnosis on handheld ultrasound devices and expedite their eventual widespread use. © 2024, CC BY-NC-SA.

关键词： Deep learning

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Weld image dust removal algorithm based on fusion of bright channel and weighted guide dark channel

UPB Scientific Bulletin, Series C: Electrical Engineering an...

引用

UPB Scientific Bulletin, Series C: Electrical Engineering and Computer Science 2020年第4期82卷 69-80页

作者： Zheng, Qingchun Lu, Kaijie Ma, Wenpeng Zhang, Zhidong Zhu, Peihao Liu, Jingna Hu, Yahui Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China Tianjin300384 China

The dust removal technology of weld image is helpful to promote the development of weld target detection and tracking control. Aiming at the problem that the image restoration algorithm has halo phenomenon in depth discontinuity and easy to cause color distortion, this paper proposes a single image restoration algorithm based on fusion of bright channel and weighted guided dark channel for dedusting of weld image. Firstly, the bright channel hypothesis is derived according to dark channel priori (DCP), and the bright channel obtained by the adaptive method will fuse with the dark channel image to construct the fusion channel. Then, the weighted guided filter is used to optimize the rough transmittance. Finally, the restored image of the weld is recovered according to the atmospheric scattering model and the restored atmospheric light. Simulation experiments and image quality analysis show that the proposed algorithm can recover the details of the weld image and suppress the halo phenomenon. The image segmentation networks are used to further verify that our algorithm can improve the accuracy and integrity of weld segmentation. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Image segmentation

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Unveiling High-Pressure Behavior of Sc3AlC MAX Phase: A Comprehensive Theoretical Study on Structural, Mechanical, Dislocation, and Electronic Properties

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Metals 2025年第5期15卷 492-492页

作者： Junping Xi Zhipeng Wang Linkun Zhang Li Ma Pingying Tang Department of Mechanical and Automotive Engineering Science and Technology College of Hubei University of Arts and Science Xiangyang 441025 China State Key Laboratory of Advanced Design and Manufacturing Technology for Vehicle Hunan University Changsha 410082 China State Key Laboratory for Powder Metallurgy Central South University Changsha 410083 China Guangxi Key Laboratory of Functional Information Materials and Intelligent Information Processing Nanning Normal University Nanning 530001 China

The structural, mechanical, dislocation, and electronic properties of the Sc3AlC MAX phase under applied pressure are investigated in detail using first-principles calculations. key parameters, including lattice parameter ratios, elastic constants, Young’s modulus, bulk modulus, shear modulus, brittle-to-ductile behavior, Poisson’s ratio, anisotropy, Cauchy pressure, yield strength, Vickers hardness, and energy factors, are systematically analyzed as a function of applied pressure. The results demonstrate that the Sc3AlC MAX phase exhibits remarkable mechanical stability within the pressure range of 0 to 60 GPa. Notably, applied pressure markedly improves its mechanical properties, such as resistance to elastic, bulk, and shear deformations. The B/G ratio suggests a tendency toward ductile behavior with increasing pressure, and the negative Cauchy pressure indicates the directional characteristics of interatomic bonding in nature. Vickers hardness and yield strength increase under pressures of 0 to 10 GPa and then decrease sharply above 50 GPa. High pressure suppresses dislocation nucleation due to the increased energy factors, along with twinning deformation. Furthermore, electronic structure analysis confirms that high pressure enhances the interatomic bonding in the Sc3AlC MAX phase, while the enhancement effect is not substantial. This study offers critical insights for designing MAX phase materials for extreme environments, advancing applications in aerospace and electronics fields.

关键词： MAX phase first-principles calculations mechanical properties energy factor high pressure

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A Memristor Based Chaotic Oscillator for Weak Signal Detection and Its Circuitry Realization

Research Square

引用

Research Square 2021年

作者： Dong, Kaifeng Xu, Kun Zhou, Youyou Zuo, Chao Wang, Leimin Zhang, Chuanke Jin, Fang Song, Junlei Mo, Wenqin Hui, Yajuan School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Wuhan Second Ship Design and Research Institute Wuhan430064 China

A new type of weak signal detection system that combines the memristor and Van der pol-Duffing chaotic system has been proposed in this paper, and the dynamic characteristics of the system are studied. It is observed that the system can change from a chaotic state to a periodic state under different driving force amplitudes. Moreover, as compared with several classical chaotic oscillators, the numerical simulation results show that the system has stronger anti-noise performance with the detectable signal-to-noise ratio reaches -163dB, and has a wider detection range. Its detection accuracy is up to 1 × 10−9. More importantly, this paper provides the circuit implementation scheme of the system, and the weak signal can be detected with our designed circuit. This may offer a possible way for weak signal detection system with good performance in anti-noise performance, detection range and accuracy. © 2021, CC BY.

关键词： Memristors

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