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Miniaturized silicon-based capacitive six-axis force/torque sensor with large range, high sensitivity, and low crosstalk

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Microsystems & Nanoengineering 2024年第6期10卷 133-149页

作者： Renjie Tan Yong Xia Xiangguang Han Linya Huang Wendi Gao Chen Jia Ping Yang Qijing Lin Shujiang Ding Chenying Wang Libo Zhao State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement TechnologiesXi’an Jiaotong University(Yantai)Research Institute for Intelligent Sensing Technology and SystemXi’an Jiaotong University710049 Xi’anChina School of Mechanical Engineering Xi’an Jiaotong UniversityXi’an 710049China School of Instrument Science and Technology Xi’an Jiaotong UniversityXi’an 710049China Electronic Materials Research Laboratory Key Laboratory of the Ministry of EducationSchool of Electronic Science and EngineeringXi’an Jiaotong University710049 Xi’anChina Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai 265503China Engineering Research Center of Energy Storage Materials and Devices of Ministry of Education National Innovation Platform(Center)for Industry-Education Integration of Energy Storage TechnologySchool of ChemistryXi’an Jiaotong UniversityXi’an 710049China

Miniaturized six-axis force/torque sensors have potential applications in robotic tactile sensing,minimally invasive surgery,and other narrow operating spaces,where currently available commercial sensors cannot meet the requirements because of their large *** this study,a silicon-based capacitive six-axis force/torque sensing chip with a small size of 9.3×9.3×0.98 mm was designed,fabricated,and tested.A sandwich decoupling structure with a symmetrical layered arrangement of S-shaped beams,comb capacitors,and parallel capacitors was employed.A decoupling theory considering eccentricity and nonlinear effects was derived to realize low axial *** proposed S-shaped beams achieved a large measurement range through stress *** results of a coupled multiphysics field finite-element simulation agreed well with those of theoretical *** test results show that the proposed sensing chip can detect six-axis force/torque separately,with all crosstalk errors less than 2.59%*** force and torque measurement ranges can reach as much as 2.5 N and 12.5 N·mm,*** sensing chip also has high sensitivities of 0.52 pF/N and 0.27 pF/(N·mm)for force and torque detection,respectively.

关键词： crosstalk shaped torque

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Diverse Gaussian Sampling for Human Motion Prediction 16th

Diverse Gaussian Sampling for Human Motion Prediction

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16th International Conference on Social robotics, ICSR + InnoBiz 2024

作者： Luo, Jiefu Wang, Jiansheng Liu, Zhenfei Cheng, Jun Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China The Chinese University of Hong Kong Hong Kong Department of Pediatric Orthopedics Shenzhen Children’s Hospital Guangdong Shenzhen518000 China

ISBN: (纸本)9789819611508

In many industrial applications, it is necessary to obtain accurate human motion prediction. The prediction of human movement based on a 3D skeleton, which forecasts future postures using the human skeletal structure, significantly aids in enabling machines to understand human behavior and react more intelligently. Additionally, by predicting human actions, potential dangers can be perceived, especially in safety-related issues, necessitating a broader range of predictions. In this paper, considering the greater diversity generated by Variational Autoencoders (VAEs), we employ VAEs for prediction. In contrast to other studies, our primary focus is on obtaining more diverse samples. Extensive experiments demonstrate that our proposed model performs well on the Human 3.6M [35] and HumanEva-I [36] datasets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Prediction models

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10-Hertz squeezed light source generation on the cesium D_(2)line using single photon modulation

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Frontiers of physics 2023年第3期18卷 167-174页

作者： Guan-Hua Zuo Yu-Chi Zhang Gang Li Peng-Fei Zhang Peng-Fei Yang Yan-Qiang Guo Shi-Yao Zhu Tian-Cai Zhang State Key Laboratory of Quantum Optics and Quantum Optics Devices Collaborative Innovation Center of Extreme OpticsInstitute of Opto-ElectronicsShanxi UniversityTaiyuan 030006China College of Physics and Electronic Engineering Shanxi UniversityTaiyuan 030006China Department of Physics Zhejiang UniversityHangzhou 310027China Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi ProvinceCollege of Physics and OptoelectronicsTaiyuan University of TechnologyTaiyuan 030024China

Generation of squeezed light source is a promising technique to overcome the standard quantum limit in precision ***,we demonstrate an experimental generation of quadrature squeezing resonating on the cesium D_(2)line down to 10 Hz for the first *** maximum squeezing in audio frequency band is 5.57 ***,we have presented a singlephoton modulation locking to control the squeezing angle,while effectively suppressing the influence of laser noise on low-frequency *** whole system operates steadily for *** generated low-frequency squeezed light source can be applied in quantum metrology,light–matter interaction investigation and quantum memory in the audio frequency band and even below.

关键词： squeezed state optical parametric amplifier low-frequency squeezing

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Flexible liquid metal electromagnetic shielding materials

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Science China(Technological Sciences) 2023年第10期66卷 2757-2774页

作者： BAI YunLong ZHANG Jie ZHANG MingKuan RAO Wei Key Laboratory of Cryogenics Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China Beijing Key Lab of CryoBiomedical Engineering and Key Lab of Cryogenics Technical Institute of Physics and ChemistryChinese Academy of SciencesBeijing 100190China School of Engineering Science University of Chinese Academy of SciencesBeijing 100039China School of Future Technology University of Chinese Academy of SciencesBeijing 100049China Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical EngineeringTianjin University of TechnologyTianjin 300384China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of TechnologyTianjin 300384China

The demand for flexible shielding has been rapidly growing in recent *** materials using solid metals,carbon materials,or MXenes as shielding units usually have difficulty in combining high shielding and flexibility(stretching and bending characteristics),and thus they gradually fail to meet the shielding needs of flexible ***,shielding materials with both flexibility and high conductivity are urgent to fill this ***-based room temperature liquid metal(LM)is an emerging functional material with a low melting point,low viscosity,low modulus,and easy ***,due to wettability and compatibility issues,it is difficult to apply bulk LMs directly in the field of electromagnetic shielding(EMS).The article reviews the fabrication methods,performance,and applications of LMs EMS materials from three perspectives:Macroscopic LMs,micro/nano-LMs,and LM-based *** gallium-based liquid EMS materials demonstrate the characteristics of high shielding performance with stretchability and a wide shielding *** this review,different types of gallium-based LM materials are described from macroscopic to microscopic,from liquid to semi-solid,from high density to low density,from room temperature to ultra-low temperature,and from monolayer structure to multilayer *** prospect of LM materials as amorphous high-performance EMS materials is demonstrated in various applications,such as mobile communication,astronomical observation,radar,and medical detection,showing tremendous potential in the EMS field.

关键词： liquid metal electromagnetic shielding flexibility

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Attention-enhanced BLSTM Network for Liquid Volume Estimation based on Tactile Sensing

Attention-enhanced BLSTM Network for Liquid Volume Estimatio...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Su, Yuanzhe Wang, Jingnan Huang, Binhua Li, Xiaoyu Liu, Yiwen Liu, Chengliang Zhou, Zhenning Yi, Zhengkun Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch Shenzhen518055 China

ISBN: (纸本)9798350327182

The task of liquid volume estimation based on tactile sensing is challenging. Previous researches mainly focused on the classification of different contents in the container, rather than achieving accurate estimation of a certain property of the contents in container, such as volume or viscosity. In addition, few studies are conducted for the regression task with advanced tactile sensors, but the performance is unsatisfactory. We propose a new deep-learning algorithm for processing the tactile signals collected from the photoresistors in the task of liquid content estimation. The proposed algorithm doesn't need hand-crafted features. In addition, we use attention after BLSTM, so that more important features can be selected to achieve better performance for liquid volume estimation. We utilize a bi-directional Long Short-Term Memory (BLSTM) architecture, which allows for the incorporation of information from both preceding and subsequent time, thereby providing a more comprehensive and informative feature set for learning. Additionally, we employ an attention mechanism following the BLSTM, allowing for the selection of more critical features and improved performance in liquid volume estimation. To prove the effectiveness of our method, we conduct experiments utilizing tactile sensors on a physical robot, achieving superior performance in liquid volume estimation. © 2023 IEEE.

关键词： Containers

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A Self-supervised Contrastive Learning Method for Grasp Outcomes Prediction

A Self-supervised Contrastive Learning Method for Grasp Outc...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Liu, Chengliang Huang, Binhua Liu, Yiwen Su, Yuanzhe Mai, Ke Zhang, Yupo Yi, Zhengkun Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch Shenzhen518055 China

ISBN: (纸本)9798350327182

In this paper, we probe the proficiency of contrastive learning techniques in forecast grasp outcomes, without supervision. Employing a dataset that's open to the public, we establish the effectiveness of contrastive learning techniques in accurately predicting grasp outcomes. More precisely, an impressive accuracy of 81.83% is achieved by the dynamic-dictionary-based method combined with the momentum updating technique, using data from just one tactile sensor, surpassing other unsupervised techniques. Our findings underscore the promise held by contrastive learning techniques in the domain of robotic grasping, while emphasizing the critical role played by precise grasp prediction in securing stable grasps. © 2023 IEEE.

关键词： Forecasting

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CDP-GAN:Near-Infrared and Visible Image Fusion Via Color Distribution Preserved GAN

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1698-1701页

作者： Jun Chen Kangle Wu Yang Yu Linbo Luo the School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsEngineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationChina University of GeosciencesWuhan 430074China the Shanghai Institute of Technical Physics Key Laboratory of Infrared System Detecting and Imaging TechnologyChinese Academy of SciencesShanghai 200083China the School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China

Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the ***。

关键词： details dealing preserving

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Rehabilitation Training of Spinal Cord Injured Individuals by a Self-Balancing Exoskeleton Robot

Rehabilitation Training of Spinal Cord Injured Individuals b...

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Li, Wentao Li, Jinke He, Yong Tian, Dingkui Li, Feng Sun, Jianquan Wu, Xinyu Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China Siat Cuhk Joint Laboratory of Robotics and Intelligent Systems China University of Chinese Academy of Sciences Shenzhen College of Advanced Technology Shenzhen518055 China China Construction Third Bureau First Engineering Mep Co. Ltd. Shenzhen518109 China

ISBN: (纸本)9798350327182

Physical therapy plays an important role in the rehabilitation for spinal cord injured individuals, and exoskeleton can assist with this process. In this paper, a self-balancing exoskeleton robot is introduced, which can provide assist not only in gait training, but also in balance training. In addition, it allows individuals walk with it without other assistive devices. This exoskeleton is designed to have a high degree of compatibility with humans. The structure and control system of the exoskeleton is introduced and the forward and inverse kinematic are solved, which enables the robot to perform various rehabilitation training actions as required. Experiments with a male subject have shown that this exoskeleton achieves the predicted results in gait training and balance training. © 2023 IEEE.

关键词： Inverse kinematics

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Variation of sEMG with Muscle Fatigue for Lower Limb Stroke Patient During Walking

Variation of sEMG with Muscle Fatigue for Lower Limb Stroke ...

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2024 IEEE International Conference on robotics and Biomimetics, ROBIO 2024

作者： Shang, Wenze Huang, Ruisen Liao, Wei-Hsin Wu, Xinyu Gao, Fei Southern University of Science and Technology Shenzhen518005 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen518055 China The Chinese University of Hong Kong Department of Mechanical and Automation Engineering Hong Kong999077 Hong Kong

ISBN: (纸本)9781665481090

SEMG signal is widely used and explored in control strategies of powered assistive human-robot interaction systems due to its non-invasive nature and ability to estimate motion intention well. However, prolonged use of the sEMG-based systems leads to muscle fatigue, contributing to unstable sEMG signals and regarding the performance of sEMG-based control strategies. In this study, three subjects, including two healthy subjects and one stroke subject, participated in our experiment, and the time domain, frequency domain, and complex features extracted from their sEMG signals were utilized to evaluate muscle fatigue. The results indicate that sEMG from the stroke side of the stroke subject contains more non-linear and chaotic parts, and the statistical differences between different trials are more significant, indicating that stroke has a more significant impact on the stroke side of the stroke subject. This study suggests that RMS in the stroke side of stroke subjects is less than that in others, whereas FuzzyEn in the stroke side of stroke subjects is greater than that in others, indicating that stroke leads to different motion patterns and more susceptibility to muscle fatigue. © 2024 IEEE.

关键词： Human robot interaction

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GelPixel: A Single-Pixel-Based Tactile Sensor

GelPixel: A Single-Pixel-Based Tactile Sensor

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2023 IEEE International Conference on Real-Time Computing and robotics, RCAR 2023

作者： Huang, Binhua Li, Xiaoyu Sumari, Putra Ye, Chaoxiang Zhou, Zhenning Yin, Meng Yi, Zhengkun Wu, Xinyu Shenzhen Institute of Artificial Intelligence and Robotics for Society Siat Branch Shenzhen518055 China Universiti Sains Malaysia School of Computer Science 11800 Malaysia Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Shenzhen518055 China

ISBN: (纸本)9798350327182

In this paper, we present the design and development of a novel optical tactile sensor that uses a single-pixel color light-to-frequency converter (TCS3200) and spectral decoding to recognize presses at different positions. This innovative approach overcomes the limitations associated with camera-based sensors, such as increased manufacturing costs and shape restrictions, enabling potential integration as a skin-like layer over a robot's body. Our proposed direct light propagation structure demonstrates enhanced sensitivity and a broader measuring range compared to traditional reflection structures. Using Ecoflex as the elastomer, the sensor's design incorporates a three-layer structure, including an LED layer, an elastomer layer, and a color sensor layer. Experimental results demonstrate that the proposed sensor performs well in localization tasks, achieving over 95% accuracy using multi-target regression for rendering poked positions. This study demonstrates the potential of single-pixel-based tactile sensors in various applications and provides a foundation for further exploration in this area. © 2023 IEEE.

关键词： Tactile sensors

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