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SSRN 2023年

作者： Zhang, Jiantao Cong, Xingang Yu, Xiangfu Luo, Yi Li, Yanlong School of Mechatronic Engineering and Automation Shanghai University Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai China

With the development of smart wearable technology, microelectronics and other technologies, there is an increasing demand for tactile detection sensors and self-powered sensors in more and more fields. This paper focuses on the study of piezoelectric transducers based on the piezoelectric effect that can be used for both vibration energy harvesting and soft tissue hardness detection. In order to harvest the vibration energy effectively, a four-beam piezoelectric transducer for energy harvesting is developed. The electromechanical coupling theoretical model of the harvester is established based on elastic mechanics and piezoelectric theory. The influence of design parameters on the output performance of energy harvesting is simulated and analyzed. In order to realize the function of hardness detection, a four-beam piezoelectric transducer for tissue hardness detection is designed. The equivalent circuit model for the transducer is established by using the equivalent circuit method. The contact between the hardness detection sensor and the tissue is analyzed. The finite element analysis method is used to simulate the hardness detection tactile sensor. The feasibility of the hardness measurement scheme is verified by harmonic response analysis. The simulation calibration curve of the modal frequency of the transducer and the elastic modulus of the measured object is fitted through the analysis results of the contact materials with different hardness. The four-beam piezoelectric transducer prototypes for energy harvesting and tissue hardness detection were fabricated. The experimental platforms for vibration energy harvesting and soft tissue hardness detection were developed, and different experiments were carried out. The feasibility of the energy harvester and the hardness detection tactile sensor design and the validity of the theoretical model were verified through experiments. © 2023, The Authors. All rights reserved.

关键词： Hardness

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Development of a Bedside Rehabilitation Robot for Stroke Survivors

Development of a Bedside Rehabilitation Robot for Stroke Sur...

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2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Lu, Xiaowei Liu, Quanquan Duan, Lihong Dong, Jiaxiang Zhang, Zhi Liu, Zhen Zhang, Xin Zhang, Xiaohua Wang, Chunbao Guo, Jing Wei, Jianjun Long, Jianjun Wang, Yulong Li, Peng Zhao, Xuezhi Wu, Zhengzhi The First Affiliated Hospital of Shenzhen University Department of Neurology Shenzhen China Guangdong University of Technology School of Automation Guangzhou China Guangdong Mk Smart Robotics CO. Ltd Zhuhai China South China University of Technology School of Mechanical and Automotive Engineering Guangzhou China Guangxi University of Science and Technology School of Mechanical and Automotive Engineering Liuzhou China Guilin University of Electronic Technology School of Mechanical and Electrical Engineering Guilin China Shenzhen Dapeng New District Nan'Ao People Hospital Department of Rehabilitation Shenzhen China School of Mechanical and Electrical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350325706

Stroke has become one of the main causes of disability and death in the elderly population. A number of stroke survivors suffers from motor dysfunction, reducing their daily quality of life. Early intervention can effectively improve rehabilitative effectiveness. Therefore, it is necessary for patients to start rehabilitation training when they are in bed. In this paper, a bedside rehabilitation robot is proposed to assist patient's lower limb rehabilitation exercise training from bedridden stage. A motor drives a double-link mechanism to achieve linear reciprocating motion for leg extension and retracting training. Two double-link mechanisms allow stroke patients to perform different training modes. A hill model of lower leg muscle was constructed to simulate the motor workload during linear reciprocating motion of patient lower limb. The preliminary experiments demonstrated the feasibility of the bedside rehabilitation robot for lower limb exercise training of stroke survivors. © 2023 IEEE.

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Adaptive Climbing Gait Design of Snake Robot Based on Extended Kalman Filter

Adaptive Climbing Gait Design of Snake Robot Based on Extend...

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2021 International Conference on Mechatronics, automation and Intelligent Control, MAIC 2021

作者： Han, Siwei W., Xiao Z.-H., Yu W., Wei School of Automation Science and Engineering South China University of Technology Guangdong Guangzhou510000 China College of Robotics Guangdong Polytechnic of Science and Technology Guangdong Zhuhai519090 China

We propose a method of climbing pipe with different diameter, which enables snake robot to divide itself into 3 parts to complete transition on the pipe according to the joints' state for now. To avoid controlling the robot from building dynamic model, a gait-based open-loop control framework is adopted. An extended kalman filter (EKF) is applied here to estimate the adaptive parameter of gait-based function for different 3 parts and corresponding joints. The adaptive parameter will help snake robot perceive the environment better and climb the pipe more steadily. © Published under licence by IOP Publishing Ltd.

关键词： Extended Kalman filters

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A Light Space Manipulator with High Load-to-Weight Ratio: System Development and Compliance Control

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Space(Science & Technology) 2021年第1期2021卷 107-118页

作者： Zhiwei Wu Yongting Chen Wenfu Xu The School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China The State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China

In order to meet the requirements of the space environment for the lightweight and load capacity of the manipulator,this paper designs a lightweight space manipulator with a weight of 9.23 kg and a load of 2 *** adopts the EtherCAT communication protocol and has the characteristics of high load-to-weight *** order to achieve constant force tracking under the condition of unknown environmental parameters,an integral adaptive admittance control method is *** control law is expressed as a third-order linear system equation,the operating environment is equivalent to a spring model,and the control error transfer function is *** control performance under the step response is further *** simulation results show that the proposed integral adaptive admittance control method has better performance than the traditional *** has no steady-state error,overcomes the problems caused by nonlinear discrete compensation,and can facilitate analysis in the frequency domain,realize parameter optimization,and improve calculation accuracy.

关键词： overcome load EtherCAT

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无人飞行器在不确定扰动下的动态目标跟踪

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engineering 2024年第4期35卷 74-85页

作者： Yanjie Chen Yangning Wu Limin Lan Hang Zhong Zhiqiang Miao Hui Zhang Yaonan Wang School of Mechanical Engineering and Automation Fuzhou UniversityFuzhou 350108China Department of Computer Science Aberystwyth UniversityAberystwyth SY233DBUK School of Robotics Hunan UniversityChangsha 410082China College of Electrical and Information Engineering Hunan UniversityChangsha 410082China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan UniversityChangsha 410082China

This study proposes an image-based visual servoing(IBVS)method based on a velocity observer for an unmanned aerial vehicle(UAV)for tracking a dynamic target in Global Positioning System(GPS)-denied *** proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target.A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is *** depth model ensures image feature accuracy and image trajectory smoothness in rotating target *** relative velocities of the UAV and the dynamic target are estimated using the proposed velocity *** to the velocity observer,translational velocity measurements are not required,and the control chatter caused by noise-containing measurements is *** integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the antidisturbance *** stability of the velocity observer and IBVS controller is analyzed using the Lyapunov *** simulations and multistage experiments are conducted to illustrate the tracking stability,anti-disturbance ability,and tracking robustness of the proposed method with a dynamic rotating target.

关键词： Unmanned aerial vehicle Visual servoing Velocity observer Target tracking

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Edge Detectors Can Make Deep Convolutional Neural Networks More Robust

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SSRN 2024年

作者： Ding, Jin Zhao, Jie-Chao Sun, Yong-Zhi Tan, Ping Wang, Jia-Wei Ma, Ji-En Fang, You-Tong School of Automation and Electrical Engineering Key Institute of Robotics of Zhejiang Province Zhejiang University of Science and Technology Hangzhou310023 China School of Electrical Engineering Zhejiang University Hangzhou310027 China

Deep convolutional neural networks (DCNN for short) are vulnerable to examples with small perturbations. Improving DCNN's robustness is of great significance to the safety-critical applications, such as autonomous driving and industry automation. Inspired by the principal way that human eyes recognize objects, i.e., largely relying on the shape features, this paper first employs the edge detectors as layer kernels and designs a binary edge feature branch (BEFB for short) to learn the binary edge features, which can be easily integrated into any popular backbone. The four edge detectors can learn the horizontal, vertical, positive diagonal, and negative diagonal edge features, respectively, and the branch is stacked by multiple Sobel layers (using edge detectors as kernels) and one threshold layer. The binary edge features learned by the branch, concatenated with the texture features learned by the backbone, are fed into the fully connected layers for classification. We integrate the proposed branch into VGG16 and ResNet34, respectively, and conduct experiments on multiple datasets. Experimental results demonstrate the BEFB is lightweight and has no side effects on training. And the accuracy of the BEFB integrated models is better than the original ones on all datasets when facing FGSM, PGD, and C&W attacks. Besides, BEFB integrated models equipped with the robustness enhancing techniques can achieve better classification accuracy compared to the original models. The work in this paper for the first time shows it is feasible to enhance the robustness of DCNNs through combining both shape-like features and texture features. © 2024, The Authors. All rights reserved.

关键词： Feature extraction

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Cervical lesion segmentation via transformer-based network

Cervical lesion segmentation via transformer-based network

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Computer Vision, Image and Deep Learning (CVIDL), International Conference on

作者： Nanyan Shen Wei Lu Huayu Gao Jing Li Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China School of Mechatronic Engineering and Automation Shanghai University Shanghai China

ISBN: (数字)9798350373820

ISBN: (纸本)9798350373837

Colposcopic diagnosis and directed biopsy is the foundation of cervical cancer screening. Automatic segmentation of cervical lesion in colposcopic images can provide great assistance and convenience. However, the existing methods based on CNNs only differentiate the abnormality from healthy tissue, which is hard to further subdivide the lesion. In this paper, a Transformer-based network called TransNet is proposed which can extract the cervical lesion and recognize the corresponding category of each lesion. Unlike the other CNN-based methods, a more powerful vision transformer is adopted as the encoder. Extensive experiments on a large clinical colposcopic image dataset show that TransNet outperforms the existing state-of-art methods and achieves great improvement.

关键词： Deep learning Image segmentation Computer vision Image recognition Biopsy Medical services Transformers

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A Multi-Class Imbalanced Learning Method Using Random Balanced Sampling for Predicting the Quality Level of Diesel Engines

A Multi-Class Imbalanced Learning Method Using Random Balanc...

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automation in Manufacturing, Transportation and Logistics (ICaMaL), International Conference on

作者： Yi-Tian Song Yan-Ning Sun Jia-Yang Zhu Li-Lan Liu Zeng-Gui Gao Jia-Hao Zhang School of Mechatronic Engineering and Automation Shanghai University Shanghai China Shanghai Key Laboratory of Intelligent Manufacturing and Robotics Shanghai University Shanghai China

ISBN: (数字)9798350378658

ISBN: (纸本)9798350378665

Numerous process items and procedures in the assembly process of a diesel engine have a direct and significant impact on its performance, and accurate and effective assembly process control is a key technical bottleneck in improving the quality consistency of batch-produced diesel engines. Accurate prediction of assembly quality can provide support for online control of assembly quality. However, due to the significant class imbalance between qualified and unqualified products of diesel engine assembly quality, the traditional imbalance learning makes it difficult to capture the small changes between classes. Therefore, an improved random balance sampling method is proposed, combined with the LightGBM classifier to create a quality prediction model. Firstly, class balancing of the training dataset is achieved by generating random weights for each class and fusing oversampling and undersampling. Then, a LightGBM-based quality prediction model is built. Finally, the effectiveness of this approach is validated using real industrial diesel engine assembly data. The comparison results demonstrate that the proposed method outperforms traditional resampling techniques. This study provides an accurate quality prediction model, laying the groundwork for the assembly quality control model of diesel engines.

关键词： Training Adaptation models Accuracy Diesel engines Process control Transportation Quality control Production Predictive models Assembly

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Point Set Registration Based on Adaptive Maximum Correntropy

Point Set Registration Based on Adaptive Maximum Correntropy

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System Simulation Technology and its Application (CCSSTA), IEEE China Conference on

作者： Yinfeng Shao Wenting Cui Liang Xu School of Electrical Engineering and Automation Tianjin University of Technology Tianjin China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798350366600

ISBN: (纸本)9798350366617

Aiming at the problem that the iterative closest point algorithm has a lot of noise in data and poor robustness to outliers, this paper proposes a point set registration algorithm based on the adaptive maximum correntropy criterion. The aim is to enhance the robustness of traditional registration methods, improve registration accuracy, and reduce registration time. Firstly, the maximum correntropy criterion is introduced to effectively identify and eliminate noise and outliers in the data. Secondly, a parameter-adaptive iterative approach is proposed to iteratively remove noise and outliers in the data, thus improving the accuracy and robustness of point set registration. Experimental results on datasets containing a large amount of noise and outliers demonstrate that the proposed algorithm effectively enhances the accuracy and robustness of point set registration.

关键词： Accuracy Adaptive systems Iterative closest point algorithm Noise Birds Robustness Systems simulation Noise measurement Iterative methods Clocks

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Highly Sensitive Flexible Resistance Strain Sensor Based on PDMS and Silver Nanowire

Highly Sensitive Flexible Resistance Strain Sensor Based on ...

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Computer, Control and robotics (ICCCR), International Conference on

作者： Weiming Sun Mei Liu Aristide Djoulde Xinyue Liu Shanghai Key Laboratory of Intelligent Manufacturing and Robotics School of Mechatronic Engineering and Automation Shanghai University Shanghai China

Flexible sensing film has a broad application prospect in the fields of medicine, wearable electronic devices, complex environment sensing, and others. In this paper, dimethylsiloxane (PDMS) was used as a flexible substrate to prepare composite conductive films by covering silver nanowires (AgNWs) with specific lines on the substrate surface. The resistance change of the sensor is mainly caused by the change in the number of contact points between AgNWs on the film surface, which has higher linearity than the traditional resistance strain gauge. The sensor is very sensitive and has a very good measuring effect on the pressure of 0-6N and the micro-bending caused by 0-1N. Common sensors made of micro-nano materials are usually affected by transverse strain. The sensor in this experiment designs a special circuit structure, which can effectively avoid the lateral effect. The sensor also has the characteristic of self-recovery, which can achieve self-recovery under a certain degree of damage. It can be used to detect small changes in the skin.

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