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

作者： Guo, Siyu Wang, Maolin Wang, Huaping Zhong, Shihao Qiu, Yukang Hou, Yaozhen Shi, Qing Fukuda, Toshio Beijing Institute of Technology Intelligent Robotics Institute School of Mechatronical Engineering Beijing100081 China Ministry of Education Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology School of Medical Technology Beijing100081 China Beijing Institute of Technology Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China

ISBN: (纸本)9798350327182

Magnetic helical microrobots have great potential in biomedical applications. However, improving their motion performance in the complex and variable in vivo fluid environment remains challenging. Previous researches mainly focus on optimizing the geometric parameter, the evolutionary structure design, and chemical modifications of the robots, with limited attention given to the impact of physical surface modifications on propulsion performance. To address this issue, we design the helical microrobot with different surface physical modifications, including dimpled and raised surfaces, to evaluate their effects on swimming performance. With ANSYS Fluent, we simulated their swimming process in water and found that microrobots with physically modified surfaces experience less resistance and exhibit a larger step-out frequency while swimming. Moreover, our findings suggest that helical microrobots with dimpled surfaces demonstrate superior swimming performance due to their larger gas-liquid interface area compared to those with raised surfaces. © 2023 IEEE.

关键词： Chemical modification

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Transformer-Based Fusion of RGB and Depth Images for Terrain Recognition

Transformer-Based Fusion of RGB and Depth Images for Terrain...

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International Conference on Biomimetic Intelligence and robotics & Medical robotics Forum, ICBIR+MRF 2024

作者： Chen, Hui Chen, Chunjie Wang, Zhuo Yang, Fangliang Pan, Heng Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen518055 China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055 China

This research aims to explore key issues in the field of walking robots and exoskeletons. By using a depth camera to record human walking data in different terrains and employing RGB and depth information for image classification, our approach utilizes both early fusion and late fusion methods to explore their impact on terrain classification. This approach achieved fast and accurate performance in recognizing terrain. We captured data for walking upstairs, downstairs, upward ramps, downward ramps and level ground and used the vision transformer for data fusion. This work compares the performance of unimodal RGB model, unimodal deep model, Pre-Fusion model and Post-Fusion model in terms of accuracy, recall and processing frequency, with accuracies of 0.954, 0.934, 0.976, and 0.976, respectively. The results show that the Post-Fusion model slightly outperforms the Pre-Fusion model in terms of accuracy and recall with more reliable classification performance. To understand the attention mechanism better, we've been visualizing the weights of the model, observing how different attention heads may capture different features of the data from various dimensional perspectives. The visualization helps in interpreting the model's focus and how it distinguishes between features of different nature, such as color texture and spatial depth. These findings can inform the ongoing refinement of terrain classification systems for applications in robotics and autonomous navigation. © 2024 The Authors.

关键词： RGB color model

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POMDP-Based Real-Time Path Planning for Manipulation of Multiple Microparticles via Optoelectronic Tweezers

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Cyborg and Bionic systems 2022年第1期2022卷 303-313页

作者： Jiaxin Liu Huaping Wang Menghua Liu Ran Zhao Yanfeng Zhao Tao Sun Qing Shi Intelligent Robotics Institute School of Mechatronical Engineering Bejing Institute of TechnologyBeijing 10081China Key Laboratory of Biomimetic Robots and Systems(Beijing Institute of Technology) Ministry of EducationBeijing 100081China School of Medical Technology Beijing Institute of TechnologyBeijing 100081China Bejing Advanced Innovation Center for Itelligent Robots and Systems Beijing Institute of TechnologyBeijing 100081China

With high throughput and high flexibility,optoelectronic tweerers(OETs)hold huge potential for massively parallel ***,the trajectory of the virtual electrode has been planned in advance in most synchronous manipulations for multiple targets based on an optically induced dielectrophoresis(ODEP)mechanism,which is insuficient to ensure the stability and eficiency in an environment with potential collision *** this paper,a synchronously discretized manipulation method based on a centralized and decoupled path planner is proposed for transporting microparticles of diferent types with an OET *** approach based on the K uhn-Munkres algorithm is utilized to achieve the goal assignment between target microparticles and goal *** the assistance of a visual feedback module,a path planning approach based on the POMDP algorithm dynamically determines the motion strategies of the particle movement to avoid potential *** geometrical parameters of the virtual electrodes are optimized for different types of particles with the goal of maximum transport *** experiments of micropatterning with different morphologies and transporting multiple micropartides(e.g,polystyrene microspheres and 3T3 cells)to goal positions are *** results demonstrate that the proposed manipulation method based on optoelectronic tweezers is effective for multicell transport and promises to be used in biomedical manipulation tasks with high flexibility and efficiency.

关键词： manipulation positions assignment

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Path Tracking control for Helical Microrobots Based on Fusion of Geometric and Model-Free Methods 13

Path Tracking Control for Helical Microrobots Based on Fusio...

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13th IEEE International Conference on CYBER Technology in Automation, control, and intelligent systems, CYBER 2023

作者： Zhong, Shihao Wang, Huaping Shi, Qing Hou, Yaozhen Qiu, Yukang Sun, Tao Huang, Qiang Fukuda, Toshio School of Medical Technology Beijing Institute of Technology Beijing100081 China Key Laboratory of Biomimetic Robots and Systems Beijing Institute of Technology Ministry of Education Beijing100081 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing100081 China Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9798350315196

Helical micron-sized robots driven by magnetic fields have garnered significant interest, particularly in the field of tracking control. However, at the microscale, time-varying uncertain perturbations in both the environment and electromagnetic system can cause these robots to deviate from their preset state. Here, we propose a novel control method that combines geometric and model-free controllers in a complementary manner to achieve accurate path-tracking of a helical microrobot on underwater unstructured surfaces. The geometric controller acts as a feedforward controller handling path information and formulating guidance law, while the model-free controller responds directly to the lateral error. To compensate for unmodeled nonlinear dynamics and unknown disturbances and achieve system dynamic linearization, we employ an extended state observer. To validate the proposed method and determine suitable ranges for input parameters of the controllers, simulations were carried out. The effectiveness of our path-tracking control method is validated through experimental results. The control technique provides an initial investigation into addressing the effects of uncertainties and perturbation on the control capabilities of magnetic microrobots. © 2023 IEEE.

关键词： controllers

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3D Reconstruction of Weakly Textured Objects Based On Denoising Polarized Images 41

3D Reconstruction of Weakly Textured Objects Based On Denois...

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第41届中国控制会议

作者： Youai Wang Yi Liu Chi Xu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Eduction CRRC Zhuzhou Locomotive Co. Ltd.

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Traditional 3D visual reconstruction technology based on feature extraction is difficult to estimate the surface depth information of a smooth object with a single texture,while the polarization 3 D reconstruction technology can recover the surface normal information from the image pixel by pixel,which has the characteristics of high precision,low texture dependence and strong material ***,the normals recovered from the polarization information have the problem of multi-value ambiguity,which needs to be corrected before the accurate normal information can be *** the same time,the image collected by the polarization camera contains a lot of noise,which will greatly affect the accuracy of reconstruction *** this paper,the characteristics of polarization information are used to denoise the polarization image,and the reference normal information is used as the prior information for correcting the polarization ***,the degree of polarization and angle of polarization are calculated based on the polarized image,then the two are fused and denoised by the Block Matching threedimensional(BM3D) method,and then the multi-valued ambiguity of polarization normal is corrected according to the reference normal ***,the corrected polarization normal is integrated to obtain a high-precision 3D shape of the object.

关键词： Polarization Denoising 3D Reconstruction Weakly Textured Objects Normal Multi-value Correction

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A Novel Deep Learning Representation for Industrial control System Data

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intelligent Automation & Soft Computing 2023年第6期36卷 2703-2717页

作者： Bowen Zhang Yanbo Shi Jianming Zhao Tianyu Wang Kaidi Wang Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang110016China Shenyang Institute of Automation Chinese Academy of SciencesShenyang110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang110169China Shenyang Aircraft Corporation Shenyang110850China Molarray Research TorontoL4B3K1Canada

Feature extraction plays an important role in constructing artificial intel-ligence(AI)models of industrial control systems(ICSs).Three challenges in this field are learning effective representation from high-dimensional features,data heterogeneity,and data noise due to the diversity of data dimensions,formats and noise of sensors,controllers and ***,a novel unsupervised learn-ing autoencoder model is proposed for ICS data in this *** traditional methods only capture the linear correlations of ICS features,our deep industrial representation learning model(DIRL)based on a convolutional neural network can mine high-order features,thus solving the problem of high-dimensional and heterogeneous ICS *** addition,an unsupervised denoising autoencoder is introduced for noisy ICS data in *** the denoising autoencoder allows the model to better mitigate the sensor noise *** this way,the represen-tative features learned by DIRL could help to evaluate the safety state of ICSs more *** tested our model with absolute and relative accuracy experi-ments on two large-scale ICS *** with other popular methods,DIRL showed advantages in four common indicators of AI algorithms:accuracy,precision,recall,and *** study contributes to the effective analysis of large-scale ICS data,which promotes the stable operation of ICSs.

关键词： Industrialcontrolsystem machinelearning deeplearning autoencoder

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Remote Sensing Image Classification Based on Lightweight Network and Pruning

Remote Sensing Image Classification Based on Lightweight Net...

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2022 Chinese Automation Congress, CAC 2022

作者： Wang, Zexi Xue, Wei Chen, Kehui Ma, Shaopeng School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

In recent years, deep neural network has continuously improved the performance of remote sensing image classification. Though The deep neural network model is powerful, it is difficult to deploy on resource-constrained hardware platforms such as mobile terminal devices and embedded devices due to the large number of network parameters. In this paper, a novel lightweight network (LW-Net) model and a network pruning method are used for remote sensing image classification. This LW-Net model adopts a net block unit to obtain more characteristic graphs with less computational complexity. The proposed network pruning method uses the sparsity regularization on the influence factor in BN layer to automatically identified and pruned unimportant channels to make the model structure simpler. Experimental results demonstrate compared with traditional deep neural networks, the proposed model with the network pruning method can greatly reduce the computational complexity and model parameters with a little accuracy loss. © 2022 IEEE.

关键词： Deep neural networks

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Vital Signs Detection Based on Scale-Space Representation and Empirical Wavelet Transform for FMCW Radar

Vital Signs Detection Based on Scale-Space Representation an...

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2022 Chinese Automation Congress, CAC 2022

作者： Wu, Dongchang Xue, Wei Yang, Xinya Li, Tin Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9781665465335

With the development of radar technology, frequency modulated continuous wave (FMCW) radar has been used for non-contact vital signs detection. In order to suppress the environmental noise and interference of breathing harmonics on heartbeat signal, this paper proposes a new vital sign detection method based on scale-space representation (SSR) and empirical wavelet transform (EWT) for the FMCW radar. First, a low-pass filter is set for the high-frequency noise elimination outside the frequency range of vital sign signals. Second, SSR is used to adaptively segment the spectrum of signals to obtain the initial frequency boundaries, and the kurtosis of the spectrum is applied to segment the spectrum again and obtain the final frequency boundaries to further eliminate noise. Third, the empirical wavelet filter bank is constructed by using the determined boundaries and EWT is used to decompose the signals to several components. Finally, according to the frequency ranges of components and the correlation between the components and vital sign signals, the components are selected to reconstruct the breathing and heartbeat signals. The experimental results show that the proposed method achieves a better detection performance than the classical EWT and empirical mode decomposition (EMD). © 2022 IEEE.

关键词： Wavelet transforms

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Optimal Scheduling Strategy of Limited Electricity Based on Energy Sharing of Multi-microgrid

Optimal Scheduling Strategy of Limited Electricity Based on ...

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2022 Chinese Automation Congress, CAC 2022

作者： Zeng, Zihan Li, Danyun Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

ISBN: (纸本)9781665465335

In the environment of limited electricity supply in distribution network, due to the limitation of its own power capacity and the uncertainty of new energy output, there will be insufficient electricity supply in microgrid, which will affect the economy and comfort of users in microgrid system. Therefore, aiming at the situation of limited electricity supply in distribution network, multi-microgrid system is taken as the research object, and the cooperative game method is adopted to realize the energy sharing of multi-microgrid system, and then the limited electricity optimal dispatching model of multi-microgrid system is constructed to realize the reasonable power distribution for different types of loads. Finally, the simulation results show that this strategy can effectively realize power sharing, reduce outage loss and improve user satisfaction. © 2022 IEEE.

关键词： Electric power distribution

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An automated FBG localization algorithm for distributed strain sensing system using weak FBG array 4

An automated FBG localization algorithm for distributed stra...

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4th International Computational Imaging Conference, CITA 2024

作者： Liang, Changshuo Zhou, Xiaoxu Wang, Yu Bai, Qing Gao, Yan Zhang, Hongjuan Jin, Baoquan Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan China Shanxi Transportation Technology Research & Development Co. Ltd. Shanxi Taiyuan China College of Electrical and Power Engineering Taiyuan University of Technology Taiyuan China

ISBN: (纸本)9781510688834

We proposed a Fiber Bragg grating (FBG) localization algorithm for Optical Frequency Domain Reflectometry (OFDR) sensing system with high density weak FBG array. The wavelength selection characteristics of FBG, which are revealed in the distance-wavelength domain spectrum of OFDR signal, are used as the standard for FBG localization. The OFDR system for FBG strain sensing using the proposed method achieved a strain sensing on 45.36 m long FBG array, which is capable of sensing strain up to 3000 μΕ, with spatial resolution of 1 cm, and root mean square error (RMSE) of 0.00192 nm. © 2025 SPIE.

关键词： Fiber Bragg gratings

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