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Parallel Learning:Overview and Perspective for Computational Learning Across Syn2Real and Sim2Real

IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 603-631页

作者： Qinghai Miao Yisheng Lv Min Huang Xiao Wang Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Artificial Intelligence Anhui UniversityHefei 266114China Qingdao Academy of Intelligent Industries Qingdao 230031China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

The virtual-to-real paradigm,i.e.,training models on virtual data and then applying them to solve real-world problems,has attracted more and more attention from various domains by successfully alleviating the data shortage problem in machine *** summarize the advances in recent years,this survey comprehensively reviews the literature,from the viewport of parallel ***,an extended parallel learning framework is proposed to cover main domains including computer vision,natural language processing,robotics,and autonomous ***,a multi-dimensional taxonomy is designed to organize the literature in a hierarchical ***,the related virtual-toreal works are analyzed and compared according to the three principles of parallel learning known as description,prediction,and prescription,which cover the methods for constructing virtual worlds,generating labeled data,domain transferring,model training and testing,as well as optimizing the strategies to guide the task-oriented data generator for better learning *** issues remained in virtual-to-real are ***,the future research directions from the viewpoint of parallel learning are suggested.

关键词： Machine learning parallel learning parallel systems sim-to-real syn-to-real virtual-to-real

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Identification and Prediction of Microvascular Invasion in Hepatocellular Carcinoma Based on Multiple Sequence Fusion Images

Identification and Prediction of Microvascular Invasion in H...

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Chinese control Conference (CCC)

作者： Mingguang Lu Yuan Zhu School of Automation China University of Geosciences Wuhan Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Hepatocellular carcinoma (HCC) is one of the most difficult diseases to be treated fundamentally in the medical field in today’s world, and the recurrence rate of HCC has been increasing year by year in recent years. The study on the identification and prediction of microvascular invasion phenomenon (MVI) in hepatocellular carcinoma is beneficial to the postoperative prevention of hepatocellular carcinoma patients, which can greatly improve the survival probability of patients after surgery. In this study, a new MVI prediction method (MSF-GWO-GPR) was proposed, which combines the multi-sequence image features of imaging histology, sifts out the unimportant features through the T-test method and the dimensionality reduction of Lasso regression, and establishes the multi-sequence Gaussian process regression (GPR) prediction model for data fusion, and combined with the Gray Wolf Optimization (GWO) algorithm to design a suitable optimization objective function to optimize the hyper-parameters in the GPR, in order to get better prediction results. Compared with the existing methods, the data from different sequences of MRI images are selected for fusion in this study, which makes the feature data richer and more complete, and the model applicability is better; moreover, by optimizing the hyperparameters in the model through the GWO, the model can be made more accurate, reduce the risk of misidentified prediction, and improve the accuracy rate. The experimental results show that MSF-GWO-GPR outperforms widely used machine learning methods in terms of accuracy, F1 score, precision, recall and AUC metrics. This may provide a new idea for the identification and prediction of MVI in hepatocellular carcinoma.

关键词： Liver cancer Accuracy Magnetic resonance imaging Prevention and mitigation Surgery Predictive models Feature extraction

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Two-Stage Representation Refinement Based on Convex Combination for 3-D Human Poses Estimation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6500-6508页

作者： Chen, Luefeng Cao, Wei Zheng, Biao Wu, Min Pedrycz, Witold Hirota, Kaoru China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Macau University of Science and Technology Institute of Systems Engineering Taipa999078 China Istinye University Research Center of Performance and Productivity Analysis Istanbul34010 Turkey Tokyo Institute of Technology Yokohama226-8502 Japan

In the human pose estimation task, on the one hand, 3-D pose always has difficulty in dividing different 2-D poses if the view is limited;on the other hand, it is hard to reduce the lifting ambiguity because of the lack of depth information, it is an important and challenging problem. Therefore, two-stage representation refinement based on the convex combination for 3-D human pose estimation is proposed, in which the two-stage method includes a dense-spatial-temporal convolutional network and a local-to-refine network. The former is applied to determine the features between each video frame;the latter is used to get the different scales of pose details. It aims to address the difficulty of estimating 3-D human pose from 2-D image sequences. In such a way, it can better use the relations between every frame in the sequence of the pose video to produce more accurate results. Finally, we combine the above network with a block called convex combination to help refine the 3-D pose location. We test the proposed approach on both Human3.6m and MPII datasets. The result confirms that our method can achieve better performance than improved CNN supervision, a simple yet effective baseline, and coarse-to-fine volumetric prediction. Besides, a robustness test experiment is carried out for the proposed method while the input is interrupted. The result verifies that our method shows better robustness. © 2024 IEEE.

关键词： Convolution

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A Reinforcement Learning Approach for Robust Restoration of Generators in Power System

A Reinforcement Learning Approach for Robust Restoration of ...

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2022 Chinese automation Congress, CAC 2022

作者： Li, Huimiao Yang, Xiaozhou Zhai, Chao Hubei Key Laboratory of Advanced Control and Intelligent Automation Fo Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Future Resilient Systems Singapore-ETH Centre Create Campus Singapore

ISBN: (纸本)9781665465335

In the past decades, cascading blackouts have caused serious damages to power systems and affected the normal operation of society, so it is crucial to quickly restore the damaged power system to normal state. In this paper, a reinforcement learning (RL) approach is developed to achieve the robust restoration of generators in power systems. Firstly, the performance recovery of damaged power system is modeled as markov decision process, and constraints such as line voltage and active power output of generators are considered. Secondly, a RL algorithm is proposed to search the optimal control strategy for generator units recovery. Based on the proposed restoration approach, Q-learning algorithm is employed to obtain the optimal strategy for power supply of generaors in power grids. Finally, numerical simulations are carried out on IEEE 9-bus system under different scenarios of external disturbances and certainties. The simulation results demonstrate the effectiveness and feasibility of the proposed approach. © 2022 IEEE.

关键词： Reinforcement learning

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Research on Path Planning of Mobile Robot Based on DWA-IMP-A∗ Algorithm 42

Research on Path Planning of Mobile Robot Based on DWA-IMP-A...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Zhi Zhang, Lin Wang, Shoukun Niu, Tianwei Xu, Yongkang Cao, Jin School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology Beijing100081 China

ISBN: (纸本)9789887581543

Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of path planning, the most popular A∗ algorithm has some problems, such as heuristic function cannot be estimated accurately, node redundancy, path is not smooth, and obstacle avoidance cannot be achieved in real time. To solve these problems, A fusion algorithm of improved A∗ combined with reverse path and dynamic window method (DWA-IMP-A∗) was proposed. The algorithm refines the heuristic function by incorporating the reverse path. The node optimization algorithm is used to further reduce the path length. The generated trajectories are smoothed by cubic spline interpolation. At the same time, it is integrated with the improved DWA algorithm to improve the efficiency and safety of robot path planning. The algorithm takes ROS mobile robot as the carrier and is tested under typical road conditions. Compared with A∗ algorithm, the planning time is reduced by 54.6% and the path length is reduced by 6.37%. Experimental results verify the effectiveness and robustness of the algorithm. The research results have certain reference significance for the path planning of various types of mobile robots and the research of driverless vehicles. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Motion planning

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Investigation of a tunnel magnetoresistance based vector magnetometer for magnetic anomaly detection 2

Investigation of a tunnel magnetoresistance based vector mag...

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2022 2nd International Conference on advanced Materials and Mechatronics, ICAMM 2022

作者： Wang, Hongpeng Yang, Ruiping Luo, Wang Ge, Jian Liu, Huan Dong, Haobin 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

The development of high-performance and miniaturized magnetometers is important for small-scale target magnetic anomaly detection. In this work, a miniaturized three-axis vector magnetometer based on the tunnel magnetoresistance (TMR) technique is investigated for magnetic anomaly detection. First, the miniaturized three-axis TMR vector magnetometer is constructed, and then, the limit of detection tests and the magnetic anomaly detection tests are performed. The indoor experimental results show that the proposed magnetometer can capture the magnetic anomalies higher than 3.9 nT, with the low-frequency equivalent magnetic noise of 46.89 pT/√Hz@1Hz. The outdoor experimental results show that the proposed magnetometer can effectively detect small-scale magnetic targets such as hammers at a distance of about 1.5 m. With the advantages of small size, low power consumption, and high magnetic measurement sensitivity, the TMR magnetometer has great application prospects for long-term magnetic anomaly monitoring, high-density magnetic imaging, and other fields. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Magnetometers

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Speech Emotion Recognition Based on Clustering Assistance

Speech Emotion Recognition Based on Clustering Assistance

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2022 Chinese automation Congress, CAC 2022

作者： Peng, Zhi-Kun Liu, Zhen-Tao Han, Meng-Ting China University of Geosciences School of Automation 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

ISBN: (纸本)9781665465335

Speech emotion recognition (SER) is a key technology to achieve natural human-computer interaction. The development of SER is significantly influenced by the scale of the sample. In recent years, the study of SER has been intensified by introducing data augmentation methods. However, most of these methods directly augment the sample data scale, neglecting the rational analysis and utilization of the feature distribution of samples. In this paper, we propose a new framework for SER based on clustering assistance, which can utilize the feature distribution information of the sample data directly and effectively. It considers the sample proportion of each emotion category in the clusters obtained by clustering, converts it into a probability score, which is called the clustering emotion probability score, and fuses it with the emotion probability score from the simple classification model according to different fusion weighting factors. We evaluated the proposed method with the baseline model on the IEMOCAP dataset. Experimental results show that our method achieves better results than the baseline model in terms of both weighted and unweighted accuracy. © 2022 IEEE.

关键词： K-means clustering

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Fabrication and Path Following control of a Magnetic Soft Microrobot 8

Fabrication and Path Following Control of a Magnetic Soft Mi...

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8th International Conference on control Science and systems Engineering, ICCSSE 2022

作者： Tang, Jianhui Zhang, Pan Wu, Jundong Wang, Yawu 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

ISBN: (纸本)9781665484138

Magnetically-controlled soft microrobots have great application prospects because of small size, flexible motion and wireless control. In this paper, a magnetically-controlled soft microrobot is designed and fabricated. In order to achieve its path-following control, two open-loop control strategies and a closed-loop one are developed. Especially, for the closed-loop control strategy, we present the image processing method and the pure pursuit algorithm, where the former is used to obtain the position and posture of the microrobot required for the latter. Finally, the developed open-loop and closed-loop control strategies are verified by carrying out the experiments. These methods are promising in numerous applications because of the ease of implementation. © 2022 IEEE.

关键词： Image processing

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Axial-torsional coupled drill-string vibration analysis based on the bit-rock interaction model considering the drilling fluid factor 13

Axial-torsional coupled drill-string vibration analysis base...

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13th Asian control Conference, ASCC 2022

作者： Huang, Hengyu Wu, Min Lu, Chengda Cao, Weihua Chen, Xin 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

ISBN: (纸本)9788993215236

To characterize drill-string system's dynamic reaction, the axial-torsional coupled drill-string vibration model need to be studied. The drill-string takes little consideration for the drilling fluid factor, and drill-string vibration model for torque and drawworks pull inputs have limited relevance in geological drilling. So an axial-torsional coupled drill-string vibration model is established, with inputs of rope lowering and rotary table rotating speed, and the influence of the drilling fluid factor is taken into account. Firstly, we build a drill-string model with the winch rope speed and rotating speed inputs based on material mechanics theory. Then, the axial-torsional coupled bit-rock interaction model is established, taking the factor of drilling fluid into consideration, and the axial and torsional drill-string vibration is coupled through the bit-rock interaction model. Finally, the model's validity is proved by simulation of the drill-string system and the verification of field data. © 2022 ACA.

关键词： Drilling Vibrations Couplings Analytical models Fluids Torque Geology

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Photonic crystal fiber pressure sensing based on birefringence effect 8

Photonic crystal fiber pressure sensing based on birefringen...

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8th Symposium on Novel Photoelectronic Detection Technology and Applications

作者： Meng, Fanlong Wang, Hong Fang, Di 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

ISBN: (数字)9781510653122

ISBN: (纸本)9781510653115

In order to achieve high sensitivity of pressure magnitude and direction measurement, the elasto-optical effect of photonic crystal fiber is studied by the full vector finite element method. First of all, the birefringence characteristics of the fundamental mode of the edge-pass high birefringence photonic crystal fiber under lateral pressure and static liquid pressure are studied. The results show that the effective refractive index of the two polarization fundamental modes changes obviously under the static liquid pressure, the phase mode birefringence changes linearly with the pressure. The second, the influence of fiber structure on birefringence is discussed, the results show that the size of birefringence can be influenced by changing the shape, position and size of the air holes in the fiber. The structure of photonic crystal fiber with high birefringence is obtained by optimizing the structure. The result show that, when free space wavelength is 1.55µm and pressure is 120MPa, the sensitivity of its phase modal birefringence up to 1.498×10-5 MPa-1 and the maximum measurable hydrostatic pressure value is 353MPa. The research is meaningful to realize the pressure sensor with multi-angle and high sensitivity. © 2022 SPIE

关键词： Birefringence

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