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2021 International Joint Conference on Neural Networks, IJCNN 2021

作者： Chen H.-B. Ni Z.-L. Li Z. Bian G.-B. Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing 100190 China University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9780738133669

Automatically recognizing surgical gestures plays a key role in computer-assisted surgery and automatic skill assessment. Solutions to this task that only rely on video without additional sensor hardware have attracted great attention since they are economical and feasible. However, it is still a challenging problem due to the variable gesture durations and the oversegmentation problem that occurred in a long gesture duration. To address the above problems, we propose a cascade network with boundary-adaptive filter to dynamically capture the long-range temporal dependencies and reduce the over-segmentation errors obviously. A cascade module is designed to enhance the temporal modeling abilities in different timescales, in which multiple similar temporal convolution networks are divided into cascade stages and a fusion stage. Every cascade stage with different temporal receptive fields has a frame-specific weight to adjust the distribution of each stage and they will be aggregated into the fusion stage to refine the predictions. The frame-specific model architecture may incur a more serious over-segmentation problem. A boundary-adaptive filter is designed to leverage gesture boundary information to smooth the prediction results adaptively, which maintains consistency within a gesture duration while keeping the gesture-crossing discrepancy. We evaluate our model on the JHU-ISI Gesture and Skill Assessment Working Set (JIGSAWS). The proposed method reaches the state-of-the-art frame-wise accuracy (83.79%) and comparable segment-level performance (83.35% F1@50). © 2021 IEEE.

关键词： action segmentation surgical gesture recognition temporal convolutional network video understanding

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Visuotactile Feedback Parallel Gripper for Robotic Adaptive Grasping

Visuotactile Feedback Parallel Gripper for Robotic Adaptive ...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Zhang, Boyue Cui, Shaowei Zhang, Chaofan Hu, Jingyi Wang, Shuo School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing100190 China Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai200031 China

ISBN: (纸本)9781665481090

In robot grasp and dexterous manipulation tasks, tactile sensing is important for the control adjustment of the manipulator. In this paper, we present a novel low-cost parallel gripper with high-resolution tactile sensing, named the GelStereo Gripper. Furthermore, an adaptive grasp strategy is proposed to endow the gripper with tactile-feedback grasp stability-maintaining ability. We install the gripper on our robot platform and conduct various grasp experiments by utilizing proposed control methods. Experimental results verify the reliability of the GelStereo gripper and also prove the effectiveness of the proposed strategy for experimental objects with different features. © 2022 IEEE.

关键词： Grippers

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Zero-Sum Differential Game-Based Fault-Tolerant Tracking control for Nonlinear systems With Multiplicative Failures

Zero-Sum Differential Game-Based Fault-Tolerant Tracking Con...

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Chinese Automation Congress (CAC)

作者： Cong Tan Mingduo Lin Hongbing Xia Bo Zhao Yancai Xu School of Systems Science Beijing Normal University Beijing China Key Laboratory of Industrial Internet of Things & Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

A novel fault-tolerant tracking control (FTTC) approach for affine nonlinear systems is developed from the perspective of zero-sum differential games (ZSDG) to deal with unknown multiplicative actuator failures in this paper. By regarding the control input and the multiplicative actuator failure as two players of a zero-sum game, a performance index function reflecting the trajectory tracking error, the control policy and the unknown failure is established. To handle the tracking Hamilton-Jacobi-Isaacs (HJI) equation associated with the established performance index function, a critic neural network is utilized. Then, the Nash equilibrium solution can be obtained, and the FTTC is achieved. The stability of the faulty nonlinear system is examined through Lyapunov-based approach. Finally, simulation results of a spring system is provided to ensure the utility and the realizability of the ZSDG-based FTTC approach.

关键词： Actuators Fault tolerance Trajectory tracking Simulation Fault tolerant systems Stability criteria Mathematical models

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jialiang Luo Shichao Chen Yisheng Lv Wenqiao Sun Fan Yang Ruijie Xu The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited Beijing China The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University Jinan China Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic University Hong Kong China

With the rapid development and widespread application of Inertial Measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field.

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Generalized Zero-Shot Learning via Implicit Attribute Composition

Generalized Zero-Shot Learning via Implicit Attribute Compos...

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IEEE International Conference on systems, Man and Cybernetics

作者： Lei Zhou Yang Liu Qiang Li School of Computer Science and Artificial Intelligence Wuhan University of Technology Wuhan China College of Computer Science and Technology Zhejiang University Hangzhou China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Zero-shot learning (ZSL) is an important but challenging task in computer vision that aims to identify unseen classes without matching training samples. Current cutting-edge ZSL methods based on locality focus on acquiring the explicit locality of distinguishing characteristics, which could face a lack of adequate supervision at the class attribute level. This paper introduces a novel approach called IAC, which aims to learn Implicit Attribute Composition for ZSL. This method is more comprehensive compared to attribute localization that solely focuses on class-level attribute supervision. IAC utilizes subspace representations that efficiently capture the inherent structure of high-dimensional image features. Then, we learn implicit attribute composition through subspace representation learning. The superiority of the proposed IAC compared to the state-of-the-art is demonstrated through sufficient experiments conducted on three commonly used ZSL datasets, CUB, SUN, and AwA2.

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A Novel Two-Stream Model for Human Motor Characteristics Learning

A Novel Two-Stream Model for Human Motor Characteristics Lea...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Xiang, Tian-Yu Zhou, Xiao-Hu Xie, Xiao-Liang Liu, Shi-Qi Yang, Hong-Jun Feng, Zhen-Qiu Hao, Jian-Long Hou, Zeng-Guang Institute of Automation The State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The School of Information Shanxi University of Finance and Economics Taiyuan030006 China The CAS Center for Excellence in Brain Science and Intelligence Technology Beijing100190 China Institute of Systems Engineering Macau University of Science and Technology The Joint Laboratory of Intelligence Science and Technology Taipa China

ISBN: (纸本)9781665481090

Electroencephalogram (EEG) is one of the most pop-ular sources for learning human motor characteristics. However, most current methods only consider its temporal features and overlook spatial information. This paper proposes a novel two-stream model based on spatial and temporal features to learn human motor characteristics from EEG signals. The spatial stream is analyzed by graph neural networks (GNN) to extract the relationship among different channels. Adjacent matrices can be learned through the training process, unlike pre-defined ones used in other GNN-based EEG analysis methods. The temporal stream is processed with mixed convolution structures, which consist ID convolution, depthwise convolution, and separable convolution. The features of two streams are fused with fully-connected neural networks for human motor characteristics learning. Experimental results show the proposed model can achieve the accuracy of 0.684/0.709 (four classes motor imagery) in subject-independent/dependent schemes, demonstrating the promising for it used in brain computer interface (BCI) scenarios. © 2022 IEEE.

关键词： Convolution

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Blockchain-based consensus study on distributed control systems 1

Blockchain-based consensus study on distributed control syst...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Zhu, Jing Deng, Hongchang Li, Xiang Yuan, Yong Wang, Feiyue College of Automation Engineering Nanjing University of Aeronautics and Astronautics Nanjing China School of Mathematics Renmin University of China Beijing China Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9781665433372

In this paper, two blockchain-based consensus mechanisms are proposed for distributed control systems, those are the proof-of-work-based (PoW-based) and proof-of-stake-based (PoS-based) consensus mechanisms. The basic idea and process of these blockchain-based consensus mechanisms are introduced, giving rise to the dynamic, impartial and efficient consensus compared with the consensus protocol achieved by traditional control theories. © 2021 IEEE.

关键词： Multi agent systems

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Optical Imaging of Epigenetic Modifications in Cancer:A Systematic Review

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Phenomics 2022年第2期2卷 88-101页

作者： Yang Du Pei Zhang Wei Liu Jie Tian CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imagingthe State Key Laboratory of Management and Control for Complex SystemsInstitute of AutomationChinese Academy of SciencesBeijing 100190China The University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Department of Supportive Care Center and Day Oncology UnitPeking University Cancer Hospital and InstituteBeijing 100142China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of MedicineBeihang UniversityBeijing 100191China School of Life Science and Technology Xidian UniversityXi’an 710071ShaanxiChina

Increasing evidence has demonstrated that abnormal epigenetic modifications are strongly related to cancer ***,sensitive and specific detection of epigenetic modifications could markedly improve biological investigations and cancer precision medicine.A rapid development of molecular imaging approaches for the diagnosis and prognosis of cancer has been observed during the past few *** biomarkers unique to epigenetic modifications and targeted imaging probes have been characterized and used to discriminate cancer from healthy tissues,as well as evaluate therapeutic *** this study,we summarize the latest studies associated with optical molecular imaging of epigenetic modification targets,such as those involving DNA methylation,histone modification,noncoding RNA regulation,and chromosome remodeling,and further review their clinical application on cancer diagnosis and ***,we further propose the future direc-tions for precision imaging of epigenetic modification in *** by promising clinical and preclinical studies associated with optical molecular imaging technology and epigenetic drugs,the central role of epigenetics in cancer should be increasingly recognized and accepted.

关键词： Epigenetic modification Optical imaging Cancer Imaging probe

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Multi-Sensor Fusion Perception System in Train 10

Multi-Sensor Fusion Perception System in Train

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10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Gao, Hongfei Huang, Yongzhen Li, Haoran Zhang, Qichao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Watrix Technology Beijing Co. Ltd. China

ISBN: (纸本)9781665424233

Environment perception is one of the most crucial modules in a self-driving system. In an open subway environment, pedestrians, equipment boxes and other unknown obstacles often appear. The perception module is required to quickly and accurately recognize the obstacle and measures the corresponding distance data. This paper proposes a detection and ranging fusion method based on one Lidar and two different focal length cameras, which be applied in the subway system, to alert drivers to possible obstacles and assist brake. First, the relative transformation between Lidar and camera is calibrated to find the intrinsic and extrinsic matrices. Modified SSD network is trained on the self-built dataset to detect the potential obstacle and produces the final detection bounding box. Then, rail track segmentation network RailNet is applied to obtain rail shape features, which offers a region of interest (ROI) for sensing systems in point cloud clustering algorithms. Further, the fusion information is utilized to estimate the distance of objects detected by the SSD detector. The proposed method can realize real-time pedestrian detection and range on the onboard embedded platform Jetson Xavier, which satisfies the subway environment's perception requirements. © 2021 IEEE.

关键词： Optical radar

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AGI in Metaverse for Smart Cities and Societies: A Cyber Physical Social Approach

AGI in Metaverse for Smart Cities and Societies: A Cyber Phy...

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control Conference (ANZCC), Australian and New Zealand

作者： Xiao Wang Jun Huang Yong-Lin Tian Fei-Yue Wang Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University Hefei China Faculty of Innovation Engineering Macau University of Science and Technology Macao China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China Macao Institute of Systems Engineering Macau University of Science and Technology Macao China

The development of artificial general intelligence (AGI) and metaverse technologies hold great potential to enhance the effectiveness of smart cities and societies. we present a cyberphysical-social approach to integrating AGI into metaverse-based smart cities and societies, with a specific focus on parallel intelligence. The proposed approach considers the interplay between the physical environment, digital systems, social dynamics, and emerging forms of parallel intelligence, as well as swarm intelligence and collective intelligence. By leveraging these forms of parallel intelligence, the integration of AGI can create more responsive and proactive infrastructure, personalized and efficient services, and foster greater community engagement. The metaverse acts as a platform for simulating real-world scenarios and testing and refining AGI models before deployment in the physical world, while also facilitating the development and coordination of parallel intelligence. However, ethical considerations must be taken into account to ensure responsible deployment and avoid exacerbating existing societal inequalities or infringing upon individual privacy rights. This report provides a comprehensive framework for the integration of AGI and parallel intelligence into metaverse-based digital and smart organizations, while emphasizing the importance of human ethics, social responsibility, and ecological sustainability.

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