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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Mengke Wang Honghao Lv Ruohan Wang Haiteng Wu Lipeng Chen Yi Chen Haihui Yuan Geng Yang State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou Shenhao Technology Hangzhou China Robotics X Tencent Shenzhen China Intelligent Manufacturing Center DongFang Electric Corporation Academy of Science and Technology Co Chengdu China China South Industries Group Corporation Hangzhou Automation Research Insititute Co. Ltd. China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Zhejiang Key Laboratory of Intelligent Operation and Maintenance Robot Hangzhou China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

With the advancement of intelligent manufacturing, an increasing number of industrial production processes are transforming unmanned operations. This trend is particularly evident in factories that involve potential safety hazards, where the demand for unmanned production is becoming increasingly urgent. Teleoperation, as a core technology for achieving unmanned factories, holds tremendous importance in keeping workers safe from danger. However, traditional teleoperation strategies encounter challenges due to mismatches between master and slave workspaces, making it difficult to achieve both high precision and operation across large workspaces simultaneously. To address this issue, this paper proposes an event-triggered control strategy for a teleoperated robot system. By introducing a foot pedal as the event-triggered switch, the enablement and termination of teleoperation are associated with the activation of the pedal. Through resetting the start position, fine-grained teleoperation is achieved throughout the entire workspace of the robot. To demonstrate the advantages of the proposed control strategy, a mimicked wiring operation task scenario is constructed for experimental verification, and the teleoperation tasks are completed successfully and efficiently.

关键词： Wiring Accuracy Service robots Switches Market research Production facilities Main-secondary

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Hypergraph-based Multi-View Action Recognition using Event Cameras

arXiv

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arXiv 2024年

作者： Gao, Yue Lu, Jiaxuan Li, Siqi Li, Yipeng Du, Shaoyi BNRist THUIBCS BLBCI School of Software Tsinghua University Beijing100084 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China BNRist THUIBCS BLBCI Department of Automation Tsinghua University Beijing100084 China Department of Ultrasound The Second Affiliated Hospital of Xi’an Jiaotong University China National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China

Action recognition from video data forms a cornerstone with wide-ranging applications. Single-view action recognition faces limitations due to its reliance on a single viewpoint. In contrast, multi-view approaches capture complementary information from various viewpoints for improved accuracy. Recently, event cameras have emerged as innovative bio-inspired sensors, leading to advancements in event-based action recognition. However, existing works predominantly focus on single-view scenarios, leaving a gap in multi-view event data exploitation, particularly in challenges like information deficit and semantic misalignment. To bridge this gap, we introduce HyperMV, a multi-view event-based action recognition framework. HyperMV converts discrete event data into frame-like representations and extracts view-related features using a shared convolutional network. By treating segments as vertices and constructing hyperedges using rule-based and KNN-based strategies, a multi-view hypergraph neural network that captures relationships across viewpoint and temporal features is established. The vertex attention hypergraph propagation is also introduced for enhanced feature fusion. To prompt research in this area, we present the largest multi-view event-based action dataset THUMV-EACT-50, comprising 50 actions from 6 viewpoints, which surpasses existing datasets by over tenfold. Experimental results show that HyperMV significantly outperforms baselines in both cross-subject and cross-view scenarios, and also exceeds the state-of-the-arts in frame-based multi-view action recognition. Copyright © 2024, The Authors. All rights reserved.

关键词： Cameras

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A Novel Fractional Order Impedance Control and Its Performance Analysis

A Novel Fractional Order Impedance Control and Its Performan...

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第33届中国控制与决策会议

作者： Guangrong Chen Huafeng Lu Bowen Hou Sheng Guo Junzheng Wang Robotics Research Center Beijing Jiaotong University Beijing Engineering and Technology Research Center of Rail Transit Line Safety and Disaster Prevention State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

In traditional impedance control model,the contact force can be reduced ***,there exists a tracking error at the stable state due to the existence of stiffness,which is not conducive to tackle tasks based on high performance position control for ***,this paper proposes a novel dynamic interaction model:fractional order impedance control,to address this ***,an integral item is added into the traditional impedance model to eliminate the tracking ***,the idea of fractional order is introduced to make the orders of inertia,damping,and stiffness change from integers to fractions to achieve more significant compliant ***,simulation results validate the advantages of proposed fractional order impedance control and it can be also employed to absorb/increase,hold/keep,and dissipate/decrease system energy to achieve jumping,bouncing and friendly contact,***,stability analysis and three criterions of choosing and tuning 6 classic parameters in the proposed fractional order impedance control are both given out.

关键词： Dynamic interaction Compliance control Fractional order Impedance control Performance analysis

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FFPA-Net: Efficient Feature Fusion with Projection Awareness for 3D Object Detection

arXiv

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arXiv 2022年

作者： Jiang, Chaokang Wang, Guangming Wu, Jinxing Miao, Yanzi Wang, Hesheng Engineering Research Center of Intelligent Control for Underground Space Ministry of Education School of Information and Control Engineering Advanced Robotics Research Center China University of Mining and Technology Xuzhou221116 China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China The Department of Engineering Mechanics Shanghai Jiao Tong University Shanghai200240 China

Promising complementarity exists between the texture features of color images and the geometric information of LiDAR point clouds. However, there still present many challenges for efficient and robust feature fusion in the field of 3D object detection. In this paper, first, unstructured 3D point clouds are filled in the 2D plane and 3D point cloud features are extracted faster using projection-aware convolution layers. Further, the corresponding indexes between different sensor signals are established in advance in the data preprocessing, which enables faster cross-modal feature fusion. To address LiDAR points and image pixels misalignment problems, two new plug- and-play fusion modules, LiCamFuse and BiLiCamFuse, are proposed. In LiCamFuse, soft query weights with perceiving the Euclidean distance of bimodal features are proposed. In BiLiCamFuse, the fusion module with dual attention is proposed to deeply correlate the geometric and textural features of the scene. The quantitative results on the KITTI dataset demonstrate that the proposed method achieves better feature-level fusion. In addition, the proposed network shows a shorter running time compared to existing methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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Dynamics of opinions with bounded confidence in social cliques: Emergence of fluctuations

arXiv

引用

arXiv 2021年

作者： Zhang, Jiangbo Yuan, Deming Wang, Lei Altafini, Claudio Shi, Guodong School of Sciences Southwest Petroleum University Chengdu China Research School of Engineering The Australian National University CanberraACT Australia School of Automation Nanjing University of Science and Technology Nanjing China Australian Center for Field Robotics The University of Sydney SydneyNSW2008 Australia Division of Automatic Control Department of Electrical Engineering Linköping University LinköpingSE-58183 Sweden Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney SydneyNSW2008 Australia

In this paper, we study the evolution of opinions over social networks with bounded confidence in social cliques. Node initial opinions are independently and identically distributed;at each time step, nodes review the average opinions of a randomly selected local clique. The clique averages may represent local group pressures on peers. Then nodes update their opinions under bounded confidence: only when the difference between an agent individual opinion and the corresponding local clique pressure is below a threshold, this agent opinion is updated according to the DeGroot rule as a weighted average of the two values. As a result, this opinion dynamics is a generalization of the classical Deffuant-Weisbuch model in which only pairwise interactions take place. First of all, we prove conditions under which all node opinions converge to finite limits. We show that in the limits the event that all nodes achieve a consensus, and the event that all nodes achieve pairwise distinct limits, i.e., social disagreements, are both nontrivial events. Next, we show that opinion fluctuations may take place in the sense that at least one agent in the network fails to hold a converging opinion trajectory. In fact, we prove that this fluctuation event happens with a strictly positive probability, and also constructively present an initial value event under which the fluctuation event arises with probability one. These results add to the understanding of the role of bounded confidence in social opinion dynamics, and the possibility of fluctuation reveals that bringing in cliques in Deffuant-Weisbuch models have fundamentally changed the behavior of such opinion dynamical processes. © 2021, CC BY-NC-ND.

关键词： Dynamics

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A Survey of Robot Manipulation in Contact

arXiv

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arXiv 2021年

作者： Suomalainen, Markku Karayiannidis, Yiannis Kyrki, Ville Center of Ubiquitous Computing Faculty of Information Technology and Electrical Engineering University of Oulu Finland Systems and Control Department of Electrical Engineering Chalmers University of Technology Gothenburg Sweden Intelligent Robotics research group Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Helsinki Finland

In this survey, we present the current status on robots performing manipulation tasks that require varying contact with the environment, such that the robot must either implicitly or explicitly control the contact force with the environment to complete the task. Robots can perform more and more manipulation tasks that are still done by humans, and there is a growing number of publications on the topics of 1) performing tasks that always require contact and 2) mitigating uncertainty by leveraging the environment in tasks that, under perfect information, could be performed without contact. The recent trends have seen robots perform tasks earlier left for humans, such as massage, and in the classical tasks, such as peg-in-hole, there is a more efficient generalization to other similar tasks, better error tolerance, and faster planning or learning of the tasks. Thus, in this survey we cover the current stage of robots performing such tasks, starting from surveying all the different in-contact tasks robots can perform, observing how these tasks are controlled and represented, and finally presenting the learning and planning of the skills required to complete these tasks. © 2021, CC BY.

关键词： Surveys

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Hybrid Vision/Force Control for Interaction with the Bottle-like Object

Hybrid Vision/Force Control for Interaction with the Bottle-...

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IEEE International Conference on robotics and automation (ICRA)

作者： Lijun Han Hesheng Wang Weidong Chen Jingchuan Wang Jianjun Yuan Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Shanghai Robotics Institute School of Mechatronic Engineering and Automation Shanghai University Shanghai China

This study proposes a hybrid vision/force control scheme for interaction with the inner surface of the bottle-like object. Based on the geometry of the object, a new generalized constraint called the bottleneck (BN) constraint is proposed, which ensures the tool passes through a fixed 3-D region and avoid collisions with the boundary of the region. To realize the hybrid vision/force control under the BN constraint, a novel dynamic controller is designed inspired by the hierarchical operational space, which can complete the different tasks defined in the decoupled subspace. To enhance the robustness of the algorithm, we develop a data-driven method and an adaptive method to estimate the Jacobian matrix online in force space and image space, respectively. The asymptotic stability of the closed-loop system is rigorously proved by the Lyapunov theory. Experiments are conducted to validate the performance of the proposed method.

关键词： Jacobian matrices Geometry Heuristic algorithms Robot vision systems Force Aerospace electronics Tools

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Multiple Functions Printed Circuit Triboelectric Nanogenerators-Based Metauniverse Sport Interactive System

SSRN

引用

SSRN 2023年

作者： Zhu, Yongsheng Zhao, Tianming Sun, Fengxin Jia, Changjun Ye, Hui Jiang, Yawei Wang, Kuo Huang, Chaorui Xie, Yannan Mao, Yupeng Physical Education Department Northeastern University Shenyang110819 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Science Shenyang China Key Laboratory for Organic Electronics and Information Displays Institute of Advanced Materials Jiangsu Key Laboratory for Biosensors Jiangsu National Synergetic Innovation Center for Advanced Materials Nanjing University of Posts and Telecommunications Jiangsu Nanjing China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China College of Information Science and Engineering Northeastern University Shenyang China School of Strength and Conditioning Training Beijing Sport University Beijing China

Metauniverse is a future society based on the convergence of the physical and the digital world, which is fully indebted to the sophisticated human-machine interface (HMI) to connect the two worlds. In this study, a metauniverse sport interactive system based on TENG has been developed, realizing interaction with human beings, devices, and the internet in real-time. This metauniverse sport interactive system is consistent with a self-powered anaerobic power meter (APM), a wireless transmission module, personalized data analysis based on the professional Wingate anaerobic power test method, and an augmented reality (AR) application. Self-powered APM is integrated with the axles of the bicycle to monitor human exercises, such as peak power (PP), mean power (MP), and fatigue index (FI). The data is transmitted to the cloud by the wireless transmission module and users can freely explore the metauniverse through the AR application. As a result of machine learning, the professional Wingate anaerobic power test method can not only reflect the anaerobic capacity, but also be used for athlete selection. This work provides a new approach to online competitions, sport training, and athlete selection and provides a new way to build metauniverse. © 2023, The Authors. All rights reserved.

关键词： Human computer interaction

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Deep Learning for Visual SLAM in Transportation robotics:A review

引用

Transportation Safety and Environment 2019年第3期1卷 177-184页

作者： Chao Duan Steffen Junginger Jiahao Huang Kairong Jin Kerstin Thurow Institute of Artificial Intelligence&Robotics(IAIR) School of Traffic&Transportation EngineeringCentral South University410075 China Institute of Automation University Rostock18119 Germany 3Center for Life Science AutomationUniversity of Rostock18119 Germany

Visual SLAM(Simultaneously Localization and Mapping)is a solution to achieve localization and mapping of robots *** achievements have been made during the past decades,geography-based methods are becoming more and more successful in dealing with static ***,they still cannot handle a challenging *** the great achievements of deep learning methods in the field of computer vision,there is a trend of applying deep learning methods to visual *** this paper,the latest research progress of deep learning applied to the field of visual SLAM is *** outstanding research results of deep learning visual odometry and deep learning loop closure detect are ***,future development directions of visual SLAM based on deep learning is prospected.

关键词： deep learning visual SLAM transportation robotics mobile robots

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Composite Adaptive Control for Anti-Unwinding Attitude Maneuvers: An Exponential Stability Result without Persistent Excitation

arXiv

引用

arXiv 2021年

作者： Shao, Xiaodong Hu, Qinglei Li, Daochun Shi, Yang Yi, Bowen School of Aeronautic Science and Engineering Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Beihang University Beijing100191 China Department of Mechanical Engineering University of Victoria VictoriaBCV8N 3P6 Canada Australian Center for Field Robotics University of Sydney SydneyNSW2006 Australia

This paper provides an exponential stability result for the adaptive anti-unwinding attitude tracking control problem of a rigid body with uncertain but constant inertia parameters, without requiring the satisfaction of persistent excitation (PE) condition. Specifically, a composite immersion and invariance (I&I) adaptive controller is derived by integrating a prediction-error-driven learning law into the dynamically scaled I&I adaptive control framework, wherein we modify the scaling factor so that the algorithm design does not involve any dynamic gains. To avoid the unwinding problem, a barrier function is introduced as the attitude error function, along with the tactful establishment of two crucial algebra properties for exponential stability analysis. The regressor filtering method is adopted in combination with the dynamic regressor extension and mixing (DREM) procedure to acquire the prediction error using only easily obtainable signals. In particular, aiding by a constructive liner time-varying filter, the scalar regressor of DREM is extended to generate a new exciting counterpart. In this way, the derived controller is shown to permit closed-loop exponential stability without PE, in the sense that both output-tracking and parameter estimation errors exponentially converge to zero. Further, the composite learning law is augmented with a power term to achieve synchronized finite/fixed-time parameter convergence. Numerical simulations are performed to verify the theoretical findings. © 2021, CC BY.

关键词： Navigation

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