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2019 IEEE International Conference on robotics and Biomimetics, ROBIO 2019

作者： Zhang, Yinlong An, Haibo Ding, Xiaojian Liang, Wei Yuan, Mingze Ji, Chunyang Tan, Jindong Shenyang Institute of Automation Guangzhou Chinese Academy of Sciences Guangzhou511548 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Fifth Electronic Instituteof MIIT Guangzhou510610 China Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee KonxvilleTN37996 United States

ISBN: (纸本)9781728163215

Reliable fault detection of rotate vector (RV) reducer is of paramount importance for the long-term maintenance of high-precision industrial robots. This paper proposes a Hidden Markov Model (HMM) based RV reducer fault detection using Acoustic Emission (AE) measurements. Compared with the conventional faults from the common rotating machinery (such as bearings and gears), the fault from the RV reducer is more complicated and undetectable due to its inherent inline and two-stage meshing structure. To this end, this work modifies the HMM model by taking into account not only the current observations and previous states, but also the subsequent series of observations within the posteriori probability framework. Through this way, the random and unknown disturbance, which is common in the industrial scenarios, could be reduced. Besides, the HMM is also applied to separate the AE signal bulks within one cycle that has 39 subcycles, which is a critical step for AE signal pre-processings. The proposed method has been evaluated on our collected AE signal dataset from the RV reducer in the industrial robotic platform. The experimental results and analysis validate that the proposed HMM based RV Reducer fault detection model can reliably and accurately detect reducer faults. © 2019 IEEE.

关键词： Hidden Markov models

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Anchor-based spatio-temporal attention 3D convolutional networks for dynamic 3D point cloud sequences

arXiv

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arXiv 2020年

作者： Wang, Guangming Chen, Muyao Liu, Hanwen Yang, Yehui Liu, Zhe Wang, Hesheng The Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge

With the rapid development of measurwement technology, LiDAR and depth cameras are widely used in the perception of the 3D environment. Recent learning based methods for robot perception most focus on the image or video, but deep learning methods for dynamic 3D point cloud sequences are underexplored. Therefore, developing efficient and accurate perception method compatible with these advanced instruments is pivotal to autonomous driving and service robots. An Anchor-based Spatio-Temporal Attention 3D Convolution operation (ASTA3DConv) is proposed in this paper to process dynamic 3D point cloud sequences. The proposed convolution operation builds a regular receptive field around each point by setting several virtual anchors around each point. The features of neighborhood points are firstly aggregated to each anchor based on the spatio-temporal attention mechanism. Then, anchor-based 3D convolution is adopted to aggregate these anchors' features to the core points. The proposed method makes better use of the structured information within the local region and learns spatio-temporal embedding features from dynamic 3D point cloud sequences. Anchor-based Spatio-Temporal Attention 3D Convolutional Neural Networks (ASTA3DCNNs) are built for classification and segmentation tasks based on the proposed ASTA3DConv and evaluated on action recognition and semantic segmentation tasks. The experiments and ablation studies on MSRAction3D and Synthia datasets demonstrate the superior performance and effectiveness of our method for dynamic 3D point cloud sequences. Our method achieves the state-of-the-art performance among the methods with dynamic 3D point cloud sequences as input on MSRAction3D and Synthia datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

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Simultaneous state and parameter estimation: The role of sensitivity analysis

arXiv

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arXiv 2020年

作者： Liu, Jianbang Gnanasekar, Aristarchus Zhang, Yi Bo, Song Liu, Jinfeng Hu, Jingtao Zou, Tao Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institute for Robotics & Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Department of Chemical & Materials Engineering University of Alberta EdmontonABT6G 1H9 Canada Key Laboratory of Energy Thermal Conversion & Control Southeast University Nanjing210096 China School of Mechanical and Electrical Engineering Guangzhou University Guangzhou510006 China

State and parameter estimation is essential for process monitoring and control. Observability plays an important role in both state and parameter estimation. In simultaneous state and parameter estimation, the parameters are often augmented as extra states of the original system. When the augmented system is observable, various existing state estimation approaches may be used to estimate the states and parameters simultaneously. However, when the augmented system is not observable, how we should proceed to maximally extract the information contained in the measured outputs is not clear. This paper concerns about simultaneous state and parameter estimation when the augmented system is not fully observable. Specifically, we first show how sensitivity analysis is related to observability of a dynamical system, and then illustrate how it may be used to select variables for simultaneous estimation. We also propose a moving horizon state estimation (MHE) design that can use the variable selection results in a natural way. Extensive simulations are carried out to show the efficiency of the proposed approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Sensitivity analysis

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Applying the Results of Hydrodynamic and Heat Transfer Processes Research in 3D Nasal Cavity Models for Revealing Predisposing Towards Respiratory Diseases at Extreme Conditions of the Arctic

Applying the Results of Hydrodynamic and Heat Transfer Proce...

引用

International Multi-Conference on Industrial Engineering and Modern Technologies (FarEastCon)

作者： G. Lukyanov A. Rassadina R. Neronov A.A. Stepanov R.Z. Alexeev The Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russia “Modern Medical Technologies” Clinic Saint-Petersburg Russia Larionov Institute of Physical and Technical Problems of the North SB RAS Yakutsk Russian Federation Laboratory of Immunological researches Yakut Science Centre of Complex Medical Problems Medical Institute M. K. Ammosov North-Eastern Federal University Yakutsk Russia

It has been found that the shape of nasal cavity influences to the hydrodynamics and heat transfer in the respiratory system which at the extreme environmental conditions of the Arctic can be a reason of predispositio... 详细信息

ISBN: (数字)9781728169514

ISBN: (纸本)9781728169521

关键词： Nose Atmospheric modeling Shape Numerical models Solid modeling Indexes Arctic

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An Abnormal State Forecasting Method for Substation Equipment based on Improved LSTM

An Abnormal State Forecasting Method for Substation Equipmen...

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2019 IEEE Sustainable Power and Energy Conference, iSPEC 2019

作者： Li, Tong Yu, Shimao Song, Chunhe Yu, Tongwei Zeng, Peng Shen, Li State Grid Liaoning Electric Power Co. Ltd. Liaoning Electric Power Research Institute Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China State Grid Liaoning Electric Power Co. Ltd. Shenyang China

ISBN: (纸本)9781728149301

Abnormal state accumulation over a long period will cause an electrical equipment fault. Therefore, Substation equipment state forecasting plays a vital role in smart grids. Fault forecasting method based on deep learning have been put forward in recent years, but they have deficiencies dealing with temporal features. This paper proposes an abnormal forecasting method for substation equipment based on improved LSTM, and temporal features of power equipment fault can be extracted effectively for a long-time span. The method reads secondary equipment information through SCADA system, then extracts feature to carry out deep learning training. In this paper, RNN and LSTM are firstly compared, and then the structure and algorithm of improved LSTM are given. This method increases coupling between forget gate and cell state compared with the standard LSTM structure, so as to make better use of information at previous moment. Meanwhile problems of network training and overfitting are discussed. Experiments are conducted to demonstrate that improved LSTM is capable of forecasting accurately the complex electric equipment state with a long forecasting horizon. The accuracy of abnormal state forecasting can reach more than 93% which has a better performance compared with many other methods. © 2019 IEEE.

关键词： SCADA systems

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Design and Characterization of a 1-axis Compact Torque Sensor for a Collaborative Robot Arm

Design and Characterization of a 1-axis Compact Torque Senso...

引用

International Conference on Information and Automation for Sustainability (ICIAfS)

作者： Thushara Sandakalum Suranga Suraji Indika Weerasekara Thilina Lalitharatne Damith Chathuranga Robotics and Control Systems Laboratory University of Moratuwa Moratuwa Sri Lanka

The paper proposes a compact torque sensor with a support structure to minimize crosstalk which can be used in a collaborative robot arm. In the torque sensor, the torque is measured by sensing the deformation of an elastic body using strain gauges. The deformable body design was carried out by an iterative process of design modifications and FEA (Finite Element Analysis) to come up with a design which satisfied all the design requirements. Further design modifications and FEA was carried out to identify and finalize the strain gauge mounting locations on the deformable body. The signal from the strain gauges are amplified, processed and then transmitted to the robot controller using serial communication. The support structure for the torque sensor includes a bearing which minimizes the crosstalk applied on the torque sensor increasing the sensor accuracy. Experiments were carried out to characterize the torque sensor for static torque conditions and to identify the linearity of the proposed sensor. The results of the simulation analysis and experiment results suggest the effectiveness of the proposed torqued sensor.

关键词： Robot sensing systems Torque Strain measurement Strain Crosstalk Safety

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Engineering Software for a Mobile Robot Motion control System

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IOP Conference Series: Materials Science and Engineering 2020年第1期714卷

作者： Igor Ryadchikov Evgeny Nikulchev Alexander Gusev Semyon Sechenev Alexey Prutskiy Laboratory of Robotics and Mechatronics Kuban State University Krasnodar Russian Federation Department of Control and Modelling Systems MIREA – Russian Technological University Moscow Russian Federation

The paper centres round the problem of the engineering a motion control system for a mobile robot based on the effective selection of software components with respect to the numerical criterion proposed by the authors. The data for the selection process comes out the reproducible experiments with the sets of alternative components in a Gazebo virtual infrastructure simulating the real robot operating conditions. The genetic algorithm is used to reduce the number of experiments with unpromising sets of software components. The methodology proposed by the authors is applied to the real task of engineering a motion control system for a non-anthropomorphic mobile robot. The virtual infrastructure and genetic algorithm parameters are provided as well as the physical model of the robot for that task. To calculate the integral quality criterion proposed in the paper, 4 partial quality criteria were measured in the experiments with different software components. The motion process of the physical robot with the selected software components is shown.

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A novel hierarchical control strategy for biped robot walking on uneven terrain

A novel hierarchical control strategy for biped robot walkin...

引用

IEEE-RAS International Conference on Humanoid Robots

作者： Chencheng Dong Xuechao Chen Zhangguo Yu Zelin Huang Qingqing Li Qinqin Zhou Qiang Huang School of Mechantronical Engineering Beijing Institute of Technology Beijing China Bionic robot mechanism perception and control laboratory Beijing China Beijing Advanced Innovation Center for Intelligent Robotics and Systems Beijing Institute of Technology Beijing China

ISBN: (数字)9781538676301

ISBN: (纸本)9781538676318

When position-controlled biped robot is blind walking on a uneven terrain at a high speed, huge foot contact impacts will be generated. However, traditional admitance control can't absorb the impact and stabilize the robot due to its slow response and Incompleteness. In this paper, we propose a control strategy including respectively designed swing leg control and support leg control with a new approach of control transition. For Swing leg control, double spring damping model is presented to optimize the admitance controller with faster response and better robustness, and a active foot height controller is also proposed to reduce the impact further. On the other hand, the control transition is accomplished by using a bionic fuzzy control. As a result, the foot contact impact can be reduced and the robot can blind walk fast on uneven terrain. Finally, the validity of the proposed strategy is confirmed by the simulation.

关键词： Legged locomotion Foot Trajectory Springs Adaptation models Robot kinematics

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An Early Stage Researcher's Primer on systems Medicine Terminology

Network and Systems Medicine

引用

Network and systems Medicine 2021年第1期4卷 2-50页

作者： Zanin, Massimiliano Aitya, Nadim A.A. Basilio, José Baumbach, Jan Benis, Arriel Behera, Chandan K. Bucholc, Magda Castiglione, Filippo Chouvarda, Ioanna Comte, Blandine Dao, Tien-Tuan Ding, Xuemei Pujos-Guillot, Estelle Filipovic, Nenad Finn, David P. Glass, David H. Harel, Nissim Iesmantas, Tomas Ivanoska, Ilinka Joshi, Alok Boudjeltia, Karim Zouaoui Kaoui, Badr Kaur, Daman Maguire, Liam P. McClean, Paula L. McCombe, Niamh De Miranda, João Luís Moisescu, Mihnea Alexandru Pappalardo, Francesco Polster, Annikka Prasad, Girijesh Rozman, Damjana Sacala, Ioan Sanchez-Bornot, Jose M. Schmid, Johannes A. Sharp, Trevor Solé-Casals, Jordi Spiwok, Vojtěch Spyrou, George M. Stalidzans, Egils Stres, Blaa Sustersic, Tijana Symeonidis, Ioannis Tieri, Paolo Todd, Stephen Van Steen, Kristel Veneva, Milena Wang, Da-Hui Wang, Haiying Wang, Hui Watterson, Steven Wong-Lin, Kongfatt Yang, Su Zou, Xin Schmidt, Harald H.H.W. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Ulster United Kingdom Center for Physiology and Pharmacology Institute of Vascular Biology and Thrombosis Research Medical University of Vienna Vienna Austria TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany Holon Israel CNR National Research Council IAC Institute for Applied Computing Rome Italy Lab of Computing Medical Informatics and Biomedical Imaging Technologies School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece Université Clermont Auvergne INRAE UNH Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Clermont-Ferrand France Université de Technologie de Compiègne Compiègne France Labex MS2T Control of Technological Systems-of-Systems CNRS and Université de Technologie de Compiègne Compiègne France Faculty of Engineering University of Kragujevac Kragujevac Serbia Kragujevac Serbia Steinbeis Advanced Risk Technologies Institute Doo Kragujevac Kragujevac Serbia Pharmacology and Therapeutics School of Medicine Galway Neuroscience Centre National University of Ireland Galway Ireland School of Computing Ulster University Ulster United Kingdom Holon Israel Department of Mathematics and Natural Sciences Kaunas University of Technology Kaunas Lithuania Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Skopje Macedonia Medicine Faculty Université Libre de Bruxelles CHU de Charleroi Charleroi Belgium Northern Ireland Centre for Stratified Medicine Biomedical Sciences Research Institute Ulster University Ulster United Kingdom Escola Superior de Tecnologia e Gestão Instituto Politécnico de Portalegre Portalegre Portugal Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Faculty of Automatic Control and Computers University Politehnica of B

Background: systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic. © Massimiliano Zanin et al., 2021;Published by Mary Ann Liebert, Inc. 2021.

关键词： Semantics

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Design of a control Platform for Mobile Robot with SSVEP-BCI System

Design of a Control Platform for Mobile Robot with SSVEP-BCI...

引用

IEEE Conference on Cybernetics and Intelligent systems

作者： Yang Liu Xinyang Li Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Hammersmith Campus Imperial College London National Heart and Lung Institute London Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728134581

ISBN: (纸本)9781728134598

This paper introduces a control platform based on brain-computer interface(BCI) for the mobile robot. The proposed platform consists of three parts: Path Planning, SSVEP-BCI and Mobile Robot control. The path planning part aims to seek an optimal path out from the starting point to the target point, which is denoted as A* algorithm in this work. The found path is shown to the user who determines the actual movement direction using SSVEP-BCI. The signal is sent to the mobile robot to control the movement of the robot. In the BCI part, the collected EEG signals are analyzed with the CCA method to obtain the homologous control signals. The mobile robot is required to complete the movement from the initial point to the destination without collision. The platform is evaluated with an off-line experiment with 4 subjects and the off-line analysis shows the feasibility of the proposed platform.

关键词： Mobile robots Visualization Electroencephalography Path planning Heuristic algorithms Frequency modulation

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