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

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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

Recognition of patient groups with sleep related disorders using bio-signal processing and deep learning

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arXiv 2021年

作者： Jarchi, Delaram Andreu-Perez, Javier Kiani, Mehrin Vysata, Oldrich Kuchynka, Jiri Prochazka, Ales Sanei, Saeid Smart Health Technologies Group School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom Embedded and Intelligent Systems Laboratory School of Computer Science and Electronics University of Essex ColchesterCO4 3SQ United Kingdom Department of Computing and Control Engineering University of Chemistry and Technology in Prague Prague 6166 28 Czech Republic Department of Neurology Faculty of Medicine in Hradec Králové Charles University Hradec Králové500 05 Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6160 00 Czech Republic School of Science and Technology Nottingham Trent University NottinghamNG11 8NS United Kingdom

Accurately diagnosing sleep disorders is essential for clinical assessments and treatments. Polysomnography (PSG) has long been used for detection of various sleep disorders. In this research, electrocardiography (ECG) and electromayography (EMG) have been used for recognition of breathing and movement-related sleep disorders. Bio-signal processing has been performed by extracting EMG features exploiting entropy and statistical moments, in addition to developing an iterative pulse peak detection algorithm using synchrosqueezed wavelet transform (SSWT) for reliable extraction of heart rate and breathing-related features from ECG. A deep learning framework has been designed to incorporate EMG and ECG features. The framework has been used to classify four groups: healthy subjects, patients with obstructive sleep apnea (OSA), patients with restless leg syndrome (RLS) and patients with both OSA and RLS. The proposed deep learning framework produced a mean accuracy of 72% and weighted F1 score of 0.57 across subjects for our formulated four-class problem. © 2021, CC BY-NC-ND.

关键词： Wavelet transforms

Authentication Technology in Industrial Control System Based on Identity Password

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Authentication Technology in Industrial Control System Based...

第三十九届中国控制会议

作者： Luyao Yang Wenli Shang Chunyu Chen Tianyu Wang Zhoubin Liu Shenyang Institute of Automation Chinese Academy of Sciences School of Information Science and Engineering Northeastern University University of Chinese Academy of Sciences Institute of Robotics and Intelligent Manufacturing Innovation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Electric Power Research Institute State Grid Zhejiang Electric Power Co.Ltd.

Aiming at the current lack of certification capability in domestic industrial control systems, an industrial control system authentication scheme based on identity cryptography algorithm is proposed. When authenticating between control system devices, the scheme integrates the identity-based digital signature algorithm into the SSL/TLS handshake protocol to complete identity authentication between the engineering station and the trusted PLC. At the same time, when the connection is established for the first time between devices, the connection authentication is selected by the challenge/response based method. The authentication technology based on the identity cryptographic algorithm no longer requires the existence of a public key certificate. This eliminates the need to revoke, store, and issue certificates, simplifies the certification process and reduces the amount of computation required by the authentication process. At the same time, the improved handshake protocol is universal in industrial control systems. The authentication technology based on the identity and password algorithm no longer requires the existence of a public key certificate, eliminating the need for certificate revocation, storage, and issuance, simplifying authentication steps, and reducing system maintenance. Finally, by establishing a test environment, the improved handshake protocol is implemented, and the feasibility of the authentication scheme is verified and analyzed.

关键词： Industrial control security digital signature identity authentication SSL/TLS handshake protocol

Roadmap for Animate Matter

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arXiv 2024年

作者： Volpe, Giorgio Araújo, Nuno A.M. Guix, Maria Miodownik, Mark Martin, Nicolas Alvarez, Laura Simmchen, Juliane Leonardo, Roberto Di Pellicciotta, Nicola Martinet, Quentin Palacci, Jérémie Ng, Wai Kit Saxena, Dhruv Sapienza, Riccardo Nadine, Sara Mano, João F. Mahdavi, Reza Adiels, Caroline Beck Forth, Joe Santangelo, Christian Palagi, Stefano Seok, Ji Min Webster-Wood, Victoria A. Wang, Shuhong Yao, Lining Aghakhani, Amirreza Barois, Thomas Kellay, Hamid Coulais, Corentin van Hecke, Martin Pierce, Christopher J. Wang, Tianyu Chong, Baxi Goldman, Daniel I. Reina, Andreagiovanni Trianni, Vito Volpe, Giovanni Beckett, Richard Nair, Sean P. Armstrong, Rachel Department of Chemistry University College London 20 Gordon Street LondonWC1H 0AJ United Kingdom Departamento de Física Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal Centro de Física Teórica e Computacional Faculdade de Ciências Universidade de Lisboa Lisboa1749-016 Portugal Department of Materials Science and Physical Chemistry Institute of Theoretical and Computational Chemistry University of Barcelona Barcelona Catalonia08028 Spain Department of Mechanical Engineering University College London London United Kingdom University of Bordeaux CNRS Centre de Recherche Paul Pascal UMR 5031 115 Avenue du Dr. Albert Schweitzer Pessac33600 France Pure and Applied Chemistry University of Strathclyde United Kingdom Department of Physics "Sapienza" University of Rome Rome00185 Italy NANOTEC-CNR Institute of Nanotechnology Soft and Living Matter Laboratory Rome00185 Italy Klosterneuburg Austria Blackett Laboratory Department of Physics Imperial College London London United Kingdom CICECO - Aveiro Institute of Materials Department of Chemistry University of Aveiro Campus Universitário de Santiago Aveiro3810-193 Portugal Department of Physics University of Gothenburg GothenburgSE-41296 Sweden Department of Physics University of Liverpool Crown Street LiverpoolL69 7ZD United Kingdom Department of Chemistry University of Liverpool Oxford Street LiverpoolL69 7ZE United Kingdom Physics Department Syracuse University SyracuseNY13244 United States The BioRobotics Institute Department of Excellence in Robotics & AI Sant'Anna School of Advanced Studies Tuscany Pisa56025 Italy Department of Mechanical Engineering Carnegie Mellon University United States Department of Mechanical Engineering Department of Biomedical Engineering The Robotics Institute Carnegie Mellon University United States Morphing Matter Lab Mechanical Engineering UC Berkeley United States Zhejiang University China Institute of Biomaterials and Biomolecular

Humanity has long sought inspiration from nature to innovate materials and devices. As science advances, nature-inspired materials are becoming part of our lives. Animate materials, characterized by their activity, adaptability, and autonomy, emulate properties of living systems. While only biological materials fully embody these principles, artificial versions are advancing rapidly, promising transformative impacts across various sectors. This roadmap presents authoritative perspectives on animate materials across different disciplines and scales, highlighting their interdisciplinary nature and potential applications in diverse fields including nanotechnology, robotics and the built environment. It underscores the need for concerted efforts to address shared challenges such as complexity management, scalability, evolvability, interdisciplinary collaboration, and ethical and environmental considerations. The framework defined by classifying materials based on their level of animacy can guide this emerging field encouraging cooperation and responsible development. By unravelling the mysteries of living matter and leveraging its principles, we can design materials and systems that will transform our world in a more sustainable manner. Copyright © 2024, The Authors. All rights reserved.

关键词： Biotic

First-principles prediction of anisotropic superconductivity in the nodal-line semi-metal TlTaSe 2

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Materials Today Quantum

Materials Today Quantum 2025年 6卷

作者： Mukhtar Lawan Adam Ibrahim Buba Garba Sulaiman Muhammad Gana Bala Ismail Adamu Abba Alhaji Bala Abdulsalam Aji Suleiman Ahmad Hamisu Tijjani Hassan Darma Auwal Musa Abdulkadir S. Gidado School of Material Science and Engineering Anhui University Hefei 230601 People's Republic of China Information Materials and Intelligent Sensing Laboratory of Anhui Province Leibniz International Joint Research Center of Materials Sciences of Anhui Province Institutes of Physical Science and Information Technology Anhui University Hefei People's Republic of China Physics Department Bayero University Kano 700231 Nigeria Sorbonne Université CNRS IMPMC 4 Place Jussieu Paris 75252 France Department of Physics Federal University Gashua Gashua 671106 Nigeria Physics Department Federal University Dutse Jigawa 720101 Nigeria Aviation and Aeronautic Center for Advanced Integrated Robotics and Autonomous Systems Engineering and Technology University of South Africa Johannesburg 1710 South Africa Institute of Materials Science and Nanotechnology Bilkent University UNAM Ankara 06800 Türkiye Department of Engineering Fundamental Sciences Sivas University of Science and Technology Sivas 58000 Türkiye Physics Department King Abdulaziz University Jedda 21589 Saudi Arabia

Recent advances in topological quantum materials have spurred significant interest in exploring superconductors that also host nontrivial band topology, as these materials can serve as platforms for novel electronic phases and quantum technologies. TlTaSe 2 is one such non-centrosymmetric, quasi-two-dimensional semimetal with nodal-line topological features protected by mirror-reflection symmetry. In this study, we theoretically predict its superconducting properties using first-principles anisotropic Migdal–Eliashberg theory. Our results indicate that the states at the Fermi, are primarily Ta 5d and Tl 6p orbitals. Thus, exhibiting a multiband electronic structure. Notably, from our calculations, we find two distinct superconducting gaps of 2.15 meV and 4.5 meV on different Fermi surface sheets, arising from strongly anisotropic electron-phonon interactions predominantly involving in-plane vibrations of the Ta and Tl atoms. Using the Allen–Dynes-modified McMillan formula with a Coulomb pseudopotential μ* = 0.16, we predict a superconducting transition temperature Tc of 6.67 K. These findings underscore the significance of TlTaSe 2 as a candidate for topological superconductivity and provide insights into how the interplay between anisotropy, electron-phonon coupling, and nontrivial band topology can be explored for quantum computing and spintronics applications.

关键词： Quantum materials TlTaSe 2 Anisotropic superconducting gaps Electron-phonon coupling Nodal-line semimetal

Position Tracking for Continuum Robots with Joint Limit Constraints

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Position Tracking for Continuum Robots with Joint Limit Cons...

International Conference on Unmanned systems and Artificial Intelligence

作者： Dengliang Lin Xin Dong Chenguang Yang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Nottingham University Nottingham UK Bristol Robotics Laboratory University of the West of England Bristol UK

ISBN: (数字)9781728158594

ISBN: (纸本)9781728158600

This paper presents a novel tip-following approach for real-time position tracking and avoiding obstacle of continuum robots with joint limit constraints. This type of hyper-redundant robot, which is more flexible and compliant to explore in complex and constrained environments, such as in pipeline or narrow entrance. However, tradictional method based on inverse kinematic model is difficult to control the end-effector of continuum robot to avoid abstcales in the constrained circumstance. Therefore a new tip-following method based on forward kinematic model is proposed to control the robot and make it inspect the environment. For the method, we use nonliner progamming approach to solve the optimization problem, which is used to find minimum of constrained nonlinear objective function to ensure that the end-effector of the robot follow the desired position with minimal error. In this paper, we employ a 24 DoF continuum robot with continuous backbone and compliant joint to the simulation, and it is testified that the proposed approch can ensure joint limit avoidance, track the end postion in real time and minimize the tracking errors.

关键词： hyper-redundant robots obstacle avoidance tip-following control kinematic model kinematics Robot Redundant robot Obstacle avoidance Continuum Location tracking Collision avoidance Joints end effectors

Attitude observers aided by implicit measurements of the Earth angular velocity

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Attitude observers aided by implicit measurements of the Ear...

IEEE Conference on Decision and Control

作者： Joel Reis Carlos Silvestre Pedro Batista Paulo Oliveira Faculty of Science and Technology University of Macau Taipa Macao China Instituto Superior Técnico Universidade de Lisboa Portugal Institute for Systems and Robotics LARSyS Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal LAETA — Associated Laboratory for Energy Transports and Aeronautics IDMEC — Institute of Mechanical Engineering Instituto Superior Técnico Universidade deLisboa Lisboa Portugal

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

In this tutorial, a new class of attitude estimation solutions is presented to determine the orientation of a robotic platform resorting only to a set of triaxial gyroscopes and an additional measurement of a constant inertial vector. This approach poses a significant advantage in terms of setup design and reduced mission costs since only one inertial measurement is required, in contrast with existing solutions that require at least two of these. Pertinent examples of viable applications include navigation of submarines or large ships, assisting autonomous robots in precise maneuvers, inertial platform stabilization, etc. The novelty of the solutions proposed herein exploit the well-known inertial information about the Earth's angular velocity by using high-grade gyroscopes that are sensitive to the planet's spin. Experimental results are presented to demonstrate the good performance achieved by the algorithms.

关键词： Observers Extraterrestrial measurements Earth Robot sensing systems Angular velocity Tutorials Gyroscopes

Semi-supervised medical image classification with relation-driven self-ensembling model

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arXiv 2020年

作者： Liu, Quande Yu, Lequan Luo, Luyang Dou, Qi Heng, Pheng Ann Department of Computer Science and Engineering Chinese University of Hong Kong Department of Radiation Oncology Stanford University StanfordCA94305 United States T Stone Robotics Institute Chinese University of Hong Kong Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

Training deep neural networks usually requires a large amount of labeled data to obtain good performance. However, in medical image analysis, obtaining high-quality labels for the data is laborious and expensive, as accurately annotating medical images demands expertise knowledge of the clinicians. In this paper, we present a novel relation-driven semi-supervised framework for medical image classification. It is a consistency-based method which exploits the unlabeled data by encouraging the prediction consistency of given input under perturbations, and leverages a self-ensembling model to produce high-quality consistency targets for the unlabeled data. Considering that human diagnosis often refers to previous analogous cases to make reliable decisions, we introduce a novel sample relation consistency (SRC) paradigm to effectively exploit unlabeled data by modeling the relationship information among different samples. Superior to existing consistency-based methods which simply enforce consistency of individual predictions, our framework explicitly enforces the consistency of semantic relation among different samples under perturbations, encouraging the model to explore extra semantic information from unlabeled data. We have conducted extensive experiments to evaluate our method on two public benchmark medical image classification datasets, i.e., skin lesion diagnosis with ISIC 2018 challenge and thorax disease classification with ChestX-ray14. Our method outperforms many state-of-the-art semi-supervised learning methods on both single-label and multi-label image classification scenarios. Copyright © 2020, The Authors. All rights reserved.

关键词： Image classification

A spatial motion control to transfer an object between a pair of air jet 15

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A spatial motion control to transfer an object between a pai...

15th International Conference on Informatics in Control, Automation and robotics, ICINCO 2018

作者： Yoshinaga, Kazuki Iwaki, Satoshi Tsuchihashi, Naoki Abe, Nobukado Ikeda, Tetsushi Kosaku, Toshiharu Takaki, Takeshi Systems Engineering Robotics Laboratory Graduate School of Information Science and Technology Hiroshima City University Asaminami Hiroshima Hiroshima Prefecture Japan Hiroshima University Graduate school of Engineering Hiroshima Japan

ISBN: (纸本)9789897583216

We propose a method in which multiple nozzles are arranged consecutively along a conveying line and an object can be relayed one after another. In this paper, as a most essential technology for such a conveyor, we focus on the transferring control of the object between a pair of air jet on a vertical plane. We propose a relaying control method based on some natural behaviours of an object in a fluid field where two air jet streams collide. Some successful experiment results are shown. Copyright © 2018 by SCITEPRESS – science and Technology Publications, Lda. All rights reserved

关键词： Conveying