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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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Distributed Leader-follower Formation Control of Nonholonomic Mobile Robots

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IFAC-PapersOnLine 2019年第15期52卷 67-72页

作者： Qun Lu Zhiqiang Miao Dan Zhang Li Yu Wenjun Ye Simon X. Yang Chun-Yi Su College of Electrical Engineering Yancheng Institute of Technology Yancheng 224003 China College of Electrical and Information Engineering Hunan University Changsha 410082 China College of Information Engineering Zhejiang University of Technology Hangzhou 310023 China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal QC H3G 1M8 Canada Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph Guelph ON N1G 2W1 Canada School of Automation Guangdong University of Technology Guangzhou 510006 China on leave from Concordia University Montreal QC H3G 1M8 Canada

This paper considers the problem of distributed leader-follower formation control for nonholonomic mobile robots only using local interactions among the robots. First, a distributed estimation strategy is presented for each follower robot to estimate the leader’s state. Then the dynamic equations of the formation tracking errors are formulated and a distributed formation control scheme is designed, which yields globally uniformly ultimately bounded stability for the closed-loop systems without requiring persistent excitation conditions. Finally, a simulation example demonstrates the effectiveness of the proposed approach.

关键词： Distributed formation control nonholonomic mobile robots distributed formation control persistent exciting conditions

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Robot Teaching by Teleoperation Based on Visual Interaction and Neural Network Learning

Robot Teaching by Teleoperation Based on Visual Interaction ...

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2017 9th International Conference on Modelling, Identification and Control (ICMIC 2017)

作者： Yang Xu Chenguang Yang Junpei Zhong Hongbin Ma Lijun Zhao Min Wang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and EngineeringSouth China University of Technology National Institute of Advanced Industrial Science and Technology School of Automation Beijing Institution of Technology State Key Laboratory of Robotics and System Harbin Institute of Technology

Traditional methods of Robot teaching require human demonstrators to program with a teaching pendant,which is a complex and time-consuming *** this paper,we propose a novel method based on teleoperation which allows a demonstrator to train robot in an intuitive *** specifically,at the beginning the demonstrator controls a robot by visual *** then a learning algorithm based on radial basis function(RBF) network is used to transfer the demonstrator's motions to the *** verify the effectiveness of this developed methods,several simulation experiments have been carried out which based on Microsoft Kinect Sensor and the Virtual Robot Experimentation Platform(V-REP).The experimental results show that this method has achieved satisfactory *** the help of this method,the robot can not only complete the task autonomously after teaching,but also can learn the details of demonstrator's behavior.

关键词： Robot Teaching Teleoperation radial basis function(RBF) network

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A unified leader-follower scheme for mobile robots with uncalibrated on-board camera

A unified leader-follower scheme for mobile robots with unca...

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2017 IEEE International Conference on robotics and automation, ICRA 2017

作者： Guo, Dejun Wang, Hesheng Chen, Weidong Liu, Ming Xia, Zeyang Leang, Kam K. Lab University of Utah Robotics Center Salt Lake CityUT84112 United States Department of Automation Shanghai Jiao Tong University Shanghai200240 China Department of Electronics and Computer Engineering Hong Kong University of Science and Technology Hong Kong Hong Kong Institute of Biomedical and Health Engineering Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781509046331

This paper studies the problem of image-based leader-follower formation control for mobile robots, where the controller is designed independently of the leader's motion. An adaptive control scheme, which is suitable for both omnidirectional and perspective cameras, is proposed. The proposed approach avoids the need for accurate calibration of the extrinsic parameters of the omnidirectional camera as well as the intrinsic and extrinsic parameters of perspective camera. Additionally, the coefficients of the plane where the feature point moves relative to the camera frame can be uncertain. These uncertain constant parameters are estimated using an adaptive estimator. Uniform Semi-global Practical Asymptotic Stability (USPAS) of the system is shown using the Lyapunov approach. Experimental results are presented to demonstrate the effectiveness of the proposed control scheme. © 2017 IEEE.

关键词： Mobile robots

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A novel extended potential field controller for use on aerial robots

A novel extended potential field controller for use on aeria...

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2016 IEEE International Conference on automation Science and Engineering, CASE 2016

作者： Woods, Alexander C. Lay, Hung M. Ha, Quang P. Advanced Robotics and Automation Laboratory Department of Computer Science and Engineering University of Nevada RenoNV89557 United States School of Electrical Mechanical and Mechatronic Systems University of Technology Sydney Australia

ISBN: (纸本)9781509024094

Unmanned Aerial Vehicles (UAV), commonly known as drones, have many potential uses in real world applications. Drones require advanced planning and navigation algorithms to enable them to safely move through and interact with the world around them. This paper presents an extended potential field controller (ePFC) which enables an aerial robot, or drone, to safely track a dynamic target location while simultaneously avoiding any obstacles in its path. The ePFC outperforms a traditional potential field controller (PFC) with smoother tracking paths and shorter settling times. The proposed ePFC's stability is evaluated by Lyapunov approach, and its performance is simulated in a Matlab environment. Finally, the controller is implemented on an experimental platform in a laboratory environment which demonstrates the effectiveness of the controller. © 2016 IEEE.

关键词： Controllers

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Cooperative load transport based on fuzzy logic controllers

Cooperative load transport based on fuzzy logic controllers

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IEEE/IAS International Conference on Industry Applications (INDUSCON)

作者： Marco Antonio Teixeira Higor Barbosa Santos Andre Schneider de Oliveira João Alberto Fabro Lucia Valeria Ramos de Arruda Flavio Neves-Jr Federal University of Technology — Parana Curitiba Parana Brazil Automation and Advanced Control System Laboratory (LASCA) Advanced Laboratory of Embedded Systems and Robotics (LASER)

This work presents the use of multiple mobile robots to perform a common transportation task. The main objective is to perform a navigation with a shared cargo, which allows the transport of objects with high payload or high sizes. Two robots are virtually linked through two Fuzzy controllers, one to control distance and another for orientation. A depth camera on the trailer's robot is used to measure the distance and orientation of the leader robot. The proposed approach is experimentally validated with two standard Pioneer mobile robots that collaboratively carry a large box.

关键词： Robot kinematics Robot sensing systems Mobile robots Payloads Three-dimensional displays Lasers

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Multi-stage feature learning based object recognition and 3D pose estimation with kinect 6

Multi-stage feature learning based object recognition and 3D...

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6th International Conference on Information Science and Technology, ICIST 2016

作者： Zeng, Wei Liang, Guoyuan Guangdong, Can Wang Wu, Xinyu Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Shenzhen China Dept. Mechanical and Automation Engineering Chinese University of Hong Kong Shenzhen China

ISBN: (纸本)9781509012206

Impressive achievements have been achieved over the years in object recognition and 3D pose estimation while detecting objects and estimating their 3D poses reliably is still a very challenging problem, especially for texture-less objects in heavily cluttered scenes. In this paper, we introduce an improved approach based on multi-stage feature learning to identify object as well as their 3D orientation efficiently. Our approach is motivated by visual neuroscience models. Currently similar architectures have been successfully applied to pedestrian detection, traffic recognition, face representation, etc. We compute the feature descriptors by multi-stage convolutional neural networks (CNNs) which could map the object identity and 3D poses to the Euclidean distance space by evaluating the similarity between descriptors. By contrast with classical approaches, our method relies on fast and approximate Nearest Neighbor (NN) matching to solve the large scale problems instead of one classifier per object or multi-class classifiers whose complexity grows rapidly with the number of objects. The experiments of detecting poorly-textured objects in cluttered scenarios have been carried out to verify the effectiveness and efficacy of the proposed approach. © 2016 IEEE.

关键词： Object recognition

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A Novel Extended Potential Field Controller for Use on Aerial Robots

A Novel Extended Potential Field Controller for Use on Aeria...

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IEEE International Conference on automation Science and Engineering

作者： Alexander C. Woods Hung M. La Quang P. Ha Advanced Robotics and Automation Laboratory Department of Computer Science and Engineering University of Nevada Reno 89557 USA School of Electrical Mechanical and Mechatronic Systems University of Technology Sydney Australia

ISBN: (纸本)9781509024100

关键词： Drones Navigation Robot sensing systems Target tracking Stability analysis

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Rehabilitation with lower limb exoskeleton robot joint load adaptive server control

Rehabilitation with lower limb exoskeleton robot joint load ...

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International Conference on Information and automation (ICIA)

作者： Shaomin Zhang Can Wang Ying Hu Duxin Liu Ting Zhang Xinyu Wu Key Laboratory of Human-Machine-Intelligence Synergic Systems Chinese Academy ot Sciences Shenzhen College of Advanced Technology University of Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Department of Mechanical and Automation The Chinese University of Hong Kong

ISBN: (纸本)9781509041039

In order to help spinal cord injury (SCI) patients to walk again, a medical robot exoskeleton have been developed to assist these patients to walk independently in SIAT, Shenzhen. The research of this article is exoskeleton robot single joint load adaptive servo control. Considering the volunteers, wearing an exoskeleton robot, joints have significant changes in load torque and the moment of inertia, so driving joints was designed based on fuzzy control. Load adaptive servo controller makes the robot in rows, counter rotating torque moment of inertia of change and change has a better adaptability, and improves the smoothness of joint movement. This method was tested and the test on SIAT exoskeletons, verify the feasibility of joint adaptive control algorithm.

关键词： Servomotors Legged locomotion Exoskeletons Torque DC motors

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A Human Motion Prediction Algorithm Based on HSMM for SIAT's Exoskeleton

A Human Motion Prediction Algorithm Based on HSMM for SIAT's...

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第35届中国控制会议

作者： Min Wang Xinyu Wu Du-Xin Liu Can Wang Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Department of Mechanical and Automation The Chinese University of Hong Kong

ISBN: (纸本)9781509009107

Getting the exoskeleton pilot's motion intent is very important for exoskeleton *** this paper,a new approach to predict human motion is *** prediction method is based on Hidden Semi-Markov *** orientation of the pilot's segment is collected by the Inertial Measurement *** Adaptive Boosting algorithm is adopted to classify the orientation data into *** sequence of motion labels is inputted into Hidden Semi-Markov Models for motion *** experimental data validate the proposed method.

关键词： Adaptive Boosting Hidden Semi-Markov Model Human Motion Prediction Exoskeleton

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