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2019 IEEE International Conference on Unmanned systems and Artificial Intelligence, ICUSAI 2019

作者： Lin, Dengliang Dong, Xin Yang, Chenguang Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou China Nottingham University Department of Mechanical Materials and Manufacturing Engineering NottinghamNG7 2RD United Kingdom Bristol Robotics Laboratory University of the West of England BristolBS16 1QY United Kingdom

ISBN: (纸本)9781728158594

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. © 2019 IEEE.

关键词： End effectors

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Classification and applications of titanium and its alloys: A review

Journal of Alloys and Compounds Communications

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Journal of Alloys and Compounds Communications 2024年 3卷

作者： Mojtaba Najafizadeh Sahar Yazdi Mansoor Bozorg Mehran. Ghasempour-Mouziraji Morteza Hosseinzadeh Masoumeh Zarrabian Pasqual Cavaliere School of Materials Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China Faculty of Chemical and Materials Engineering Shahrood University of Technology Shahrood *** Iran Department of Innovation Engineering University of Salento Via per Arnesano Lecce 73100 Italy School of Medical Sciences Shahrood Branch Islamic Azad University Shahrood Iran TEMA - Centre for Mechanical Technology and Automation University of Aveiro Portugal LASI Intelligent Systems Associate Laboratory Guimarães Portugal Engineering and Sustainable Technology ManagementIndustry 4.0: Automation Robotics & 3D Manufacturing SRH Hochschule Berlin Germany Department of Engineering Ayatollah Amoli Branch Islamic Azad University Amol Iran

Due to its numerous properties, iron is one of the most useful materials on the planet. The mechanical and physical properties of iron and its alloys are suitable and manageable. These alloys have significant issues like heavyweight, low corrosion resistivity and some other limitations. The researchers and companies for solving problems look out for other alternative materials. Titanium and its alloys, according to the researchers, have a huge variety of engineering applications. Titanium and titanium alloys have high strength and corrosion resistance, and they perform well at high temperatures up to nearly 600 °C. Titanium and its alloys have a density of about 60 % that of steel and its alloys, and about 50 % that of nickel alloys. Even though titanium and its alloys have cost and supply problems, they're utilized in numerous industries, which includes aerospace, automotive, and navy projects. Titanium and its alloys have unique properties, indicating that they are cost-effective components that require special manufacturing techniques. This study aims to explore the potential of titanium and its alloys to replace iron in various engineering applications. Addressing the critical need for materials with superior performance characteristics is essential for advancing technological development.

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Abstracting the Abstract: A Swarm Art Project 2017

Abstracting the Abstract: A Swarm Art Project

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8th International Conference on Digital Arts, ARTECH 2017

作者： Fernandes, Carlos M. LARSyS: Laboratory for Robotics and Systems in Engineering and Science University of Lisbon Lisbon Portugal

ISBN: (纸本)9781450352734

关键词： Abstracting

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Cooperative Motion Planning with Time, Energy and Active Navigation Constraints

Cooperative Motion Planning with Time, Energy and Active Nav...

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Symposium on Autonomous Underwater Vehicle Technology (AUV)

作者： Bahareh Sabetghadam Rita Cunha Antόnio Pascoal Laboratory of Robotics and Engineering Systems (LARSyS) ISR /IST University of Lisbon Lisbon Portugal

ISBN: (纸本)9781728102542

One of the key elements for the successful execution of multiple AUV missions is the availability of reliable and efficient cooperative motion planning systems. In a representative mission, this system should have the capability to generate collision-free trajectories from the AUVs' initial positions to desired goal positions while optimizing some mission specific performance metric. The trajectories must also satisfy different constraints imposed by environmental conditions, AUV dynamics, and underwater communication limitations. This calls for the availability of algorithms that can deal with a large number of constraints and complex cost functions. In this paper we address the cooperative motion planning problem for a group of AUVs with time, energy, and active navigation constraints. We focus on two challenging problems. In the first problem the trajectories should guide the AUVs to a desired formation with minimum energy consumption, while in the second the information content of the path should be maximized for accurate single-beacon AUV positioning. We formulate the problems as optimal control problems to explicitly address the objectives and constraints. We employ the “direct multiple shooting” method along with a structure-exploiting optimization solver to efficiently solve the optimal control problem. Numerical results illustrate the efficacy of the methodology adopted for cooperative motion planning.

关键词： Trajectory Planning Optimization Energy consumption Navigation Optimal control Vehicle dynamics

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F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning

arXiv

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arXiv 2020年

作者： Li, Wenhao Jin, Bo Wang, Xiangfeng Yan, Junchi Zha, Hongyuan School of Data Science The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China School of Software Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201804 China School of Computer Science and Technology Key Laboratory of Mathematics and Engineering Applications Ministry of Education East China Normal University Shanghai200062 China Department of Computer Science and Engineering Key Laboratory of Artificial Intelligence Ministry of Education Shanghai Jiao Tong University Shanghai200240 China

Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications due to non-interactivity between agents, the curse of dimensionality, and computation complexity. Hence, several decentralized MARL algorithms are motivated. However, existing decentralized methods only handle the fully cooperative setting where massive information needs to be transmitted in training. The block coordinate gradient descent scheme they used for successive independent actor and critic steps can simplify the calculation, but it causes serious bias. This paper proposes a flexible fully decentralized actor-critic MARL framework, which can combine most of the actor-critic methods and handle large-scale general cooperative multi-agent settings. A primal-dual hybrid gradient descent type algorithm framework is designed to learn individual agents separately for decentralization. From the perspective of each agent, policy improvement and value evaluation are jointly optimized, which can stabilize multi-agent policy learning. Furthermore, the proposed framework can achieve scalability and stability for the large-scale environment. This framework also reduces information transmission by the parameter sharing mechanism and novel modeling-other-agents methods based on theory-of-mind and online supervised learning. Sufficient experiments in cooperative Multiagent Particle Environment and StarCraft II show that the proposed decentralized MARL instantiation algorithms perform competitively against conventional centralized and decentralized methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Gradient methods

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Short-Term Photovoltaic Power Prediction Modeling Based on AdaBoost Algorithm and Elman

Short-Term Photovoltaic Power Prediction Modeling Based on A...

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IEEE International Conference on Power and Energy systems (ICPES)

作者： Wenxuan Sun Tao Zhang Ran Tao Anna Wang College Of Information Science and Engineering Northeastern University Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China School of Electrical Engineering Dalian University of Technology Dalian China

ISBN: (数字)9781665404945

ISBN: (纸本)9781665404952

In recent years, with the rapid expansion of the installed capacity of renewable energy systems, the availability, stability and quality of smart grids have become increasingly important [1] . The application of renewable energy production forecasting has also been rapidly developed, especially in the field of solar photovoltaic (PV) [2][3] . In the example of solar PV output prediction, machine learning and hybrid technologies have been implemented for many applications. In this paper, a high-precision PV system output power prediction model based on improved AdaBoost and Elman is proposed. Multiple model using integrated AdaBoost algorithm fusion with the bat algorithm for the parameters of optimized combination of weak Elman neural network predictor to become a higher prediction precision, the method of strong predictor of the model can according to the weather information, such as temperature, solar radiation and the history of the output of the PV system data, the probability of photovoltaic power generation for 12 hours and deterministic prediction. The prediction accuracy of the model is determined by Root Mean Squared Error (RMSE). Experimental results show that the prediction accuracy of this algorithm is better than that of other benchmark models, and the algorithm can effectively predict the volatility and irregularity of complex time series.

关键词： Photovoltaic systems Renewable energy sources Machine learning algorithms Machine learning Predictive models Prediction algorithms Numerical models

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Lightweight and conformal acousto-ultrasonic sensing network for multi-scale structural health monitoring: A review

FlexMat

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FlexMat 2024年

作者： Yehai Li Shifeng Guo Zhongqing Su Keqin Ding Xian Jun Loh Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China The Key Laboratory of Biomedical Imaging Science and System Chinese Academy of Sciences Shenzhen China Department of Mechanical Engineering The Hong Kong Polytechnic University Kowloon Hong Kong Technology Innovation Center of Structural Health Monitoring of State Market Regulation China Special Equipment Inspection & Research Institute Beijing China Institute of Materials Research and Engineering (IMRE) Agency for Science Technology and Research (A*STAR) Singapore Singapore

Structural health monitoring (SHM) has been increasingly investigated for decades. Different physical principles have been developed for damage identification, such as electronics, mechanics, magnetics, etc., with different coverage (i.e., global, large-area, and local monitoring) and sensitivity. Mechanical acousto-ultrasonic-based methods have formed a big family in SHM technologies. Multiple wave/resonance modes have been utilized for versatile SHM tasks. The permanently integrated sensing networks play a significant role in achieving a cost-effective and reliable SHM system, with major concerns including weight increase for large-scale deployment and conformity for complex geometry structures. In this review, typical acousto-ultrasonic sensors made of different material systems are discussed, along with advantages and limitations. Moreover, advanced network installation methods have been introduced, including surface-mounting with pre-integrated networks on substrates and in situ printing, and embedding with composite layup and metal additive manufacturing. Sensor versatility and usage in multi-scale SHM techniques are then highlighted. Different wave/resonance modes are transmitted and received with corresponding elements and network designs. In conclusion, this systematic review mainly covers a collection of acousto-ultrasonic sensors, two modalities of network installation, and their employment with various SHM methods, hopefully providing a useful guide to building lightweight and conformal networks with passive or active-passive sensors, and developing complete and reliable SHM strategies by integrating different damage identification methods on multiple scales.

关键词： acousto-ultrasonic conformal installation lightweight sensing networks structural health monitoring

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BTI Aging Monitoring based on SRAM Start-up Behavior

BTI Aging Monitoring based on SRAM Start-up Behavior

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Asian Test Symposium (ATS)

作者： Shengyu Duan Peng Wang Gaole Sai School of Computer Engineering and Science Shanghai University Shanghai China State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology China

ISBN: (数字)9781728174679

ISBN: (纸本)9781728174686

Bias Temperature Instability (BTI) is one of the dominant CMOS aging mechanisms. It causes time-dependent variation, threatening circuit lifetime reliability. BTI-induced circuit errors are not detectable at the fabrication stage. On-line monitoring schemes are therefore necessary to capture the degradations during the operational time. Traditional aging monitoring techniques exhibit high implementation complexity and low stability. In this paper, we propose a BTI monitoring approach by simply tracking the start-up behavior of SRAM cells. SRAM is a widely used on-chip device in many applications. We study the impact of BTI for SRAM start-up values and age some cells in a manipulated manner. The BTI degradation is evaluated based on the number of SRAM cells starting with a certain value. This technique can be used to estimate the degradation for on-chip logic circuits without introducing additional circuitry, and thus has very low implementation complexity. We use an SRAM array with 1024 cells to estimate the degradations for multiple logic circuits, and show the average mean absolute percentage error as 8.48%. In addition, this technique is robust considering process, voltage and temperature variations.

关键词： Degradation Monitoring Logic circuits Transistors SRAM cells Aging System-on-chip

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Design of a Sextuple Cross-Coupled SRAM Cell with Optimized Access Operations for Highly Reliable Terrestrial Applications

Design of a Sextuple Cross-Coupled SRAM Cell with Optimized ...

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Asian Test Symposium (ATS)

作者： Aibin Yan Zhen Wu Jun Zhou Yuanjie Hu Yan Chen Zuobin Ying Xiaoqing Wen Patrick Girard School of Computer Science and Technology Anhui Engineering Laboratory of IoT Security Technologies Hefei China Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Laboratory of Informatics Robotics and Microelectronics of Montpellier CNRS Montpellier France

ISBN: (数字)9781728126951

ISBN: (纸本)9781728126968

The Aggressive technology scaling makes modern advanced SRAMs more and more sensitive to soft errors that include single-node upsets (SNUs) and double-node upsets (DNUs). This paper presents a novel Sextuple Cross-Coupled SRAM cell, namely SCCS cell, which can tolerate both SNUs and DNUs. The cell mainly consists of six cross-coupled input-split inverters, constructing a large error-interceptive feedback loop to robustly retain stored values. Since the cell has many redundant storage nodes, the cell achieves the following robustness: (1) the cell can self-recover from all possible SNU; (2) the cell can self-recover from partial DNUs; (3) the cell can avoid the occurrence of other DNUs due to node-separation. Simulation results validate the excellent robustness of the proposed cell. Moreover, compared with the state-of-the-art typical existing hardened cells, the proposed cell achieves an approximate 61% read access time as well as 12% write access time reduction at the costs of 47% power dissipation as well as 44% silicon area on average.

关键词： Transistors SRAM cells Simulation Integrated circuit reliability Feedback loop

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An Early Stage Researcher's Primer on systems Medicine Terminology

Network and Systems Medicine

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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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