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IEEE/RSJ International Conference on intelligent Robots and systems (IROS)

作者： Zhengcai Cao Yiyang Sun Zhe Ma MengChu Zhou State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China College of Information Science and Technology Beijing University of Chemical Technology Beijing China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Topological semantic maps provide a practical solution to enhance indoor navigation for the Partially Sighted or Visually Impaired (PSVI). Segmenting indoor floor plans and extracting boundaries are key to constructing these maps. The existing methods exhibit low accuracy in segmentation. To achieve desired high segmentation accuracy, we introduce a Context-Enhanced Full-Resolution Network (CEFRN) for floor plan segmentation. It is designed to harness the shallow detailed features and inter-category contextual dependencies inherent in floor plans. CEFRN integrates modified residual blocks to capture the low-stage full-resolution features while maintaining its compactness. A position attention module is employed to refine the deep-stage contextual information. We also propose a two-dimensional deep supervision method to merge features from both stages, which significantly boosts the feature representation ability of CEFRN. Finally, a practical topological semantic mapping method for PSVI indoor navigation is introduced. Experimental results demonstrate that CEFRN’s segmentation accuracy well exceeds the state-of-the-art methods’. It can be used to well support accurate topological semantic mapping.

关键词： Accuracy Hospitals Indoor navigation Semantics Feature extraction Mobile robots Floors intelligent robots Autonomous vehicles Drones

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PLC and Human Machine Interface based PV Condition Monitoring Structure Comprising an Innovative Fault Detection Scheme

PLC and Human Machine Interface based PV Condition Monitorin...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Amir Nedaei Aref Eskandari Nima Pourshahbaz Sherko Salehpour Parviz Parvin Andreas Livera George Makrides Mohammadreza Aghaei Department of Electrical Engineering Amirkabir University of Technology (AUT) Tehran Iran Department of Electrical Engineering Iran University of Science and Technology (IUST) Tehran Iran Department of Physics and Energy Engineering Amirkabir University of Technology (AUT) Tehran Iran Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus (UCY) PHAENTON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus (UCY) PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus Department of Ocean Operations and Civil Engineering Norwegian University of Science and Technology (NTNU) Ålesund Norway Department of Sustainable Systems Engineering (INATECH) University of Freiburg Freiburg Germany

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

Photovoltaic (PV) systems operate outdoors and are inevitably exposed to various environmental stresses. These stresses may result in several faults and failures which can affect the PV proper performance in terms of reducing the output power and even in some catastrophic cases may end in fire hazards. Therefore, PV systems need to be constantly and carefully monitored to maintain their appropriate performance. In this paper, a condition monitoring (CM) scheme is proposed based on the Programmable Logic Controller (PLC). The scheme is capable to detect line-to-line (LL) and line-to-ground (LG) faults on the DC-side of the PV array and also enables the system to track the maximum power point (MPP) and provides the operator with the real-time PV information via Human-Machine Interface (HMI).

关键词： Condition monitoring Photovoltaic systems Human-machine systems Programmable logic devices Programmable logic arrays Real-time systems Hazards Logic Stress Monitoring

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An intelligent Condition Monitoring Scheme For Photovoltaic systems using Programmable Logic Controller

An Intelligent Condition Monitoring Scheme For Photovoltaic ...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

Environmental and other stresses are constantly affecting photovoltaic (PV) components which can end in various faults. The anomalous condition can reduce the PV output power or even result in a calamitous fire hazard. Hence, PV systems must be monitored constantly in order to ensure their proper performance. This paper proposes an intelligent PV condition monitoring scheme based on Programmable Logic Controller (PLC). This scheme monitors the PV performance and detects different faults and failures on the DC-side of the array. It also takes advantage of Human-Machine Interface (HMI) which provides the operators with useful real-time data from the array.

关键词： Condition monitoring Photovoltaic systems Human-machine systems Programmable logic devices Real-time systems Arrays Logic Monitoring Stress Logic arrays

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Non-Convex Potential Games for Finding Global Solutions to Sensor Network Localization

Non-Convex Potential Games for Finding Global Solutions to S...

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European Control Conference (ECC)

作者： Gehui Xu Guanpu Chen Yiguang Hong Baris Fidan Thomas Parisini Karl H. Johansson Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Electrical and Electronic Engineering Imperial College London London UK Department of Engineering and Architecture University of Trieste Trieste Italy

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results.

关键词： Location awareness Coordinate measuring machines Simulation Current measurement Noise Europe Games

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Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data

Deep Learning-Based Prediction of Subsurface Oil Reservoir P...

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Annual Conference of Industrial Electronics Society

作者： Haibo Cheng Yunpeng He Peng Zeng Shichao Li Valeriy Vyatkin State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden Department of Electrical Engineering and Automation Aalto University Helsinki Finland

Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction.

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Variational Bayesian Learning Based Localization and Channel Reconstruction in RIS-aided systems

arXiv

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arXiv 2024年

作者： Li, Yunfei Luo, Yiting Wu, Xianda Shi, Zheng Ma, Shaodan Yang, Guanghua The Department of Electrical Engineering Anhui Polytechnic University Wuhu City China The School of Electronics and Information Engineering South China Normal University Foshan528000 China The School of Intelligent Systems Science and Engineering Jinan University Zhuhai519070 China The State Key Laboratory of Internet of Things for Smart City the Department of Electrical and Computer Engineering University of Macau Taipa China

The emerging immersive and autonomous services have posed stringent requirements on both communications and localization. By considering the great potential of reconfigurable intelligent surface (RIS), this paper focuses on the joint channel estimation and localization for RIS-aided wireless systems. As opposed to existing works that treat channel estimation and localization independently, this paper exploits the intrinsic coupling and nonlinear relationships between the channel parameters and user location for enhancement of both localization and channel reconstruction. By noticing the non-convex, nonlinear objective function and the sparser angle pattern, a variational Bayesian learning-based framework is developed to jointly estimate the channel parameters and user location through leveraging an effective approximation of the posterior distribution. The proposed framework is capable of unifying near-field and far-field scenarios owing to exploitation of sparsity of the angular domain. Since the joint channel and location estimation problem has a closed-form solution in each iteration, our proposed iterative algorithm performs better than the conventional particle swarm optimization (PSO) and maximum likelihood (ML) based ones in terms of computational complexity. Simulations demonstrate that the proposed algorithm almost reaches the Bayesian Cramer-Rao bound (BCRB) and achieves a superior estimation accuracy by comparing to the PSO and the ML algorithms. Copyright © 2024, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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Adaptive Robust Invariant Extended Kalman filtering for Biped Robot

Adaptive Robust Invariant Extended Kalman filtering for Bipe...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Gao, Chengzhi Xie, Ye Zhu, Shiqiang Huang, Guanyu Kong, Lingyu Xie, Anhuan Gu, Jason Zhang, Dan Shao, Jun Qian, Haofu Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Zhejiang University Zhejiang Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University HalifaxNSB3H 4R2 Canada York University North YorkM3J 1P3 Canada School of Mechanical Engineering Zhejiang University Hangzhou310007 China

ISBN: (纸本)9781665481090

The precise estimation of system states is essential for the locomotion control of biped robots to maintain balance. Currently, the estimation of system states is either based on vision data that is susceptible to the environment, or fusing data from Inertial Measurement Unit (IMU) and the kinematic calculation. Invariant Extended Kalman Filtering (IEKF) is one of the most successful fusing algorithms to estimate system state. Generally, in IEKF, the noise covariance of system state is assumed to be known. However, the noise covariance of contact point for biped is not available since the ground-contact situation normally varies and not previously known. This paper presents a new fusing algorithm-Adaptive Robust Invariant Extended Kalman Filtering (ARIEKF) to adaptively adjust the noise parameter of contact point. The proposed algorithm applied the principle of robust estimation to resist outlier effects of state, and introduced an adaptive factor for the noise covariance of state to control its outlying disturbance influences. This paper firstly completed the full state estimation of biped robot using the theory of Lie groups and invariant observer. Then, the adaptive scale factor evaluated by three-segment approach was adopted to adjust the noise covariance of contact point. Finally, both IEKF and proposed ARIEKF are applied to our biped robot-Cosmos and the accuracy of two algorithms are compared. The mean square errors of the velocity of two algorithms were evaluated using the measurements from motion capture system. Experiments demonstrated that the mean square errors of the velocity are decreased 50 percent when compared with IEKF. © 2022 IEEE.

关键词： Mean square error

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Guest Editorial Special Issue on Near-Field Communications (NFCs) in Internet of Everything

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IEEE Internet of Things Journal 2025年第12期12卷 18459-18460页

作者： Pin-Han Ho Miaowen Wen Zhiguo Ding Marco Di Renzo Wei Duan Department of Electrical and Computer Engineering University of Waterloo Waterloo ON Canada School of Electronic and Information Engineering South China University of Technology Guangzhou China Department of Computer Communication Engineering Khalifa University Abu Dhabi UAE Intelligent Physical Communications group in the Laboratory of Signals and Systems (L2S) Paris-Saclay University Gif-sur-Yvette France School of Information Science and Technology Nantong University Nantong China

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Operational strategies for a photovoltaic-thermal system integrated with an electric air-to-water heat pump

Operational strategies for a photovoltaic-thermal system int...

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International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED)

作者： Giuseppe Russo Andreas V. Olympios Chandan Pandey Annamaria Buonomano Christos N. Markides Department of Chemical Engineering Clean Energy Processes (CEP) Laboratory and Sargent Centre for Process Systems Engineering Imperial College London UK Department of Industrial Engineering University of Naples Federico II Naples Italy Department of Electrical and Computer Engineering PV Technology Laboratory University of Cyprus Nicosia Cyprus PHAETHON Centre of Excellence for Intelligent Efficient and Sustainable Energy Solutions Nicosia Cyprus

ISBN: (数字)9798350375923

ISBN: (纸本)9798350375930

In this study, operational strategies are investigated for an air-based photovoltaic-thermal (PV-T) system integrated with a domestic air-to-water heat pump. The PV-T system is used to simultaneously generate electricity and heat ambient air, which serves as the heat source for the heat pump. By utilising a variable-speed fan to regulate airflow, the PV-T system outlet temperature is adjusted, and the focus is on how different outlet temperatures impact the PVT system electrical and thermal efficiency, heat pump performance, and overall electricity requirements for heating. The performance of the integrated system is assessed for a case study of a household application in north Italy. The optimal PV-T outlet temperature is found to be between 30 – 35 °C, resulting in only 5% less electricity production than an equivalent PV system with equal nominal electricity capacity, while reducing overall electricity required for heating by over 15% compared to PV-integrated heat pumps.

关键词： Photovoltaic systems Fans Temperature Heat pumps Electricity Buildings Water heating Production Temperature control Resistance heating

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GaRField++: Reinforced Gaussian Radiance Fields for Large-Scale 3D Scene Reconstruction

arXiv

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arXiv 2024年

作者： Zhang, Hanyue Yang, Zhiliu Zuo, Xinhe Tong, Yuxin Long, Ying Liu, Chen School of Information Science and Engineering Yunnan University Yunnan Kunming650500 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Yunnan Kunming650500 China Department of Electrical and Computer Engineering Clarkson University PotsdamNY13699 United States

This paper proposes a novel framework for large-scale scene reconstruction based on 3D Gaussian splatting (3DGS) and aims to address the scalability and accuracy challenges faced by existing methods. For tackling the scalability issue, we split the large scene into multiple cells, and the candidate point-cloud and camera views of each cell are correlated through a visibility-based camera selection and a progressive point-cloud extension. To reinforce the rendering quality, three highlighted improvements are made in comparison with vanilla 3DGS, which are a strategy of the ray-Gaussian intersection and the novel Gaussians density control for learning efficiency, an appearance decoupling module based on ConvKAN network to solve uneven lighting conditions in large-scale scenes, and a refined final loss with the color loss, the depth distortion loss, and the normal consistency loss. Finally, the seamless stitching procedure is executed to merge the individual Gaussian radiance field for novel view synthesis across different cells. Evaluation of Mill19, Urban3D, and MatrixCity datasets shows that our method consistently generates more high-fidelity rendering results than state-of-the-art methods of large-scale scene reconstruction. We further validate the generalizability of the proposed approach by rendering on self-collected video clips recorded by a commercial drone. © 2024, CC BY.

关键词： 3D reconstruction

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