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Neural Networks, Information and Communication Engineering (NNICE), International Conference on

作者： Lizhi Hu Wei Lu Xiang Li Hui Lin Navigation and Localization Algorithm Department Zhejiang HuaRay Technology Co. Lt. Hangzhou China Software Research and Development Center Zhejiang HuaRay Technology Co. Lt. Hangzhou China

Localization and Navigation technology of mobile robots is becoming increasingly important in production and manufacturing factory. It is necessary to ensure localization and docking accuracy at high accuracy points and routes. In this paper, we propose a high-accuracy localization method based on 2D laser, wheel odometry, and prior probability grid map. The algorithm can maintain the accuracy of robot trajectory estimation in an dynamic environment that changes over time. Two resolution prior probability grid maps are constructed to determine the initial pose of the mobile robot. A factor graph model is constructed, allowing multiple relative or absolute observations, to be added to the factor graph as factors. During localization, two local submaps are constructed in real time, and are jointly optimized with prior maps before being used to the local scan matching. The laser odometry is generated by using local submaps scan matching, and is added to the factor graph model along with the wheel odometry and prior map scan matching. At the same time, several artificial features are designed at high-accuracy docking target points, and ensure the final docking accuracy by identifying artificial features.

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A METHOD FOR ALGEBRAIC ANALYSIS OF THE TLM algorithm

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INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 1995年第1期8卷 61-71页

作者： WITWIT, ARM WILKINSON, AJ PULKO, SH Department of Electronic Engineering The University of Hull Hull HU6 7RX U.K. Abdul Mehdi Witwit was born in Babylon in 1965. He graduated in Electronic Engineering from the Univeristy of Hull in 1990. He has recently submitted his Ph.D. thesis on the topic of meshing in TLM diffusion problems. Anthony James Wilkinson graduated from the niversity of Hull with a B.Sc. in Electronic Engineering in 1982 and a Ph.D. in adaptive control in 1987. He is currently a lecturer in the Department of Electronic Engineering where his research interests include TLM algorithms and computer control of magnetostrictive actuation. Susan Pulko obtained a B.Sc. in physics together with an ARCS from Imperial College (London) in 1977. This was followed by a Ph.D. from the University of Nottingham in 1981. Her current research interests centre on the TLM algorithm and on its application to a range of physical processes especially as applied to manufacturing. Current work involves development of the algorithm itself and TLM applications in the glass and ceramic industries.

An analogy is described between the TLM algorithm and discrete state-space control theory. The analogy is used to derive the characteristic equations corresponding to parameterized model structures. Characteristic equations corresponding to several widely used node structures are derived by this means and found to be consistent with the observed behaviour of corresponding TLM models. An example is given of the use of the analogy in the predictive mode.

关键词： algorithms

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RaftGP: Random Fast Graph Partitioning

RaftGP: Random Fast Graph Partitioning

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IEEE Conference on High Performance Extreme Computing (HPEC)

作者： Yu Gao Meng Qin Yibin Ding Li Zeng Chaorui Zhang Weixi Zhang Wei Han Rongqian Zhao Bo Bai Theory Lab 2012 Labs Central Research Institute Huawei Technologies Co. Ltd. Department of Computer Science & Engineering Hong Kong University of Science & Technology Algorithm & Technology Development Department Global Technical Service Department Huawei Technologies Co. Ltd.

Graph partitioning (GP), a.k.a. community detection, is a classic problem that divides the node set of a graph into densely-connected blocks. Following prior work on the IEEE HPEC Graph Challenge benchmark and recent advances in graph machine learning, we propose a novel RAndom FasT Graph Partitioning (RaftGP) method based on an efficient graph embedding scheme. It uses the Gaussian random projection to extract community-preserving features from classic GP objectives. These features are fed into a graph neural network (GNN) to derive low-dimensional node embeddings. Surprisingly, our experiments demonstrate that a randomly initialized GNN even without training is enough for RaftGP to derive informative community-preserving embeddings and support high-quality GP. To enable the derived embeddings to tackle GP, we introduce a hierarchical model selection algorithm that simultaneously determines the number of blocks and the corresponding GP result. We evaluate RaftGP on the Graph Challenge benchmark and compare the performance with five baselines, where our method can achieve a better trade-off between quality and efficiency. In particular, compared to the baseline algorithm [1] of the IEEE HPEC Graph Challenge, our method is 6.68x - 23.9x faster on graphs with 1E3 - 5E4 nodes and at least 64.5x faster on larger (IE5 node) graphs on which the baseline takes more than 1E4 seconds. Our method achieves better accuracy on all test cases. We also develop a new graph generator to address some limitations of the original generator in the benchmark.

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Incremental Model Predictive Control for Velocity-Controlled Robot Manipulators

Incremental Model Predictive Control for Velocity-Controlled...

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Annual Conference of Industrial Electronics Society

作者： Yongchao Wang Hengrui Li Cong Li Fangzhou Liu School of Aerospace Science and Technology Xidian University Xi’an China Algorithm Engineer Research and Development Department Agile Robots Beijing China College of Intelligence Science and Technology National University of Defense Technology Changsha China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In this article, an incremental model predictive controller is proposed for the velocity-controlled robot manipulator. First, the time-delay estimation (TDE) technique is used to approximate the unknown discrepancy between the command and the real joint velocity due to velocity dynamics, and the equation of motion in the incremental form is obtained. Then, on the basis of the resulting equation of motion and taking into account joint position and velocity constraints, the incremental model predictive controller is developed by formulating a constrained optimal control problem (OCP). The constrained OCP is cast to a quadratic programming (QP) problem, making it possible to employ computationally efficient QP solvers to solve the constrained OCP. As a result, real-time control is guaranteed. Finally, experiments on a robot manipulator are implemented to verify the effectiveness of the developed incremental model predictive controller.

关键词： Service robots Computational modeling Optimal control Estimation Predictive models Mathematical models Robustness Computational efficiency Quadratic programming Predictive control

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A NOVEL APPROACH FOR HOLOGRAPHIC 3D CONTENT GENERATION WITHOUT DEPTH MAP

arXiv

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arXiv 2023年

作者： Kim, Hakdong Jee, Minkyu Lee, Yurim Choi, Kyudam Yoon, MinSung Kim, Cheongwon Department of Digital Contents Sejong University Seoul05006 Korea Republic of Department of Algorithm Development Selvers Seoul04594 Korea Republic of Department of Software Sejong University Seoul05006 Korea Republic of Department of Software Convergence Sejong University Seoul05006 Korea Republic of Communication & Media Research Laboratory Electronics and Telecommunications Research Institute Daejeon34129 Korea Republic of

In preparation for observing holographic 3D content, acquiring a set of RGB color and depth map images per scene is necessary to generate computer-generated holograms (CGHs) when using the fast Fourier transform (FFT) algorithm. However, in real-world situations, these paired formats of RGB color and depth map images are not always fully available. We propose a deep learning-based method to synthesize the volumetric digital holograms using only the given RGB image, so that we can overcome environments where RGB color and depth map images are partially provided. The proposed method uses only the input of RGB image to estimate its depth map and then generate its CGH sequentially. Through experiments, we demonstrate that the volumetric hologram generated through our proposed model is more accurate than that of competitive models, under the situation that only RGB color data can be provided. Copyright © 2023, The Authors. All rights reserved.

关键词： Holograms

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RaftGP: Random Fast Graph Partitioning

arXiv

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arXiv 2023年

作者： Gao, Yu Qin, Meng Ding, Yibin Zeng, Li Zhang, Chaorui Zhang, Weixi Han, Wei Zhao, Rongqian Bai, Bo Theory Lab Central Research Institute 2012 Labs Huawei Technologies Co. Ltd China Algorithm & Technology Development Department Global Technical Service Department Huawei Technologies Co. Ltd. China Department of Computer Science & Engineering Hong Kong University of Science & Technology Hong Kong

Graph partitioning (GP), a.k.a. community detection, is a classic problem that divides the node set of a graph into densely-connected blocks. Following prior work on the IEEE HPEC Graph Challenge benchmark and recent advances in graph machine learning, we propose a novel RAndom FasT Graph Partitioning (RaftGP) method based on an efficient graph embedding scheme. It uses the Gaussian random projection to extract community-preserving features from classic GP objectives. These features are fed into a graph neural network (GNN) to derive low-dimensional node embeddings. Surprisingly, our experiments demonstrate that a randomly initialized GNN even without training is enough for RaftGP to derive informative community-preserving embeddings and support high-quality GP. To enable the derived embeddings to tackle GP, we introduce a hierarchical model selection algorithm that simultaneously determines the number of blocks and the corresponding GP result. We evaluate RaftGP on the Graph Challenge benchmark and compare the performance with five baselines, where our method can achieve a better trade-off between quality and efficiency. In particular, compared to the baseline algorithm [1] of the IEEE HPEC Graph Challenge, our method is 6.68x – 23.9x faster on graphs with 1E3 – 5E4 nodes and at least 64.5x faster on larger (1E5 node) graphs on which the baseline takes more than 1E4 seconds. Our method achieves better accuracy on all test cases. We also develop a new graph generator to address some limitations of the original generator in the benchmark. Copyright © 2023, The Authors. All rights reserved.

关键词： Graph neural networks

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An Improved Non-Geometrical Stochastic Model for Non-WSSUS Vehicle-to-Vehicle Channels

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ZTE Communications 2019年第4期17卷 62-71页

作者： HUANG Ziwei CHENG Xiang ZHANG Nan State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871China Key Laboratory of Wireless Sensor Network&Communication Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China Wireless Algorithm Department Product Research and Development SystemZTE CorporationShanghai 201203China

A novel non-geometrical stochastic model(NGSM)for non-wide sense station ary uncorrelated scattering(non-WSSUS)vehicle-to-vehicle(V2V)channels is *** model is based on a conventional NGSM and employs a more accurate method to reproduce the realistic characteristics of V2V channels,which successfully extends the existing NGSM to include the line-of-sight(LoS)***,the statistical properties of the proposed model in different scenarios,including Doppler power spectral density(PSD),power delay profile(PDP),and the tap correlation coefficient matrix are simulated and compared with those of the existing ***,the simulation results dem onstrate not only the utility of the proposed model,but also the correctness of our theoreti cal derivations.

关键词： vehicle-to-vehicle non-WSSUS channels non-geometrical stochastic model LoS component statistical properties

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The IPI identifies the window of opportunity for treatment before cardio-respiratory arrest

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Resuscitation 2010年第2期81卷 S42-S42页

作者： Einav, S. Helvitz, Y. Ronen, M. Hersch, M. Intensive Care Unit Shaare Zedek Hebrew University Medical Center Jerusalem Israel Algorithm Engineering Department of Research and Development Oridion Medical

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An Intelligent Age of Information Based Self-Energized Uav-Assisted Wireless Communication System

SSRN

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SSRN 2022年

作者： Jeganathan, Anandpushparaj Dhayabaran, Balaji Jayakody, Dushantha Nalin K. Ranchagodage Don, Sanjaya Arunapriya Muthuchidambaranathan, P. Department of Electronics and Communication Engineering National Institute of Technology Tiruchirappalli620015 India Senior Member Technical Staff Baseband Algorithm Development Team Saankhya Labs Private Limited Bengaluru560001 India Centro de Investigaçä em Tecnologias Autónoma TechLab Universidade Autónoma Lisboa Portugal School of Computer Science and Robotics National Research Tomsk Polytechnic University Tomsk Russia Centre for Telecommunication Research School of Engineering Sri Lanka Technological Campus Padukka 10500 Sri Lanka

Internet-of-things (IoT) is an enabling technology in the fourth generation industrial revolution. An unified performance metric named age of information (AoI) is introduced to quantify the freshness of data and its applications. Thus, this paper study the combination of AoI and full-duplex enabled unmanned aerial vehicle (FD-UAV) as a promising solution to improve latency and spectrum efficiency of a wireless powered sensor network. A sensor node (SN), located in a transport infrastructure, harvests energy from radio frequency signals transmitted by the FD-UAV. This uses to transmit real time sensor observations to the data sink via FD-UAV. The SN generates an update after replenished the battery and transmits by using the harvested energy. A closed-form expression for average AoI (AAoI) is derived as a function of time allocated for energy harvesting (EH). The optimal time allocation for EH that maximizes the freshness of data update is identified. Deep learning algorithms such as Long-Short Term Memory (LSTM) is used to predict the AAoI. Simulation results demonstrate the usefulness performance bounds in-terms of freshness of data updates. © 2022, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Millimeter wave communications with reconfigurable intelligent surface: Performance analysis and optimization

arXiv

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arXiv 2020年

作者： Du, Hongyang Zhang, Jiayi Cheng, Julian Lu, Zhaohu Ai, Bo School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China School of Engineering University of British Columbia KelownaBCV1V 1V7 Canada Algorithm Department Wireless Product Research and Development Institute Wireless Product Operation ZTE Corporation Shenzhen518000 China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China

Reconfigurable Intelligent Surface (RIS) can create favorable multipath to establish strong links that are useful in millimeter wave (mmWave) communications. While previous works used Rayleigh or Rician fading, we use the fluctuating two-ray (FTR) distribution to model the small-scale fading in mmWave frequency. First, we obtain the statistical characterizations of the product of independent FTR random variables (RVs) and the sum of product of FTR RVs. For the RIS-aided and amplify-and-forward (AF) relay systems, we derive exact end-to-end signal-to-noise ratio (SNR) expressions. To maximize the end-to-end SNR, we propose a novel and simple way to obtain the optimal phase shifts at the RIS elements. The optimal power allocation scheme for the AF relay system is also proposed. Furthermore, we evaluate important performance metrics including the outage probability and the average bit error probability. To validate the accuracy of our analytical results, Monte-Carlo simulations are subsequently conducted to provide interesting insights. It is found that the RIS-aided system can achieve the same performance as the AF relay system with low transmit power. More interestingly, as the channel conditions improve, the RIS-aided system can outperform the AF relay system having the same transmit power with a smaller number of reflecting elements. Copyright © 2020, The Authors. All rights reserved.

关键词： Signal to noise ratio

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