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Reciprocal Safety Velocity Cones for Decentralized Collision Avoidance in Multi-Agent systems

IFAC-PapersOnLine 2023年第2期56卷 8024-8029页

作者： Soulaimane Berkane Dimos V. Dimarogonas Department of Computer Science and Engineering University of Quebec in Outaouais 101 St-Jean Bosco Gatineau QC J8X 3X7 Canada Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology SE-100 44 Stockholm Sweden

In this paper, we solve the inter-agent collision avoidance problem in an arbitrary n-dimensional Euclidean space using reciprocal safety velocity cones (RSVCs). We propose a decentralized feedback control strategy that guarantees simultaneously asymptotic stabilization to a reference and collision avoidance. Our algorithm is purely decentralized in the sense that each agent uses only local information about its neighbouring agents. Moreover, the proposed solution can be implemented using only inter-agent bearing measurements. Therefore, the algorithm is a sensor-based control strategy which is practically implementable using a wide range of sensors such as vision systems and range scanners. Simulation results in a two dimensional environment cluttered with agents shows that the number of possible deadlocks is marginal and decrease with the decrease in the clutteredness of the workspace.

关键词： Collision avoidance multi-agent systems sensor-based methods motion planning feedback control

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Neural Network-Assisted Hybrid Model Based Message Passing for Parametric Holographic MIMO Near Field Channel Estimation

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IEEE Transactions on Wireless Communications 2025年

作者： Yuan, Zhengdao Guo, Yabo Gao, Dawei Guo, Qinghua Wang, Zhongyong Huang, Chongwen Jin, Ming Wong, Kai-Kit Henan Open University Artificial Intelligence Technology Engineering Research Center Zhengzhou450002 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia Zhengzhou University School of Information Engineering Zhengzhou450002 China Xidian University Hangzhou Institute of Technology Hangzhou311200 China University of Wollongong School of Electrical Computer and Telecommunications Engineering NSW2522 Australia Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China University College London Department of Electronic and Electrical Engineering Torrington Place WC1E 7JE United Kingdom Yonsei University Yonsei Frontier Lab Seoul Korea Republic of

Holographic multiple-input and multiple-output (HMIMO) is a promising technology with the potential to achieve high energy and spectral efficiencies, enhance system capacity and diversity, etc. In this work, we address the challenge of HMIMO near field (NF) channel estimation, which is complicated by the intricate model introduced by the dyadic Green's function. Despite its complexity, the channel model is governed by a limited set of parameters. This makes parametric channel estimation highly attractive, offering substantial performance enhancements and enabling the extraction of valuable sensing parameters, such as user locations, which are particularly beneficial in mobile networks. However, the relationship between these parameters and channel gains is nonlinear and compounded by integration, making the estimation a formidable task. To tackle this problem, we propose a novel neural network (NN) assisted hybrid method. With the assistance of NNs, we first develop a novel hybrid channel model with a significantly simplified expression compared to the original one, thereby enabling parametric channel estimation. Using the readily available training data derived from the original channel model, the NNs in the hybrid channel model can be effectively trained offline. Then, building upon this hybrid channel model, we formulate the parametric channel estimation problem with a probabilistic framework and design a factor graph representation for Bayesian estimation. Leveraging the factor graph representation and unitary approximate message passing (UAMP), we develop an effective message passing-based Bayesian channel estimation algorithm. Extensive simulations demonstrate the superior performance of the proposed method. © 2025 IEEE.

关键词： Green's function

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Risk Analysis in Vehicle and Electric Scooter Interaction

Risk Analysis in Vehicle and Electric Scooter Interaction

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IEEE Symposium on Intelligent Vehicle

作者： Zhitong He Yiyang Guo Yaobin Chen Brian King Lingxi Li Transportation and Autonomous Systems Institute (TASI) Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis Indianapolis Indiana USA Los Altos High School Los Altos CA USA

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

The proliferation of shared micro-mobility services, including electric scooters (e-scooters), plays an important role in modern urban travel. Despite the growing popularity of e-scooters, their interactions with motor vehicles or pedestrians can lead to potential traffic accidents. In particular, the vehicle and e-scooter interaction (VEI) at intersections is of utmost importance to study, where the actions and intentions of e-scooter riders can vary greatly depending on the dynamic traffic situations. Moreover, due to the unique moving characteristics of e-scooters, drivers must maintain adequate awareness of the environment to mitigate unforeseen collision risks. In this paper, we aim to provide a novel risk analysis methodology to identify potential risky factors in the VEI process. Qualitative and quantitative analyses of various traffic situations are introduced to validate the functionality of the proposed system. The backtracking process algorithm (BPA) is also applied to demonstrate the effectiveness of the proposed framework.

关键词： Electric potential Backtracking Motorcycles Traffic control Tires Trajectory Risk analysis

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Towards Imbalanced Motion: Part-Decoupling Network for Video Portrait Segmentation

arXiv

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arXiv 2023年

作者： Yu, Tianshu Xia, Changqun Li, Jia State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China Peng Cheng Laboratory Shenzhen518055 China

Video portrait segmentation (VPS), aiming at segmenting prominent foreground portraits from video frames, has received much attention in recent years. However, simplicity of existing VPS datasets leads to a limitation on extensive research of the task. In this work, we propose a new intricate large-scale Multi-scene Video Portrait Segmentation dataset MVPS consisting of 101 video clips in 7 scenario categories, in which 10,843 sampled frames are finely annotated at pixel level. The dataset has diverse scenes and complicated background environments, which is the most complex dataset in VPS to our best knowledge. Through the observation of a large number of videos with portraits during dataset construction, we find that due to the joint structure of human body, motion of portraits is part-associated, which leads that different parts are relatively independent in motion. That is, motion of different parts of the portraits is imbalanced. Towards this imbalance, an intuitive and reasonable idea is that different motion states in portraits can be better exploited by decoupling the portraits into parts. To achieve this, we propose a Part-Decoupling Network (PDNet) for video portrait segmentation. Specifically, an Inter-frame Part-Discriminated Attention (IPDA) module is proposed which unsupervisedly segments portrait into parts and utilizes different attentiveness on discriminative features specified to each different part. In this way, appropriate attention can be imposed to portrait parts with imbalanced motion to extract part-discriminated correlations, so that the portraits can be segmented more accurately. Experimental results demonstrate that our method achieves leading performance with the comparison to state-of-the-art methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Large datasets

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Millimeter-Wave Agricultural Channel Measurements in Corn and Soybean Fields at Different Growth Stages

Millimeter-Wave Agricultural Channel Measurements in Corn an...

引用

2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Vuran, Mehmet C. Lunar, Mohammad Mosiur Nie, Shuai Ge, Yufeng Pitla, Santosh Bai, Geng Koksal, Can Emre University of Nebraska-Lincoln School of Computing LincolnNE68588 United States University of Nebraska-Lincoln Department of Biological Systems Engineering LincolnNE68583 United States Ohio State University Department of Electrical and Computer Engineering ColumbusOH43210 United States

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

Extensive agricultural field experiments in the millimeter-wave spectrum have been conducted for the first time in corn and soybean fields to study the impacts of crop type, crop growth stage, and antenna height on the path loss. Path loss analysis is conducted based on the field measurements and control experiment data. Based on experiments with over 6,860 data points collected over a five-month period in three crop fields, our results suggest that common crops, such as corn and soybean, impact the mmWave channel. The observations provide essential guidelines for the deployment of agricultural millimeter-wave wireless networks. © 2022 IEEE.

关键词： Millimeter waves

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Hybrid Multi-Agent Deep Reinforcement Learning for Active-IRS-Based Rate Maximization Over 6G UAV Mobile Wireless Networks

Hybrid Multi-Agent Deep Reinforcement Learning for Active-IR...

引用

MILCOM, Military Communications Conference

作者： Shuming Yi Fei Wang Xi Zhang College of Electronic and Information Engineering Southwest University Chongqing China Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA

Intelligent reflecting surface (IRS) can significantly improve unmanned aerial vehicle (UAV) communication qualities by reconfiguring or even optimizing wireless propagation environments. For active IRS (AIRS) enabled UAV-based mobile wireless networks, we aim to maximize the sum transmission rates of all IoT devices (IoTDs), by jointly optimizing the AIRSs’ phase shifts and amplification factors and UAV trajectory under the discrete IRS model. First, we formulate a sum transmission rate maximization problem for IoTDs, where all IoTDs can transmit data simultaneously by integrating the non-orthogonal multiple access (NOMA) and frequency division multiple access (FDMA) techniques. The formulated problem is non-convex because the coupled phase shifts and amplification factors are both discrete variables based on the discrete IRS model. Hence, we develop multi-agent deep reinforcement learning (MADRL) based schemes by integrating the deep deterministic policy gradient (DDPG) and Dueling Deep Q Network (Dueling DQN) techniques to derive the UAV trajectory and the amplification factors and phase shifts of AIRSs, respectively. Finally, we validate and evaluate the performances improvements of our developed MADRL-based schemes through extensive simulations.

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Embedded System Security Protocols: Latest Trends and Issues

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International Journal of High Speed Electronics and systems 2025年第3期34卷

作者： Han, Huimin Gulzar, Yonis Nizamani, Ahsan Ahmed Nizamani, Abdul Haseeb Ali, Sijjad Aslam Bhatti, Mughair Mechanical and Electrical Engineering College Hainan Vocational University of Science and Technology Haikou571126 China Department of Management Information Systems King Faisal University P.O. Box 380 Al-Ahsa31982 Saudi Arabia School of Computer Science and Engineering Central South University Changsha410083 China College of Computer Science and Software Engineering Shenzhen University Guandong Shenzhen China School of Geography Nanjing Normal University Jiangsu Nanjing China

Given the increasingly serious security threats faced by embedded systems, an analysis has been conducted on the characteristics and vulnerabilities of embedded systems. Detailed discussions are provided on security threats faced by embedded systems from two major aspects: hardware-based attacks such as side-channel attacks, hardware Trojans, fault injection, microprobes, and hardware reverse engineering, and software attacks aimed at damaging, tampering, and stealing. The analysis includes existing security measures both domestically and internationally, highlighting their shortcomings. Based on the concept of trusted computing, the paper offers future research suggestions from several perspectives, including theoretical research models, trusted measurement, trusted reporting, trusted sharing, and isolation of resources. Finally, an ideal comprehensive joint security enhancement scheme is proposed, and future research directions are discussed. © 2025 World Scientific Publishing Company.

关键词： Embedded software

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Learning to Control Linear systems can be Hard

arXiv

引用

arXiv 2022年

作者： Tsiamis, Anastasios Ziemann, Ingvar Morari, Manfred Matni, Nikolai Pappas, George J. Automatic Control Laboratory ETH Zurich Switzerland School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Department of Electrical and Systems Engineering University of Pennsylvania United States

In this paper, we study the statistical difficulty of learning to control linear systems. We focus on two standard benchmarks, the sample complexity of stabilization, and the regret of the online learning of the Linear Quadratic Regulator (LQR). Prior results state that the statistical difficulty for both benchmarks scales polynomially with the system state dimension up to system-theoretic quantities. However, this does not reveal the whole picture. By utilizing minimax lower bounds for both benchmarks, we prove that there exist non-trivial classes of systems for which learning complexity scales dramatically, i.e. exponentially, with the system dimension. This situation arises in the case of underactuated systems, i.e. systems with fewer inputs than states. Such systems are structurally difficult to control and their system theoretic quantities can scale exponentially with the system dimension dominating learning complexity. Under some additional structural assumptions (bounding systems away from uncontrollability), we provide qualitatively matching upper bounds. We prove that learning complexity can be at most exponential with the controllability index of the system, that is the degree of underactuation. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear systems

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基于侧基多通道和对称性破缺效应的分子电导调控

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Science China Materials 2024年第6期67卷 1994-1999页

作者：郝杰汪博宇赵璁霍雅妮王进莹贾传成郭雪峰 Center of Single-Molecule Sciences Institute of Modern OpticsFrontiers Science Center for New Organic MatterTianjin Key Laboratory of Micro-scale Optical Information Science and TechnologyCollege of Electronic Information and Optical EngineeringNankai UniversityTianjin 300350China Network for Computational Nanotechnology School of Electrical and Computer EngineeringPurdue UniversityIndiana 47907USA Beijing National Laboratory for Molecular Sciences National Biomedical Imaging CenterCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China

化学取代是有效调节分子电导,产生多通道输运、量子干涉效应和其他机制的关键方法.但分子骨架和侧基之间存在复杂的相互作用,目前仍未被研究清楚.在本工作中,我们结合扫描隧道显微镜裂结实验技术和第一性原理计算方法,深入研究了具有不... 详细信息

化学取代是有效调节分子电导,产生多通道输运、量子干涉效应和其他机制的关键方法.但分子骨架和侧基之间存在复杂的相互作用,目前仍未被研究清楚.在本工作中,我们结合扫描隧道显微镜裂结实验技术和第一性原理计算方法,深入研究了具有不同σ和π侧基的分子电导.实验结果及理论分析表明,σ侧基的加入引起了分子前线轨道的对称性破缺并加剧了分子内散射,从而导致电导的降低.相反,π侧基引入了额外的电荷传输通道,实现了电荷传输的多通道效应,增加了分子的电导.这些发现为未来分子功能化和分子电子器件的设计提供了坚实的基础.

关键词： side substituent multiple-channel effect symmetry-breaking effect single-molecule junction

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Spatial and Contextual Path Network for Image Inpainting

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Intelligent Automation & Soft Computing 2024年第2期39卷 115-133页

作者： Dengyong Zhang Yuting Zhao Feng Li Arun Kumar Sangaiah Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation Changsha University of Science and TechnologyChangsha410114China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China International Graduate Institute of AI National Yunlin University of Science and TechnologyYunlinTaiwan Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon

Image inpainting is a kind of use known area of information technology to repair the loss or damage to the *** feature extraction is the core of image *** enough space for information and a larger receptive field is very important to realize high-precision image ***,in the process of feature extraction,it is difficult to meet the two requirements of obtaining sufficient spatial information and large receptive fields at the same *** order to obtain more spatial information and a larger receptive field at the same time,we put forward a kind of image restoration based on space path and context path *** the space path,we stack three convolution layers for 1/8 of the figure,the figure retained the rich spatial *** the context path,we use the global average pooling layer,where the accept field is the maximum of the backbone network,and the pooling module can provide global context information for the maximum accept *** order to better integrate the features extracted from the spatial and contextual paths,we study the fusion module of the two *** fusionmodule first path output of the space and context path,and then through themass normalization to balance the scale of the characteristics,finally the characteristics of the pool will be connected into a feature vector and calculate the weight *** of images in order to extract context information,we add attention to the context path refinement *** modules respectively from channel dimension and space dimension to weighted images,in order to obtain more effective *** show that our method is better than the existing technology in the quality and quantity of themethod,and further to expand our network to other inpainting networks,in order to achieve consistent performance improvements.

关键词： Image inpainting attention deep learning convolutional network

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