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Multi-UAV Collaborative Mission Planning Method for Self-Organized Sensor Data Acquisition

computers, Materials & Continua 2024年第10期81卷 1529-1563页

作者： Shijie Yang Jiateng Yuan Zhipeng Zhang Zhibo Chen Hanchao Zhang Xiaohui Cui School of Information Science and Technology Beijing Forestry UniversityBeijing100083China Engineering Research Center for Forestry-Oriented Intelligent Information Processing of National Forestry and Grassland Administration Beijing100083China State Key Laboratory of Efficient Production of Forest Resources Beijing100083China Division of Biostatistics Department of Population HeathGrossman School of MedicineNew York UniversityNew YorkNY 10016USA

In recent years,sensor technology has been widely used in the defense and control of sensitive areas in cities,or in various scenarios such as early warning of forest fires,monitoring of forest pests and diseases,and protection of endangered *** sensors to collect data and then utilizing unmanned aerial vehicle(UAV)to collect the data stored in the sensors has replaced traditional manual data collection as the dominant *** current strategies for efficient data collection in above scenarios are still imperfect,and the low quality of the collected data and the excessive energy consumed by UAV flights are still the main problems faced in data *** regards this,this paper proposes a multi-UAV mission planning method for self-organized sensor data acquisition by comprehensively utilizing the techniques of self-organized sensor clustering,multi-UAV mission area allocation,and sub-area data acquisition scheme *** improvedα-hop clustering method utilizes the average transmission distance to reduce the size of the collection sensors,and the K-Dimensional method is used to form a multi-UAV cooperative workspace,and then,the genetic algorithm is used to trade-off the speed with the age of information(AoI)of the collected information and the energy consumption to form the multi-UAV data collection operation *** combined optimization scheme in paper improves the performance by 95.56%and 58.21%,respectively,compared to the traditional baseline *** order to verify the excellent generalization and applicability of the proposed method in real scenarios,the simulation test is conducted by introducing the digital elevation model data of the real terrain,and the results show that the relative error values of the proposed method and the performance test of the actual flight of the UAV are within the error interval of±10%.Then,the advantages and disadvantages of the present method with the existing mainstream schemes are tested,and

关键词： Unmanned aerial vehicle sensor self-organization path planning multi-UAV task assignment

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RW-STT: Random Walk Embedded Spatial-Temporal Transformer Networks for Traffic Flow Forecasting 3

RW-STT: Random Walk Embedded Spatial-Temporal Transformer Ne...

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3rd International Conference on Control Theory and Applications, ICoCTA 2023

作者： Kong, Weishan Ju, Yanni Luo, Jialan Wang, Jun Huang, Liwei School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Department of Road Traffic Management Sichuan Police College Luzhou China Intelligent Policing Key Laboratory of Sichuan Province Luzhou China School of Public Administration University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781839539824

Predicting traffic patterns is crucial for urban traffic management and planning, which predicts future traffic data based on current traffic conditions. To acquire better prediction accuracy, traffic flow forecasting requires complex dependencies in both temporal and spatial information. The spatial information is highly related to the traffic network, and how to effectively capture the relationships between graph nodes in the traffic network is crucial. To deal with this problem, we propose to utilize random walk embedding to capture the information transmission and correlations between nodes. Then, we combine random walk with transformer and propose random walk embedded spatial-temporal transformer (RWSTT) model to deal with the traffic flow forecasting problem. Experimental results on three traffic datasets demonstrate that RW-STT can capture more comprehensive correlations between spatial nodes and outperforms other baselines significantly. © The Institution of Engineering & technology 2023.

关键词： Forecasting

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PpNNT: Multiparty Privacy-Preserving Neural Network Training System

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第1期5卷 370-383页

作者： Feng, Qi He, Debiao Shen, Jian Luo, Min Choo, Kim-Kwang Raymond Wuhan University School of Cyber Science and Engineering Wuhan430072 China Shandong Provincial Key Laboratory of Computer Networks Jinan250014 China School of Information Science and Technology Zhejiang Sci-Tech University Hangzhou310018 China Shanghai Technology Innovation Centre of Distributed Privacy-Preserving Artificial Intelligence Matrix Elements Technologies Shanghai201204 China University of Texas at San Antonio Department of Information Systems and Cyber Security San AntonioTX78249 United States

By leveraging smart devices [e.g., industrial Internet of Things (IIoT)] and real-time data analytics, organizations, such as production plants can benefit from increased productivity, reduced costs, enhanced self-monitoring, and autonomous decision-making. In such a setting, machine learning plays an important role in data analytics, but the use of conventional centralized machine learning solutions may raise uncomfortable concerns about data privacy. Hence, one can explore the use of federated learning. In this article, we propose privacy-preserving deep neural network training (PpNNT), which is designed to support federated learning in the multiparty setting. To minimize the overall costs, we further design a hybrid architecture to fully maximize resource utilization. Our proposed design allows the PpNNT system to provide high security, efficiency, and scalability for IIoT data analytics, as evidenced by our theoretical security proof and experimental results on the CIFAR10 dataset. © 2020 IEEE.

关键词： Decision making

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Finite-time tracking control of heterogeneous multi-AUV systems with partial measurements and intermittent communication

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science China(Information sciences) 2024年第5期67卷 165-182页

作者： Bo CHEN Jiangping HU Bijoy Kumar GHOSH School of Automation Engineering University of Electronic Science and Technology of China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Yangtze Delta Region Institute (Huzhou) University of Electronic Science and Technology of China Department of Mathematics and Statistics Texas Tech University

The development of a distributed trajectory-tracking control strategy that is independent of velocity measurements is critical to achieving finite-time tracking control of autonomous underwater vehicle(AUV) systems. In this study, a group of heterogeneous AUV systems with intermittent communication links is considered and a finite-time trajectory-tracking control strategy is developed. The strategy includes two observers and one controller proposed for each follower-AUV. The first observer, a hybrid finite-time observer,estimates the state of the leader, whereas the second observer, which relies only on the position measurement,is proposed to estimate the states of the follower-AUV itself. In addition, a distributed trajectory-tracking controller is designed using the states estimated by the intermittent communication network even without velocity measurements. A homogeneous technique is utilized to prove that all followers can track the leader in a finite time. Finally, the effectiveness of the developed finite-time tracking control strategy is illustrated by numerical simulations.

关键词： distributed observer finite-time tracking homogeneous technique intermittent communication multiple heterogeneous AUVs

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Photo-induced flexible semiconductor CdSe/CdS quantum rods alignment

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Journal of Semiconductors 2023年第9期44卷 83-89页

作者： Wanlong Zhang Julian Schneider Maksym F.Prodanov Valerii V.Vashchenko Andrey L.Rogach Xiaocong Yuan Abhishek K.Srivastava Nanophotonics Research Center Institute of Microscale OptoelectronicsShenzhen UniversityShenzhen 518060China State Key Laboratory of Advanced Displays and Optoelectronics Technologies Department of Electronic&Computer EngineeringHong Kong University of Science and TechnologyHong Kong SARChina Department of Materials Science and Engineering and Centre for Functional Photonics(CFP) City University of Hong KongHong Kong SARChina

The anisotropic absorption and emission from semiconductor CdSe/CdS quantum rods(QRs)provide extra benefits among other photoluminescence *** photo-induced alignment technique,the QRs can be oriented in liquid crystal polymer matrix at a large *** this article,a 2D Dammann grating pattern,within“SKL”characters domains aligned QRs in composite film,was fabricated by multi-step photo exposure using several photo masks,and a continuous geometric lens profile pattern aligned QRs was realized by the single step polarization converting holographic irradiation *** polarized optical microscope and fluorescence microscope are employed to determine the liquid crystal director profiles and QRs anisotropic excitation *** have been able to orient the QRs in fine binary and continuous patterns that confirms the strong quantum rod aligning ability of the proposed ***,the proposed approach paves a way for photoinduced flexible QRs alignments to provide a highly specific and difficult-to-replicate security application at a large scale.

关键词： quantum rods photo alignment liquid crystal flexible alignment polarized emission

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LiDAR Road-Atlas: An Efficient Map Representation for General 3D Urban Environment

Field Robotics

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Field Robotics 2025年 3卷 435-459页

作者： Banghe Wu Chengzhong Xu Hui Kong School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing Jiangsu China The State Key Laboratory of Internet of Things for Smart City (SKL-IOTSC) Department of Computer Science University of Macau Macau The State Key Laboratory of Internet of Things for Smart City (SKL-IOTSC) Department of Electromechanical Engineering (EME) University of Macau Macau

In this work, we propose the LiDAR Road-Atlas, a compact and efficient 3D map representation, for autonomous robot or vehicle navigation in a general urban environment. The LiDAR Road-Atlas can be generated by an online mapping framework which incrementally merges local 2D occupancy grid maps (2D-OGMs). Specifically, the contributions of our method are threefold. First, we solve the challenging problem of creating local 2D-OGMs in nonstructured urban scenes based on a real-time delimitation of traversable and curb regions in a LiDAR point cloud. Second, we achieve accurate 3D mapping in multiple-layer urban road scenarios by a probabilistic fusion scheme. Third, we achieve a very efficient 3D map representation of a general environment thanks to the automatic local-OGM-induced traversable-region labeling and a sparse probabilistic local point-cloud encoding. Given the LiDAR Road-Atlas, one can achieve accurate vehicle localization, path planning, and some other tasks. Our map representation is insensitive to dynamic objects which can be filtered out in the resulting map based on a probabilistic fusion. Empirically, we compare our map representation with a couple of popular map representations in robotics society, and our map representation is more favorable in terms of efficiency, scalability, and compactness. Additionally, we also evaluate localization performance given the LiDAR Road-Atlas representations on two public datasets. With a 16-channel LiDAR sensor, our method achieves an average global localization error of 0.26 m (translation) and 1.07° (rotation) on the Apollo dataset, and 0.89 m (translation) and 1.29° (rotation) on the MulRan dataset, respectively, at 10 Hz, which validates its promising performance. The code for this work is open-sourced at https://***/IMRL/Lidar-road-atlas.

关键词： Three-dimensional displays Roads Laser radar Robots Navigation Semantics Location awareness Autonomous vehicles Robot kinematics Cameras

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Transcriptomic analysis of Andrias davidianus meat and experimental validation for exploring its bioactive components as functional foods

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Food science and Human Wellness 2024年第1期13卷 166-172页

作者： Changge Guan Zhenglin Tan Shucheng Li Yi Wang Naoyuki Yamamoto Chong Zhang Songjun Wang Junjie Chen Xinhui Xing Key Laboratory for Industrial Biocatalysis Ministry of Education of ChinaDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China School of Life Science and Technology Tokyo Institute of TechnologyYokohama 226-0026Japan Sensing System Research Center National Institute of Advanced Industrial Science and TechnologyTsukuba 305-8565Japan Center for Synthetic and Systems Biology Tsinghua UniversityBeijing 100084China Henan Giant Salamander Protection and Development Association Luoyang 471000China Intelligent Computing Research Center Harbin Institute of TechnologyShenzhen 518071China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate SchoolShenzhen 518055China Institute of Biomedical Health Technology and Engineering Shenzhen Bay LaboratoryShenzhen 518067China

Andrias davidianus(Chinese giant salamander,CGS)is the largest and oldest extant amphibian species in the world and is a source of prospective functional food in ***,the progress of functional peptides mining was slow due to lack of reference genome and protein sequence *** this study,we illustrated full-length transcriptome sequencing to interpret the proteome of CGS meat and obtain 10703 coding DNA *** functional annotation and amino acid composition analysis,we have discovered various genes related to signal transduction,and 16 genes related to *** have also found vast variety of functional peptides through protein coding sequence(CDS)analysis by comparing the data obtained with the functional peptide ***-Pro-Ile predicted by the CDS analysis was released from the CGS meat through enzymatic hydrolysis,suggesting that our approach is *** study suggested that transcriptomic analysis can be used as a reference to guide polypeptide mining in CGS meat,thereby providing a powerful mining strategy for the bioresources with unknown genomic and proteomic sequences.

关键词： Chinese giant salamander Transcriptomic analysis Bioactive components Functional peptides mining

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A Proactive Selection Method for Dynamic Access Points Grouping in User-centric UDN

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China Communications 2021年第4期18卷 153-165页

作者： Bo Hu Fangxia Zuo Chuan’anWang Shanzhi Chen State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China Department of Computer Science Anhui Science and Technology UniversityAnhui 233100China State Key Laboratory of Wireless Mobile Communications China Academy of Telecommunication TechnologyBeijing 100191China

Network densification is a promising solution to fulfill network capacity requirement and transmission rate for beyond 5G and 6G wireless ***-dense network(UDN)integrates heterogeneous network resources and coordinates technologies on quality of service controlling,to provide users with flexible ***,dense deployment reduces coverage radius of the cell,resulting in an increase on handover frequency,which makes a serious impact on service *** this paper,we propose a proactive selection method for dynamic access points grouping(DAPGing)in accordance with“user-centric”philosophy,which selects target Access Points(AP)and reduces handover times to ensure communication *** method includes two criteria:1)the user’s sojourn time,which is determined by analyzing the AP coverage area;2)neighbor relationship between APs,which is determined by coverage area and signal strength characteristics between neighboring ***,candidate APs become the proactive selected ones to update the AP *** geometry is used to build system model and performance metrics are analyzed,including AP group coverage probability and average update *** analysis shows that the proposed proactive selection method brings similar coverage probability to traditional handover method,while average update frequency is reduced more than 20%selection criteria.

关键词： proactive selection user-centric ultradense network stochastic geometry model

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Mechanical Design with Experimental Verification of a Lightweight Exoskeleton Chair

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Journal of Bionic Engineering 2021年第2期18卷 319-332页

作者： Zihao Du Zefeng Yan Tiantian Huang Ou Bai Qin Huang Bin Han State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Human Cyber-Physical Systems Laboratory Department of Electrical and Computer EngineeringFlorida International UniversityMiami 33174USA Department of Rehabilitation Medicine Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China

In this study,a human-chair model was developed as the basis for a wearable-chair design.A prototype chair,HUST-EC,based on the model was fabricated and *** the optimization under the golden divisional method,an optimized simulation of the operating mode with the lowest chair height was implemented.A novel multi-link support structure has been established with parameters optimized using Matlab *** stress analysis of the solid models was conducted to ensure the adequate support from the designed chair for the *** subjects participated in the evaluation experiment,who performed both static tasks and dynamic *** experimental results consisted of subjective evaluation and objective *** experimental data demonstrate that(1)the HUST-EC can effectively reduce the activation level of related muscles at a variety of tasks;(2)the plantar pressure was reduced by 54%–67%;(3)the angle between the upper body and the vertical axis was reduced by 59%–77%;(4)the subjective scores for chair comfortability,portability,and stability were all higher than *** results further revealed that the designed chair can reduce the musculoskeletal burden and may improve work efficiency.

关键词： exoskeleton wearable chair bionic robot mechanism design ergonomics

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RoadFormer: Duplex Transformer for RGB-Normal Semantic Road Scene Parsing

arXiv

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arXiv 2023年

作者： Li, Jiahang Zhang, Yikang Yun, Peng Zhou, Guangliang Chen, Qijun Fan, Rui The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China The Department of Computer Science and Engineering The Hong Kong University of Science and Technology Hong Kong

The recent advancements in deep convolutional neural networks have shown significant promise in the domain of road scene parsing. Nevertheless, the existing works focus primarily on freespace detection, with little attention given to hazardous road defects that could compromise both driving safety and comfort. In this article, we introduce RoadFormer, a novel Transformer-based data-fusion network developed for road scene parsing. RoadFormer utilizes a duplex encoder architecture to extract heterogeneous features from both RGB images and surface normal information. The encoded features are subsequently fed into a novel heterogeneous feature synergy block for effective feature fusion and recalibration. The pixel decoder then learns multi-scale long-range dependencies from the fused and recalibrated heterogeneous features, which are subsequently processed by a Transformer decoder to produce the final semantic prediction. Additionally, we release SYN-UDTIRI, the first large-scale road scene parsing dataset that contains over 10,407 RGB images, dense depth images, and the corresponding pixel-level annotations for both freespace and road defects of different shapes and sizes. Extensive experimental evaluations conducted on our SYN-UDTIRI dataset, as well as on three public datasets, including KITTI road, CityScapes, and ORFD, demonstrate that RoadFormer outperforms all other state-of-the-art networks for road scene parsing. Specifically, RoadFormer ranks first on the KITTI road benchmark. Our source code, created dataset, and demo video are publicly available at ***/RoadFormer. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantic Segmentation

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