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arXiv 2023年

作者： Zhang, Biru Wang, Jiankun Meng, Max Q.-H. Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China

Multi-robot path planning is a computational process involving finding paths for each robot from its start to the goal while ensuring collision-free operation. It is widely used in robots and autonomous driving. However, the computational time of multi-robot path planning algorithms is enormous, resulting in low efficiency in practical applications. To address this problem, this article proposes a novel multi-robot path planning algorithm (Multi-Agent Rapidly-exploring Random Disjointed-Trees*, MA-RRdT*) based on multi-tree random sampling. The proposed algorithm is based on a single-robot path planning algorithm (Rapidly-exploring Random disjointed-Trees*, RRdT*). The novel MA-RRdT* algorithm has the advantages of fast speed, high space exploration efficiency, and suitability for complex maps. Comparative experiments are completed to evaluate the effectiveness of MA-RRdT*. The final experimental results validate the superior performance of the MA-RRdT* algorithm in terms of time cost and space exploration efficiency. Copyright © 2023, The Authors. All rights reserved.

关键词： Space research

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Bringing sensation to prosthetic hands-chronic assessment of implanted thin-film electrodes in humans

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npj Flexible Electronics 2023年第1期7卷 32-45页

作者： PaulČvančara Giacomo Valle Matthias Müller Inga Bartels Thomas Guiho Arthur Hiairrassary Francesco Petrini Stanisa Raspopovic Ivo Strauss Giuseppe Granata Eduardo Fernandez Paolo M.Rossini Massimo Barbaro Ken Yoshida Winnie Jensen Jean-Louis Divoux David Guiraud Silvestro Micera Thomas Stieglitz Laboratory for Biomedical Microtechnology Department of Microsystems Engineering-IMTEKAlbert-Ludwig-University FreiburgFreiburgGermany Center for Neuroprosthetics and Institute of Bioengineering School of EngineeringÉcole Polytechnique Fédérale de Lausanne(EPFL)LausanneSwitzerland The Biorobotics Institute Scuola Superiore Sant’AnnaPisaItaly Camin Team INRIAUniversity of MontpellierMontpellierFrance Institute of Neurology Catholic University of the Sacred HeartRomaItaly Institute of Neurosurgery Catholic University of the Sacred HeartRomaItaly Department of Neuroscience&Neurorehabilitation IRCCS San Raffaele Roma00166 RomeItaly Department of Electrical and Electronic Engineering University of CagliariCagliariItaly Biomedical Engineering Department Indiana University-Purdue UniversityIndianapolisINUSA SMI Dept.Health Science and TechnologyAalborg UniversityAalborgDenmark AXONIC/Groupe MXM VallaurisFrance BrainLinks-BrainTools Albert-Ludwig-University FreiburgFreiburgGermany Bernstein Center Freiburg Albert-Ludwig-University FreiburgFreiburgGermany Present address:Laboratory for Neuroengineering Department of Health Sciences and TechnologyInstitute for Robotics and Intelligent SystemsETH ZürichZürichSwitzerland

Direct stimulation of peripheral nerves with implantable electrodes successfully provided sensory feedback to amputees while using hand *** of the electrodes is key to success,which we have improved for the polyimide-based transverse intrafascicular multichannel electrode(TIME).The TIMEs were implanted in the median and ulnar nerves of three trans-radial amputees for up to six *** present a comprehensive assessment of the electrical properties of the thin-film metallization as well as material status post *** TIMEs stayed within the electrochemical safe limits while enabling consistent and precise amplitude *** lead to a reliable performance in terms of eliciting *** signs of corrosion or morphological change to the thin-film metallization of the probes was observed by means of electrochemical and optical *** presented longevity demonstrates that thin-film electrodes are applicable in permanent implant systems.

关键词： film electrodes sensation

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Joint Beamforming and Resource Allocation for Integrated Satellite-Terrestrial Networks

Joint Beamforming and Resource Allocation for Integrated Sat...

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IEEE International Conference on Communications (ICC)

作者： Girim Kwon Wonjae Shin Andrea Conti William C. Lindsey Moe Z. Win Wireless Information and Network Sciences Laboratory Massachusetts Institute of Technology Cambridge MA USA Department of Electrical and Computer Engineering Ajou University Gyeonggi-do South Korea Department of Engineering and CNIT University of Ferrara Ferrara Italy Ming Hsieh Department of Electrical Engineering University of Southern California Los Angeles CA USA

Integrated satellite-terrestrial networks (ISTNs) are essential for providing ubiquitous mobile ultra-broadband service in beyond 5G networks. The spectral efficiency and reliability of ISTN depend on the integrated architecture and its operational strategies including interference management and resource allocation. Our view is to integrate terrestrial access and satellite backhaul networks and to develop an optimization technique for their joint operation. This paper proposes an efficient integrated access and backhaul (IAB) architecture for satellite-terrestrial networks (STNs) based on reverse time division duplexing (TDD) considering both uplink (UL) and downlink (DL). In particular, in-band backhauling and gNodeB (gNB) cooperation are considered for high spectral efficiency and reliability. A framework for joint optimization of cooperative beamforming and resource allocation is developed to maximize the UL-DL rate region of the in-band IAB. The proposed scheme is verified using the 3rd Generation Partnership Project (3GPP) standard channel models. Results show that the proposed scheme significantly outperforms the conventional wireless backhauling, while approaching to an outer bound of the UL-DL rate region.

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Internet of Digital Twin: Framework, Applications and Enabling Technologies

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IEEE Communications Surveys and Tutorials 2025年

作者： Liu, Ruhan Luan, Tom H. Qu, Youyang Xiang, Yong Gao, Longxiang Zhao, Dongmei Deakin University School of Info Technology MelbourneVIC3125 Australia Xi'an Jiaotong University School of Cyber Science and Engineering Shaanxi Xi'an710049 China Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computing Power Internet and Service Computing Jinan China McMaster University Department of Electrical and Computer Engineering HamiltonON Canada

Intelligent physical systems, such as smart vehicles and robotic arms, are increasingly integrated into both industrial and everyday applications. However, the systems typically face hardware limitations that constrain their computational capacities. Digital twin systems offer a solution by creating real-time digital replicas of physical systems that enhance computational efficiency, overcoming physical limitations. Moreover, multiple digital twins that hold complementary knowledge can conveniently collaborate to share information and computational resources, further improving the performance of physical systems by forming an Internet of Digital Twin (IoDT). This paper presents a comprehensive investigation of the digital twin network, tracing the evolution of digital twins and providing a classification of the key technologies, functional frameworks, and application domains of IoDT. This paper delves into the IoDT communication framework by studying the fundamental communication modes of IoDT, exploring its integration with advanced technologies such as edge computing, blockchain, 5G/6G networks, and machine learning to facilitate data transmission, interaction, and omni-directional sensing. By offering a broad perspective, the paper aims to deepen stakeholders' understanding of current research and potential future developments, encouraging further exploration of IoDT technologies and their evolution. © 1998-2012 IEEE.

关键词： 5G mobile communication systems

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Automating smart Internet of Things devices in modern homes using context-based fuzzy logic

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Computational Intelligence 2024年第1期40卷

作者： Ming, Chen Kadry, Seifedine Dasel, A. Antony Hubei Key Laboratory of Power System Design and Test for Electrical Vehicle Hubei University of Arts and Science Xiangyang China School of Automotive and Traffic Engineering Hubei University of Arts and Science Xiangyang China Department of Mathematics and Computer Science Beirut Arab University Beirut Lebanon Department of Mechanical Engineering VIT University Vellore India

Internet of Things (IoT) is mainly used to connect different embedded objects over the internet to make communication between them possible. With the help of IoT, devices find a way to interact, work together, and study from each other's experiences just like humans do. IoT finds its way in applications such as smart home, smart city, healthcare, agriculture, and so on. The name smart home arises due to the automation of the normal home appliances to make it smart. When the devices of the normal smart home are connected via the internet, they become a part of the IoT. The smart home should ensure the following characteristics such as security, comfort, convenience, and energy saving. The article presents a technique for IoT controlled devices in a smart home using context-based fuzzy logic. Fuzzy logic is mainly used to monitor and analyze the real-time data collected from the sensors in the smart homes from various environments. Context-based fuzzy logic uses a multivalued logic principle which differs from the normal Boolean logic, where the truth value lies between only zero and one (ie, true or false). The proposed smart home is implemented in a real case scenario where it yields an accuracy of 90.5%, response time of 6.41 milliseconds, and an F-measure of 97%. © 2020 Wiley Periodicals LLC.

关键词： Internet of things

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2021 Monthly Rice Production in Chinese Coastal Provinces 3

2021 Monthly Rice Production in Chinese Coastal Provinces

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3rd International Conference on Big Data Analytics and Practices, IBDAP 2022

作者： Parmar, Ajeet Munasinghe, Thilanka Tubbs, Heidi Anyamba, Assaf Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering Troy United States Rensselaer Polytechnic Institute Department of Information Technology and Web Science Troy United States Oak Ridge National Laboratory Geospatial Science and Human Security Division Oak Ridge United States

ISBN: (数字)9781665469388

ISBN: (纸本)9781665469388

This paper explores the dynamics of rice production in the Chinese provinces of Liaoning, Jilin, Heilongjiang, Shanghai, Jiangsu, and Zhejiang and seeks to predict monthly rice production in the months of April through October using precipitation and Normalized Difference Vegetation Index as the predictor variables available. We utilize ridge and lasso regression models to predict the rice yield. Results indicate that a lasso regression model with an R2 value of 0.9991501 with an adjusted R2 value of 0.9991502 and a ridge regression model with an R2 value of 0.9865443 with an adjusted R2 value of 0.9870637 are possible. The lasso regression model does not account for all predictor variables while the ridge regression model does. Both models could be expanded upon to include more observations. © 2022 IEEE.

关键词： Regression analysis

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A Collaborative Resequencing Approach Enabled by Multi-Core Prea for a Multi-Stage Automotive Flow Shop

SSRN

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SSRN 2023年

作者： Yang, Miao Li, Congbo Tang, Ying Wu, Wei Zhang, Xu State Key Laboratory of Mechanical Transmission College of Mechanical and Vehicle Engineering Chongqing University Chongqing400044 China Department of Electrical and Computer Engineering Rowan University GlassboroNJ08028 United States

The production sequences on a multi-stage automotive flow shop (MSAFS) have chance to be disturbed by emergency orders from the market or warehouses. This kind of dynamic disturbance burdens the timely resequencing, and an improper resequencing scheme would increase the total production cost and makespan. To tackle this problem, an collaborative resequencing approach of a MSAFS is proposed enabled by a multi-core promising-region evolutionary algorithm (PREA) to deal with emergency orders for an effective and efficient resequencing during the automotive production. First, considering the characteristics of automotive production, a collaborative resequencing strategy based on the sliding window is proposed in response to emergency orders. Then, a mathematical model that integrates the welding, painting, and assembly processes is developed with the objectives of minimizing production cost and delivery delay. Next, a multi-core PREA is developed to optimize the collaborative resequencing model in effect. Finally, a case study is conducted to verify the feasibility and superiority of the proposed approach. The numerical results reveal that the proposed approach is capable to realize an effective resequencing optimization for handling emergency orders in automotive production with high computational performance. © 2023, The Authors. All rights reserved.

关键词： Evolutionary algorithms

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Exciton-activated effective phonon magnetic moment in monolayer MoS2

arXiv

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arXiv 2024年

作者： Tang, Chunli Ye, Gaihua Nnokwe, Cynthia Fang, Mengqi Xiang, Li Mahjouri-Samani, Masoud Smirnov, Dmitry Yang, Eui-Hyeok Wang, Tingting Zhang, Lifa He, Rui Jin, Wencan Department of Electrical and Computer Engineering Auburn University AuburnAL36849 United States Department of Physics Auburn University AuburnAL36849 United States Department of Electrical and Computer Engineering Texas Tech University LubbockTX79409 United States Department of Mechanical Engineering Stevens Institute of Technology HobokenNJ07030 United States National High Magnetic Field Laboratory TallahasseeFL32310 United States Phonon Engineering Research Center of Jiangsu School of Physics and Technology Nanjing Normal University Nanjing210023 China

Optical excitation of chiral phonons plays a vital role in studying the phonon-driven magnetic phenomena in solids. Transition metal dichalcogenides host chiral phonons at high symmetry points of the Brillouin zone, providing an ideal platform to explore the interplay between chiral phonons and valley degree of freedom. Here, we investigate the helicity-resolved magneto-Raman response of monolayer MoS2 and identify a doubly degenerate Brillouin-zone-center chiral phonon mode at ∼270 cm−1. Our wavelength- and temperature-dependent measurements show that this chiral phonon is activated through the resonant excitation of A exciton. Under an out-of-plane magnetic field, the chiral phonon exhibits giant Zeeman splitting, which corresponds to an effective magnetic moment of ∼2.5µB. Moreover, we carry out theoretical calculations based on the morphic effects in nonmagnetic crystals, which reproduce the linear Zeeman splitting and Raman cross-section of the chiral phonon. Our study provides important insights into lifting the chiral phonon degeneracy in an achiral covalent material, paving a new route to excite and control chiral phonons. © 2024, CC BY.

关键词： Phonons

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Enhancing the multi-Tone continuous-wave lidar with phase detection

Enhancing the multi-Tone continuous-wave lidar with phase de...

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2021 Industrial Optical Devices and Systems, ODS 2021

作者： Bayer, M. Mert Guentchev, George N. Li, Xun Velazco, Jose E. Boyraz, Ozdal Electrical Engineering and Computer Science Department University of California IrvineCA92697 United States Jet Propulsion Laboratory PasadenaCA91109 United States

ISBN: (数字)9781510644953

ISBN: (纸本)9781510644946

Over the past years, light detection and ranging (lidar) technologies have been investigated and commercialized for various applications such as autonomous vehicles, terrestrial mappings, and precision measurements. Currently, the frequently used ranging methods are the pulsed time of flight (PToF) and frequency modulated continuous wave (FMCW) lidars that relies on frequency sweeping to capture range and velocity information. We have previously developed and demonstrated the multi-Tone continuous wave (MTCW) that operates by employing amplitude modulation via multiple radio frequencies (RF) and coherent detection. Here, we present a theoretical and experimental study on phase-based MTCW lidar that can detect the range and velocity of objects with arbitrary velocities. The experiments demonstrate that the phase and frequency of the Doppler-shifted fixed RF tones can be used to extract the range and velocity information in a single shot measurement. We show that a © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Optical radar

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Learning-Based Low-Latency Collaborative Inference for Multi-Branch Models in D2D-Assisted MEC

Learning-Based Low-Latency Collaborative Inference for Multi...

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2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Guo, Kai Xiao, Yilin Lu, Xiaozhen Xiao, Liang Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China School of Science and Engineering The Chinese University of HongKong Shenzhen China Peng Cheng Laboratory Shenzhen China College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics Nanjing China Xiamen University Department of Information and Communication Engineering Xiamen China

ISBN: (纸本)9798350368369

Deploying high-complexity deep neural network (DNN) on mobile devices presents significant challenges, stemming from the conflict between their computationally intensive demands and the constrained computational resources. Device-to-device (D2D) assisted mobile edge computing (MEC) exploits sharing resources among devices to perform DNN inference collaboratively for higher efficiency. However, most existing collaborative inference schemes ignore the structure of DNN models, thus suffering from high latency under dynamic network conditions and computational loads. In this paper, we propose a learning-based low-latency collaborative inference scheme for multi-branch models, which schedules the computations of each DNN layer to optimize the alignment between the DNN structure's characteristics and the D2D network environments. Specifically, the computational task of each branch is assigned to nearby mobile devices or the edge server for efficient collaboration. In addition, we design proximal policy optimization with task-specific architecture to choose the computational scheduling policy, which contains a two-stream NN to extract features from the D2D network and the tasks at each layer, as well as a multi-head output to obtain the collaborative devices for all tasks in the layer. Simulation results show that the proposed scheme reduces the inference latency compared with benchmarks. © 2025 IEEE.

关键词： Reinforcement learning

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