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作者： Su, Bo Ying Wei, Zhongqi McCann, James Yuan, Wenzhen Liu, Changliu Department of Electrical and Computer Engineering Carnegie Mellon University PittsburghPA15213 United States Department of Mechanical Engineering Carnegie Mellon University PittsburghPA15213 United States Robotics Institute Carnegie Mellon University PittsburghPA15213 United States

Tactile skins made from textiles enhance the robot–human interaction by localizing contact points and measuring contact forces. This paper presents a solution for rapidly fabricating, calibrating, and deploying these skins on industrial robot arms. The novel automated skin calibration procedure maps skin locations to robot geometry and calibrates contact force. Through experiments on a FANUC LR Mate 200id/7L industrial robot, we demonstrate that tactile skins made from textiles can be effectively used for human–robot interaction in industrial environments, and can provide unique opportunities in robot control and learning, making them a promising technology for enhancing robot perception and interaction. © 2023 by ASME.

关键词： Calibration

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Organoid intelligence:Integration of organoid technology and artificial intelligence in the new era of in vitro models

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Medicine in Novel Technology and Devices 2024年第1期21卷 39-44页

作者： Huaiyu Shi Andrew Kowalczewski Danny Vu Xiyuan Liu Asif Salekin Huaxiao Yang Zhen Ma Department of Biomedical&Chemical Engineering Syracuse UniversitySyracuseNYUSA BioInspired Institute for Material and Living Systems Syracuse UniversitySyracuseNYUSA Department of Mechanical&Aerospace Engineering Syracuse UniversitySyracuseNYUSA Department of Electrical Engineering&Computer Science Syracuse UniversitySyracuseNYUSA Department of Biomedical Engineering University of North TexasDentonTXUSA

Organoid Intelligence ushers in a new era by seamlessly integrating cutting-edge organoid technology with the power of artificial ***,three-dimensional miniature organ-like structures cultivated from stem cells,offer an unparalleled opportunity to simulate complex human organ systems in *** the convergence of organoid technology and AI,researchers gain the means to accelerate discoveries and insights across various *** intelligence algorithms enable the comprehensive analysis of intricate organoid behaviors,intricate cellular interactions,and dynamic responses to *** synergy empowers the development of predictive models,precise disease simulations,and personalized medicine approaches,revolutionizing our understanding of human development,disease mechanisms,and therapeutic *** Intelligence holds the promise of reshaping how we perceive in vitro modeling,propelling us toward a future where these advanced systems play a pivotal role in biomedical research and drug development.

关键词： Organoids Machinelearning Deep learning Artificial intelligence Stem cells

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Fourier Imager Network(FIN):A deep neural network for hologram reconstruction with superior external generalization

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Light(Science & Applications) 2022年第9期11卷 2225-2234页

作者： HANLONG CHEN LUZHE HUANG TAIRAN LIU AYDOGAN OZCAN Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California Nano Systems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USAElectrical and Computer Engineering DepartmentUniversity of CaliforniaLos AngelesCA 90095USA David Geffen School of Medicine University of California Los AngelesLos AngelesCA 90095USA

Deep learning-based image reconstruction methods have achieved remarkable success in phase recovery and holographic ***,the generalization of their image reconstruction performance to new types of samples never seen by the network remains a *** we introduce a deep learning framework,termed Fourier Imager Network(FIN),that can perform end-to-end phase recovery and image reconstruction from raw holograms of new types of samples,exhibiting unprecedented success in external *** architecture is based on spatial Fourier transform modules that process the spatial frequencies of its inputs using learnable filters and a global receptive *** with existing convolutional deep neural networks used for hologram reconstruction,FIN exhibits superior generalization to new types of samples,while also being much faster in its image inference speed,completing the hologram reconstruction task in~0.04 s per 1 mm^(2) of the sample *** experimentally validated the performance of FIN by training it using human lung tissue samples and blindly testing it on human prostate,salivary gland tissue and Pap smear samples,proving its superior external generalization and image reconstruction *** holographic microscopy and quantitative phase imaging,FIN and the underlying neural network architecture might open up various new opportunities to design broadly generalizable deep learning models in computational imaging and machine vision fields.

关键词： field. generalization holographic

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Safe-By-Design Digital Twins for Human-Robot Interaction: A Use Case for Humanoid Service Robots

Safe-By-Design Digital Twins for Human-Robot Interaction: A ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jon Škerlj Mazin Hamad Jean Elsner Abdeldjallil Naceri Sami Haddadin Department of Computer Engineering School of Computation Information and Technology Chair of Robotics and Systems Intelligence Munich Institute of Robotics and Machine Intelligence Technical University of Munich (TUM)

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Integrating humanoid service mobile robots into human environments presents numerous challenges, primarily concerning the safety of interactions between robots and humans. To address these safety concerns, we propose a novel approach that leverages the capabilities of digital twin technology by tailoring it to incorporate comprehensive and robust safety concepts. This paper introduces a "safe-by-design" digital twin that operates alongside the real twin robot in the loop, engaging real-time safety framework during physical interactions with the surrounding environment, including *** validate the effectiveness of our proposed safe-by-design digital twin framework, we conducted experiments using a humanoid service mobile robot alongside simulated human counterparts. Our results demonstrate the capability of the integrated impact safety module within the proposed digital twin approach to limit the velocities of both the robot’s base and arms, adhering to injury biomechanics-based safety thresholds. These findings emphasize the promise of our proposed approach for ensuring the physical safety of humanoid service mobile robots operating in dynamic human environments. It enables the digital twin to preemptively identify potential safety hazards and formulate safe intervention actions to ensure the robot’s compliance with safety regulations, paving the way for safer and more widespread adoption of robotic systems in various service domains.

关键词： Service robots Tracking Humanoid robots Human-robot interaction Robot sensing systems Safety Digital twins

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Impact of UAV Body Dynamics on Coverage Probability in 5G FR2

Impact of UAV Body Dynamics on Coverage Probability in 5G FR...

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IEEE Conference on Wireless Communications and Networking

作者： Pawan Srivastava Rajesh Kumar Samantaray M. P. R. S. Kiran Department of Electrical Engineering Connected Intelligence Lab IDRP on Robotics and Mobility Systems Indian Institute of Technology Jodhpur Rajasthan India

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

The next-generation wireless communication technologies, such as 5G Frequency Range 2 (FR2), WLANs, etc., are utilizing the millimeter-wave (mmWave) spectrum for increased data rates. For example, applications involving unmanned aerial vehicles (UAVs) for coverage extension in 5G comprise a huge amount of user data to be transmitted to the gNodeB (gNB). Hence, utilizing mmWave communication technologies such as 5G FR2 to establish the link between the UAV and gNB can be a suitable option. However, one of the critical technologies of 5G FR2 is the utilization of directional beamforming, and the impact of the axial unsteadiness of UAV s on the coverage needs to be carefully analyzed. This paper studies and models the effect of beam misalignment manifested due to axial disturbances in UAVs while hovering at a fixed altitude on the network performance. Firstly, a stochastic model for beam misalignment is developed by collecting real-time inertial data from a hovering UAV over multiple flights. Second, an analytical formulation of the coverage probability in a directional UAV to gNB mmWave communication link is formulated. The performance analysis shows that the analytical model matches the simulation outcomes with less than 2% error.

关键词： Wireless communication 5G mobile communication Millimeter wave technology Stochastic processes Autonomous aerial vehicles Real-time systems Performance analysis

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A Bi-population Cooperative Optimization Algorithm Assisted by an Autoencoder for Medium-scale Expensive Problems

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IEEE/CAA Journal of Automatica Sinica 2022年第11期9卷 1952-1966页

作者： Meiji Cui Li Li MengChu Zhou Jiankai Li Abdullah Abusorrah Khaled Sedraoui IEEE the School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China the Department of Electronics and Information Engineering Tongji UniversityShanghai 201804China the Helen and John C.Hartmann Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of Engineeringand K.A.CARE Energy Research and Innovation CenterKing Abdulaziz UniversityJeddah 21589Saudi Arabia

This study presents an autoencoder-embedded optimization(AEO)algorithm which involves a bi-population cooperative strategy for medium-scale expensive problems(MEPs).A huge search space can be compressed to an informative lowdimensional space by using an autoencoder as a dimension reduction *** search operation conducted in this low space facilitates the population with fast convergence towards the *** strike the balance between exploration and exploitation during optimization,two phases of a tailored teaching-learning-based optimization(TTLBO)are adopted to coevolve solutions in a distributed fashion,wherein one is assisted by an autoencoder and the other undergoes a regular evolutionary ***,a dynamic size adjustment scheme according to problem dimension and evolutionary progress is proposed to promote information exchange between these two phases and accelerate evolutionary convergence *** proposed algorithm is validated by testing benchmark functions with dimensions varying from 50 to *** indicated in our experiments,TTLBO is suitable for dealing with medium-scale problems and thus incorporated into the AEO framework as a base *** with the state-of-the-art algorithms for MEPs,AEO shows extraordinarily high efficiency for these challenging problems,t hus opening new directions for various evolutionary algorithms under AEO to tackle MEPs and greatly advancing the field of medium-scale computationally expensive optimization.

关键词： Autoencoder dimension reduction evolutionary algorithm medium-scale expensive problems teaching-learning-based optimization

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Guest Editorial Enabling Technologies and systems for Industry 5.0: From Foundation Models to Foundation Intelligence

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IEEE Transactions on systems, Man, and Cybernetics: systems 2024年第11期54卷 6496-6499页

作者： Tang, Ying Tian, Yonglin Lin, Yilun Lv, Chen Fanti, Maria Pia Rowan University Department of Electrical and Computer Engineering GlassboroNJ08028 United States Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China Institute of Automation Chinese Academy of Sciences Beijing100190 China Shanghai AI Laboratory Urban Computing Laboratory Shanghai200232 China Nanyang Technological University School of Mechanical and Aerospace Engineering Jurong West639798 Singapore Polytechnic University of Bari Department of Electrical and Information Engineering Bari70126 Italy

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Resilient distributed optimization under mobile malicious attacks

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IFAC-PapersOnLine 2023年第2期56卷 997-1002页

作者： Yuan Wang Changxin Liu Hideaki Ishii Karl Henrik Johansson Department of Robotics Hunan University Changsha China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden Department of Computer Science Tokyo Institute of Technology Yokohama Japan

This article addresses the distributed optimization problem in the presence of malicious adversaries that can move within the network and induce faulty behaviors in the attacked nodes. We first investigate the vulnerabilities of a consensus-based secure distributed optimization protocol under mobile adversaries. Then, a modified resilient distributed optimization algorithm is proposed. We develop conditions on the network structure for both complete and non-complete directed graph cases, under which the proposed algorithm guarantees that the estimates by regular nodes converge to the convex combination of the minimizers of their local functions. Simulations are carried out to verify the effectiveness of our approach.

关键词： Fault-tolerant distributed optimization multi-agent systems network security mobile adversary agents

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Crop protection and disease detection using artificial intelligence and computer vision: a comprehensive review

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Multimedia Tools and Applications 2025年第7期84卷 3723-3743页

作者： Shah, Kanish Sushra, Rajat Shah, Manan Shah, Dhairya Shah, Haard Raval, Megh Prajapati, Mitul Software Engineer Walmart SunnyvaleCA United States Atmiya Vidya Mandir Gujarat Surat India Department of Chemical Engineering School of Energy Technology Pandit Deendayal Energy University Gujarat Gandhinagar India Robotics ECE Concentration Northeastern University BostonMA United States Department of Computer Science Concentration in AI Hofstra University HempsteadNY United States Department of Chemical Engineering S. S Agrawal Institute of Engineering & Technology Gujarat Navsari India R &D Engineer Span Inspection Systems Pvt. Ltd Gujarat Gandhinagar India

The technological advancements in the field of agriculture have increased to a great extent in recent years, and many techniques have evolved from other techniques. Some methods are improved or upgraded from the previous versions by implementing a new model or using better hardware devices. This has been helpful for the farmers in increasing crop productivity, and the life expectancy of crops has also increased as the diseases inside or outside the crops can be detected much earlier, and learning at an early stage helps prevent other crops. In this paper, we have presented a study where many varieties of fruits and vegetables have been taken to determine which method was used for a particular crop. By analyzing the various works carried out by the authors, it was inferred that most of the works revolved around image processing and hyperspectral imaging. Due to this, we had also included most of the papers, particularly as the models and hardware components used were much better than other works. Then, a comparative study was done where different fruits and vegetables highlighted the two main areas: the method used and the accuracy obtained. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Crops

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Hyper-Drive: Visible-Short Wave Infrared Hyperspectral Imaging Datasets for Robots in Unstructured Environments

Hyper-Drive: Visible-Short Wave Infrared Hyperspectral Imagi...

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Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, WHISPERS

作者： Nathaniel Hanson Benjamin Pyatski Samuel Hibbard Charles DiMarzio Taşkın Padır Institute for Experiential Robotics Electrical and Computer Engineering Department Northeastern University Boston Massachusetts USA

Hyperspectral sensors have enjoyed widespread use in the realm of remote sensing; however, they require additional considerations for reliable functionality onboard mobile robots. In this work, we introduce a first-of-its-kind system architecture with snapshot hyperspectral cameras and point spectrometers to efficiently generate composite datacubes from a moving robot base. Our system collects and registers datacubes spanning the visible to shortwave infrared (660-1700 nm) spectrum while simultaneously capturing the ambient solar spectrum reflected off a white reference tile. We collect and disseminate a large dataset of more than 500 labeled datacubes from on-road and off-road terrain compliant with the ATLAS ontology to further the integration hyperspectral imaging (HSI). Our analysis of these data demonstrates that HSI is beneficial in terrain class separability and is a significant opportunity to increase understanding of scene composition from a robot-centric context. All code and data are open source online: https://***/hyper_drive_data

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