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ai-assisted flexible electronics in humanoid robot heads for natural and authentic facial expressions

The Innovation 2025年第2期6卷 13-15页

作者： Nian Dai Kaijun Zhang Fan Zhang Junfeng Li Junwen Zhong YongAn Huang Han Ding Department of Electromechanical Engineering and Centre for AI and Robotics University of MacaoMacao SAR 999078China State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Flexible Electronics Research Center Huazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Electric Engineering Wuhan University of TechnologyWuhan 430070China

The realization of natural and authentic facial expressions in humanoid robots poses a challenging and prominent research domain,encompassing interdisciplinary facets including mechanical design,sensing and actuation control,psychology,cognitive science,flexible electronics,artificial intelligence(ai),*** have traced the recent developments of humanoid robot heads for facial expressions,discussed major challenges in embodied ai and flexible electronics for facial expression recognition and generation,and highlighted future trends in this *** humanoid robot heads with natural and authentic facial expressions demands collaboration in interdisciplinary fields such as multi-modal sensing,emotional computing,and human-robot interactions(HRIs)to advance the emotional anthropomorphism of humanoid robots,bridging the gap between humanoid robots and human beings and enabling seamless HRIs.

关键词： facial expressionsdiscussed facial expression embodied ai humanoid robot heads flexible electronics natural authentic humanoid robots facial expressions

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Social engineering attack types and prevention techniques- A survey

Social engineering attack types and prevention techniques- A...

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Shruti Bhatla Satya Prakash Yadav Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Turkey Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Kyrenia Turkey Department of Computer Science and Engineering Graphic Era Hill University Dehradun Department of Computer Science and Engineering G.L. Bajaj Institute of Technology and Management (GLBITM) Greater Noida India

The term "Cyber Security" is getting more and more popular and important over the last few years. Since computers and most of the devices are connected to the internet, they are likely to be hacked by the hackers. In the past, this issue was not a big problem, because not every device is required to be connected to the internet or the internet was not popular as today. But the case has changed over the years. All the changes in the technology area also changed the cyber-attack models as well. With the development of technology and the change of usage of the internet over the last years cyber-attacks have become more common and popular by the hackers. Hackers have discovered that they have an opportunity to steal or earn money in a short time without having to spend too much effort. These days, the type of cyber-attacks is not the same as the ones in the past. As time passes, the cyber-attack methods are also changing and evolving. Today, hackers are using more advanced and effective cyber-attack methods compared to past years. There are many methods that are impossible to cover all of them in this article. Our main focus will be on social engineering attacks in this article. Social engineering attacks use different approaches to cyber attacking. Unlike trying to explode a victim’s social media password etc. using advanced exporting programs, algorithms or techniques, social engineering attacks focus on fooling victims into providing their data to hackers by themselves without using or implementing any password cracking, exploiting techniques etc. We will go over what social media engineering is, type of social engineering methods, what countermeasures can be used to protect from social engineering and more in this article.

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FRAME: A Modular Framework for Autonomous Map Merging: Advancements in the Field

IEEE Transactions on Field Robotics

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IEEE Transactions on Field robotics 2024年 1卷 1-26页

作者： Nikolaos Stathoulopoulos Björn Lindqvist Anton Koval Ali-Akbar Agha-Mohammadi George Nikolakopoulos Department of Computer Electrical and Space Engineering Robotics and AI Group Luleå University of Technology Luleå Sweden Jet Propulsion Laboratory California Institute of Technology Pasadena CA USA

In this article, a novel approach for merging 3-D point cloud maps in the context of egocentric multirobot exploration is presented. Unlike traditional methods, the proposed approach leverages state-of-the-art place recognition and learned descriptors to efficiently detect overlap between maps, eliminating the need for the time-consuming global feature extraction and feature matching process. The estimated overlapping regions are used to calculate a homogeneous rigid transform, which serves as an initial condition for the general iterative closest point (GICP) point cloud registration algorithm to refine the alignment between the maps. The advantages of this approach include faster processing time, improved accuracy, and increased robustness in challenging environments. Furthermore, the effectiveness of the proposed framework is successfully demonstrated through multiple field missions of robot exploration in a variety of different underground environments.

关键词： Robots Point cloud compression Feature extraction Three-dimensional displays Robot sensing systems Robot kinematics Accuracy

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Scientific Computing with Diffractive Optical Neural Networks

Scientific Computing with Diffractive Optical Neural Network...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Chen, Ruiyang Tang, Yingheng Ma, Jianzhu Gao, Weilu Department of Electrical and Computer Engineering The University of Utah Salt Lake CityUT84112 United States School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue University West LafayetteIN47907 United States Institute for AI Industry Research Tsinghua University Beijing10084 China

ISBN: (纸本)9781957171395

We deploy reconfigurable diffractive optical neural networks for multiple scientific computing applications, including guiding quantum material synthesis, predicting properties of materials, biomolecules, and nanophotonic devices, and dynamic stabilization of an inverted pendulum with reinforcement learning. © Optica Publishing Group 2024 © 2024 TheAuthor (s)

关键词： Optical fibers

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Scientific Computing with Diffractive Optical Neural Networks

Scientific Computing with Diffractive Optical Neural Network...

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CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Diffractive optics

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Mobile edge fog, Blockchain Networking and Computing-A survey

Mobile edge fog, Blockchain Networking and Computing-A surve...

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Ramiz Salama Fadi Al-Turjman Shruti Bhatla Divya Mishra Department of Computer Engineering AI and Robotics Institute Research Center for AI and IoT Near East University Nicosia Mersin Turkey Artificial Intelligence Engineering Dept. AI and Robotics Institute Near East University Nicosia Mersin Turkey Research Center for AI and IoT Faculty of Engineering University of Kyrenia Kyrenia Mersin Turkey Department of Computer Science and Engineering Graphic Era Hill University Dehradun ABES Engineering College Ghaziabad

Mobile edge computing (MEC) and blockchain technology are two rapidly evolving areas in computer science that have the potential to significantly impact the design and operation of distributed systems. MEC involves the deployment of computing resources and services at the edge of the network, closer to the end users, enabling lowlatency, high-bandwidth applications such as augmented reality and machine learning. Blockchain technology, on the other hand, is a distributed database that allows for secure, transparent, and immutable record-keeping, with potential applications in a wide range of industries. In this project, we explore the integration of MEC and blockchain technology for the management of distributed computing resources at the edge of the network. We review the state of the art in these two areas, including existing projects and prototypes, and describe our materials and method for evaluating their potential for integration. Our results show that the combination of MEC and blockchain has the potential to enable new applications and services that require both low latency and secure, decentralized data management. We conclude by summarizing the main contributions of our work and discussing future directions for research in this area. Our findings have implications for the design and operation of distributed systems, and have the potential to enable new applications and services in a wide range of industries.

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Maintaining Visibility of Dynamic Objects in Cluttered Environments Using Mobile Manipulators and Vector Field Inequalities

Maintaining Visibility of Dynamic Objects in Cluttered Envir...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Fatih Dursun Bruno Vilhena Adorno Simon Watson Wei Pan Department of Electrical and Electronic Engineering Manchester Centre for Robotics and AI University of Manchester UK Department of Computer Science

Vision-based perception has become prevalent in robotic applications, especially in those where the control loop relies on visual data, such as visual servoing. For those applications, ensuring that the features or target object remain visible to the camera is critical, necessitating visibility-aware control. In this paper, we propose a method to guarantee the visibility of a dynamic object using a constrained kinematic controller and Vector Field Inequalities (VFIs) to include a linear visibility constraint. Unlike existing methods, we introduce constraints into the kinematic controller to ensure the target's visibility without needing a trajectory optimizer or local planner. Our method maintains the target object in the camera field of view (FoV) by representing the FoV with four infinite planes and maintaining the distance between the target object and each plane higher than a predefined distance. We evaluated the proposed approach using a mobile manipulator in two simulations involving cluttered environments: the first scenario involves a stationary target object, whereas the second scenario presents a more challenging workspace involving a moving target. Our results demonstrate that the proposed approach successfully maintains the target within the FoV while avoiding obstacles in the workspace, showing the potential of our method to improve the safety and reliability of visual-servoing-based robotic systems.

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Slotted ALOHA with Code Combining for IoT Networks 3

Slotted ALOHA with Code Combining for IoT Networks

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3rd IEEE International Mediterranean Conference on Communications and Networking, MeditCom 2023

作者： Tyrovolas, Dimitrios Chrysologou, Athanasios Chondrogiannis, Georgios Tegos, Sotiris Mekikis, Prodromos-Vasileios Diamantoulakis, Panagiotis Ioannidis, Sotiris Liaskos, Christos Chatzidiamantis, Nestor Karagiannidis, George Aristotle University of Thessaloniki Dept. of Electrical and Computer Engineering Thessaloniki Greece Technical University of Chania Dept. of Electrical and Computer Engineering Chania Greece University of Ioannina Computer Science Engineering Department Ioannina Greece Cyber Security Systems and Applied Ai Research Center Lebanon

ISBN: (纸本)9798350333732

Internet of Things (IoT) networks are expected to be a key enabler technology for smart cities, due to their ability to offer real-time monitoring. In this work, we propose a novel medium access control (MAC) protocol, inspired by the synergy of slotted ALOHA and hybrid automatic repeat request with code combining (HARQ-CC), termed as code combining slotted ALOHA (CCSA), to improve the performance of IoT networks with multiple randomly deployed sensors. Specifically, we provide analytical closed-form expressions for the network's outage probability as well as for its average throughput when CCSA is applied. Finally, we provide simulation results that reveal the authenticity of the derived expressions and reveal the capabilities of HARQ-CC to significantly improve the network's performance when the sensors' access is based on a random access scheme. © 2023 IEEE.

关键词： Wireless sensor networks

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Multi-Object Discovery by Low-Dimensional Object Motion

Multi-Object Discovery by Low-Dimensional Object Motion

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International Conference on computer Vision (ICCV)

作者： Sadra Safadoust Fatma Güney KUIS AI Center and Department of Computer Engineering Koç University

Recent work in unsupervised multi-object segmentation shows impressive results by predicting motion from a single image despite the inherent ambiguity in predicting motion without the next image. On the other hand, the set of possible motions for an image can be constrained to a low-dimensional space by considering the scene structure and moving objects in it. We propose to model pixel-wise geometry and object motion to remove ambiguity in reconstructing flow from a single image. Specifically, we divide the image into coherently moving regions and use depth to construct flow bases that best explain the observed flow in each region. We achieve state-of-the-art results in unsupervised multi-object segmentation on synthetic and real-world datasets by modeling the scene structure and object motion. Our evaluation of the predicted depth maps shows reliable performance in monocular depth estimation.

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Memory Enabled Segmentation of Terrain for Traversability based Reactive Navigation

Memory Enabled Segmentation of Terrain for Traversability ba...

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IEEE International Conference on robotics and Biomimetics

作者： Mario A.V. Saucedo Akash Patel Christoforos Kanellakis George Nikolakopoulos Department of Computer Electrical and Space Engineering Robotics & AI Team Luleå University of Technology Luleå Sweden

This article presents a novel 2D traversability image estimation for local reactive navigation, that attributes the fusion of a novel Convolutional Neural Network (CNN) for coarse semantic segmentation on terrain roughness, with surface geometric normals. The proposed segmentation model consists of a U-Net based Encoder-Decoder architecture with a MobileNet V3 Large backbone for real-time performance. At the bottom layer, the bottleneck block commonly found in a U-Net has been enhanced with an Atrous Spatial Pyramid Pooling (ASPP) block. In addition, a SEResNet based decoder instead of the classical stacked convolution blocks of U-Net has been implemented, while a concatenation layer has been added at the output. Moreover, the development of a novel memory module to dynamically update the semantic segmentation image based on certainty heat maps is also shown. The efficacy of the proposed scheme has been evaluated in real-life environments such as indoors, outdoors and subterranean (SubT) environments on a Pioneer 3AT mobile robot.

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