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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Zeng, Yu Zhang, Yang Liu, Jiachen Shen, Linlin Deng, Kaijun He, Weizhao Wang, Jinbao Computer Vision Institute School of Computer Science & Software Engineering Shenzhen University China Shenzhen Institute of Artificial Intelligence and Robotics for Society China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University China Guangdong Provincial Key Laboratory of Intelligent Information Processing China

Hair editing is a critical image synthesis task that aims to edit hair color and hairstyle using text descriptions or reference images, while preserving irrelevant attributes (e.g., identity, background, cloth). Many existing methods are based on StyleGAN to address this task. However, due to the limited spatial distribution of StyleGAN, it struggles with multiple hair color editing and facial preservation. Considering the advancements in diffusion models, we utilize Latent Diffusion Models (LDMs) for hairstyle editing. Our approach introduces Multi-stage Hairstyle Blend (MHB), effectively separating control of hair color and hairstyle in diffusion latent space. Additionally, we train a warping module to align the hair color with the target region. To further enhance multi-color hairstyle editing, we fine-tuned a CLIP model using a multi-color hairstyle dataset. Our method not only tackles the complexity of multi-color hairstyles but also addresses the challenge of preserving original colors during diffusion editing. Extensive experiments showcase the superiority of our method in editing multi-color hairstyles while preserving facial attributes given textual descriptions and reference images. © 2024 Neural information processing systems foundation. All rights reserved.

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Comparison between Docker and Kubernetes based Edge Architectures for Enabling Remote Model Predictive Control for Aerial Robots 48

Comparison between Docker and Kubernetes based Edge Architec...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Santi Seisa, Achilleas Gajanan Satpute, Sumeet Nikolakopoulos, George Luleå University of Technology Robotics and Ai Team Department of Computer Electrical and Space Engineering Luleå Sweden

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Edge computing is becoming more and more popular among researchers who seek to take advantage of the edge resources and the minimal time delays, in order to run their robotic applications more efficiently. Recently, many edge architectures have been proposed, each of them having their advantages and disadvantages, depending on each application. In this work, we present two different edge architectures for controlling the trajectory of an Unmanned Aerial Vehicle (UAV). The first architecture is based on docker containers and the second one is based on kubernetes, while the main framework for operating the robot is the Robotic Operating System (ROS). The efficiency of the overall proposed scheme is being evaluated through extended simulations for comparing the two architectures and the overall results obtained. © 2022 IEEE.

关键词： Edge computing

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MambaMOS: LiDAR-based 3D Moving Object Segmentation with Motion-aware State Space Model 24

MambaMOS: LiDAR-based 3D Moving Object Segmentation with Mot...

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32nd ACM International Conference on Multimedia, MM 2024

作者： Zeng, Kang Shi, Hao Lin, Jiacheng Li, Siyu Cheng, Jintao Wang, Kaiwei Li, Zhiyong Yang, Kailun College of Computer Science and Electronic Engineering Hunan University Changsha China College of Optical Science and Engineering Zhejiang University Hangzhou China School of Robotics Hunan University Changsha China School of Electronics and Information Engineering South China Normal University Foshan China

ISBN: (纸本)9798400706868

LiDAR-based Moving Object Segmentation (MOS) aims to locate and segment moving objects in point clouds of the current scan using motion information from previous scans. Despite the promising results achieved by previous MOS methods, several key issues, such as the weak coupling of temporal and spatial information, still need further study. In this paper, we propose a novel LiDAR-based 3D Moving Object Segmentation with Motion-aware State Space Model, termed MambaMOS. Firstly, we develop a novel embedding module, the Time Clue Bootstrapping Embedding (TCBE), to enhance the coupling of temporal and spatial information in point clouds and alleviate the issue of overlooked temporal clues. Secondly, we introduce the Motion-aware State Space Model (MSSM) to endow the model with the capacity to understand the temporal correlations of the same object across different time steps. Specifically, MSSM emphasizes the motion states of the same object at different time steps through two distinct temporal modeling and correlation steps. We utilize an improved state space model to represent these motion differences, significantly modeling the motion states. Finally, extensive experiments on the SemanticKITTI-MOS and KITTI-Road benchmarks demonstrate that the proposed MambaMOS achieves state-of-the-art performance. The source code is publicly available at https://***/Terminal-K/MambaMOS © 2024 ACM.

关键词： Embeddings

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IoT-based remote control for robotic arm

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International Journal of Systems, Control and Communications 2024年第2期15卷 146-158页

作者： Do, Tri Nhut Department of Embedded Systems and Robotics Faculty of Computer Engineering University of Information Technology Viet Nam Vietnam National University Ho Chi Minh City 1 Han Thuyen Street Linh Trung Ward Thu Duc Ho Chi Minh City71308 Viet Nam

Robotic arms can perform various tasks with high accuracy, efficiency, and safety, especially in hazardous environments. This paper presents four degrees of freedom robotic arm that can be controlled remotely by two methods: direct control via Wi-Fi and indirect control via internet. We have designed an embedded system that allows the user to manipulate the robotic arm by moving the robot hand in different directions. We have also developed two software applications for remote control: one using MIT inventor 2 tool for direct control, and another using a web-based interface for indirect control. The software applications enable the user to adjust the angles of the four servo motors that drive the robotic arm in both clockwise and counter – clockwise directions. We have conducted several experiments to demonstrate the feasibility and stability of our system under different scenarios. Our results show that our system can perform wireless control of the robotic arm effectively using various mobile devices such as phone, tablet, or computer such as laptop, personal computer. © 2024 Inderscience Enterprises Ltd.

关键词： Robotic arms

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iDrone: IoT-Enabled Unmanned Aerial Vehicles for Detecting Wildfires Using Convolutional Neural Networks

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SN computer Science 2022年第3期3卷 1-13页

作者： Sethuraman, Sibi Chakkaravarthy Tadkapally, Gaurav Reddy Mohanty, Saraju P. Subramanian, Anitha School of Computer Science and Engineering and Center of Excellence in Artificial Intelligence and Robotics (AIR) VIT-AP University Amaravati India Department of Computer Science and Engineering University of North Texas Denton 76207 TX United States School of Electronics Engineering and Center of Excellence in Artificial Intelligence and Robotics (AIR) VIT-AP University Amaravati India

The rise of global temperatures, over the past few decades, has disrupted the usual balance of nature. As a result of increasing temperatures, wildfires have destroyed millions of acres of land, thousands of structures, and homes. The pollution and toxic gases produced by the wildfires are carried out to thousands of miles, thus threatening the lives all around the world. Most wildfires occur due to anthropogenic factors, which cannot be predicted solely based on climate conditions. Henceforth, to detect wildfires before escalating, we propose iDrone, which is a wildfire detection system equipped with an end-to-end CNN image classification model: XtinguishNet, trained on a wildfire imagery dataset to detect the possible flames or smokes in an image. In addition, our approach also acquires the weather data and the intensity of the fire. Contrasting with existing wildfire detection systems, our proposed solution is a fusion of the Internet of Things (IoT) and Deep Learning, aiming to provide a one-stop solution for all the needs required to minimize the damage caused by wildfires. When validated and tested using various benchmark datasets, video surveillance, iDrone acquired a high accuracy of 98.36% with the least computational power. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： CNN computer vision Deep learning Forest fires iDrone Wildfires

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Visual Tracking Nonlinear Model Predictive Control Method for Autonomous Wind Turbine Inspection 21

Visual Tracking Nonlinear Model Predictive Control Method fo...

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21st International Conference on Advanced robotics, ICAR 2023

作者： Amer, Abdelhakim Mehndiratta, Mohit Le Fevre Sejersen, Jonas Pham, Huy Xuan Kayacan, Erdal Department of Electrical and Computer Engineering Aarhus C8000 Denmark Gim Robotics Espoo Finland Automatic Control Group Paderborn University Department of Electrical Engineering and Information Technology Paderborn Germany

ISBN: (纸本)9798350342291

Automated visual inspection of on- and off-shorewind turbines using aerial robots provides several benefits, namely, a safe working environment by circumventing the need for workers to be suspended high above the ground, reduced inspection time, preventive maintenance, and access to hard-to-reach areas. A novel nonlinear model predictive control (NMPC) framework alongside a global wind turbine path planner is proposed to achieve distance-optimal coverage for wind turbine inspection. Unlike traditional MPC formulations, visual tracking NMPC (VT-NMPC) is designed to track an inspection surface, instead of a position and heading trajectory, thereby circumventing the need to provide an accurate predefined trajectory for the drone. An additional capability of the proposed VT-NMPC method is that by incorporating inspection requirements as visual tracking costs to minimize, it naturally achieves the inspection task successfully while respecting the physical constraints of the drone. Multiple simulation runs and real-world tests demonstrate the efficiency and efficacy of the proposed automated inspection framework, which outperforms the traditional MPC designs, by providing full coverage of the target wind turbine blades as well as its robustness to changing wind conditions. The implementation codes11https://***/open-airlab/VTNMPC-Autonomous-Wind-Turbine-Inspection are open-sourced. © 2023 IEEE.

关键词： Inspection

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Benefits of Internet of Things (IoT) Applications in Health care - An Overview 1

Benefits of Internet of Things (IoT) Applications in Health ...

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Chaudhary, Preeti Yadav, Satya Prakash Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Nicosia Artificial Intelligence Engineering Dept. Mersin10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty OfEngineering Kyrenia Mersin10 Turkey Graphic Era Hill University Computer Science and Engineering Dehradun India Department of Computer Science and Engineering Greater Noida201306 India

ISBN: (纸本)9798350338027

In a nutshell, the IoT refers to the idea of integrating high-tech technology in the form of "smart"gadgets and sensors into a single setting to gather data. There are still numerous areas in which machines cannot compete favorably with people, but data collection and analysis are undeniably two of their strongest points. The Internet of Things makes it possible to fully or partially automation data, it involves related activities, which is obviously very important for the healthcare industry. What exactly is the Internet connected medical things, and how exactly might it make a significant impact on the sector? By having to apply the concept of the internet of things (IoT) to the field of medicine, several significant advancements have become possible, including the ability to automatically control the thermostat of containers while transmitting inoculations and antibiotics, the accurate tracking of the ailments of a lot of illnesses without a need for additional meetings with a general practitioner, the correct and most useful use of meds, and a great deal more. All of this is realizable because of the capability of MedTech gadgets to carry out continuous monitoring system. The potential applications of internet of things technology in healthcare are very interesting. Let's review the ways in which this technology. © 2023 IEEE.

关键词： Medical applications

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Mechatronic Design of an Omnidirectional Octorotor UAV 10

Mechatronic Design of an Omnidirectional Octorotor UAV

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10th International Conference on Automation, robotics, and Applications, ICARA 2024

作者： Hamandi, Mahmoud Ali, Abdullah Mohamed Evangeliou, Nikolaos Chaikalis, Dimitris Tzes, Anthony Kyriakopoulos, Konstantinos Khorrami, Farshad Center for Artificial Intelligence and Robotics Abu Dhabi129188 United Arab Emirates Electrical Engineering NYUAD Abu Dhabi129188 United Arab Emirates New York University Electrical and Computer Engineering BrooklynNY11201 United States

ISBN: (纸本)9798350394245

The design of an omnidirectional octorotor (OmniOcta) is the scope of this article. The pose of the UAV's thrusters is computed via an optimization algorithm that guarantees the omnidirectionality of the platform. The thrusters' positions are restricted in a semispherical volume with different polar coordinates while their pose is determined in order to avoid the interaction between their propellers' air-funnels. The octorotor is manufactured using 3D printed parts and its employed electronics were selected so as to have the smallest weight. The number of thrusters was then selected as the minimal number that could lift the platform's weight in all rotation directions with the chosen electronic and aerodynamic components. Simulations were conducted to show the capacity of the UAV to lift its weight, while experiments were conducted to identify the allocation matrix of the constructed UAV. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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CF-AMVRGO: Collaborative Filtering based Adaptive Moment Variance Reduction Gradient Optimizer for Movie Recommendations

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International Journal of computers and Applications 2022年第11期44卷 1015-1023页

作者： Lakshmi Chetana, V. Seetha, Hari School of Computer Science and Engineering VIT-AP University Andhra Pradesh Vijayawada India Center of Excellence AI and Robotics VIT-AP University Andhra Pradesh Vijayawada India

In recent decades, recommendation systems are used in a variety of applications like social connections, movies, music, and venues. The existing algorithms has certain limitations like data sparsity, cold start problem, and poor scalability to degrade the movie recommendation performance. To address the aforementioned concerns, a new matrix factorization-based collaborative filtering algorithm is developed to enhance movie recommendation performance. In a neural collaborative filtering algorithm, an adaptive moment variance reduction gradient optimizer is applied in low-rank matrix factorization for representing the users and items in a low dimensional latent space to obtain effective movie recommendation performance. In this paper, the proposed algorithm performance is evaluated on three benchmark datasets;movielens 100K, 1M, and 10M datasets. Simulation results showed that the proposed algorithm obtained the difference of 0.08 and 0.056 roots mean square error value in movielens 1M and 10M datasets, which are better compared to the existing collaborative filtering-based deep learning algorithm. © 2022 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Collaborative filtering

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Mobile edge fog, Blockchain Networking and Computing-A survey 1

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

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1st International Conference on Computational Intelligence, Communication Technology and Networking, CICTN 2023

作者： Salama, Ramiz Al-Turjman, Fadi Bhatla, Shruti Mishra, Divya Ai and Robotics Institute Research Center for Ai and IoT Near East University Nicosia Department of Computer Engineering Mersin10 Turkey Ai and Robotics Institute Near East University Artificial Intelligence Engineering Dept. Mersin Nicosia10 Turkey University of Kyrenia Research Center for Ai and IoT Faculty of Engineering Kyrenia Mersin10 Turkey Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Abes Engineering College Ghaziabad India

ISBN: (纸本)9798350338027

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. © 2023 IEEE.

关键词： Blockchain

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