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CPL-SLAM: Centralized Collaborative Multi-Robot Visual-Inertial SLAM Using Point-and-Line Features

IEEE Internet of Things Journal 2025年第12期12卷 21866-21875页

作者： Liu, Xin Wen, Shuhuan Liu, Huaping Richard Yu, F. Yanshan University Engineering Research Center The Ministry of Education for Intelligent Control System and Intelligent Equipment Key Lab of Intelligent Rehabilitation and Neuroregulation in Hebei Province Department of Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Shenzhen University College of Computer Science and Software Engineering China Carleton University Canada

Traditional visual-inertial SLAM (Simultaneous Localization and Mapping) systems predominantly rely on feature point matching from a single robot to realize the robot pose estimation and environment map construction. However, in complex scenarios, these traditional systems struggle with issues such as tracking failures due to illumination changes, rapid movements, and low-texture environments, and they perform poorly in terms of mapping efficiency and global consistency. To address these challenges, we propose a centralized collaborative SLAM system that employs both point and line features for tracking in the robot and map fusion in the cloud. The proposed system leverages the fusion of point and line features across all instances in the process, which allows our method to achieve higher localization accuracy in structured, low-texture scenes. With the aid of classifying gravity-aligned vertical lines and spatial parallel lines, the proposed system can deliver faster and more accurate odometry in complex scenes. Furthermore, we developed intra-robot and inter-robot loop closure detection methods based on point and line features, generating a globally consistent sparse point cloud and structured scene map in the cloud. Our method is able to build richer maps while improving accuracy compared to existing methods. Experimental results on public datasets and in real-world environments show that, compared to existing advanced methods, our approach demonstrates better performance. © 2014 IEEE.

关键词： SLAM robotics

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Cloud-Edge Collaborative-Based Digital Twin System for Hardware Limited IIoT Scenario 9

Cloud-Edge Collaborative-Based Digital Twin System for Hardw...

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9th IEEE Smart World Congress, SWC 2023

作者： Han, Qiaojian Zhang, Jiaji Ding, Hui Sun, Jian Zhang, Haixia Yuan, Dongfeng Shandong University School of Information Science and Engineering Qingdao China Shandong Key Laboratory of Wireless Mobile Communication Technologies Jinan China Northwestern Polytechnical University School of Computer Science Xi'an China Yunnan Development and Reform Commission Kunming China Shandong University School of Control Science and Engineering Jinan China

ISBN: (纸本)9798350319804

As the demand for more efficient intelligent manufacturing models continues to grow, the manufacturing industry is in urgent need of improving the intelligence and informatization of manufacturing models. Digital Twin, as an emerging intelligent technology, can enhance the intelligence of the Industrial Internet of Things (IIoT) in manufacturing industry by providing virtual-physical mapping and real-time interaction. However, the current deployment of Digital Twin in practical industrial scenarios is challenging due to limited resources on local hardware and high computing loads in the cloud center. To address these challenges, this paper has established an edge-cloud collaborative Digital Twin System that includes the Edge Digital Twin (EDT) mode in IIoT Scenario. EDT mode enables Digital Twin System to complete most of its tasks with fewer computing resources without relying on three-dimensional (3D) modeling. The remaining tasks need to upload the EDT to the cloud. After combining the 3D model of the cloud, the complete Digital Twin can be obtained. Experimental results show that the proposed solution is verified through a case of intelligent exterior inspection of air conditioner units in a laboratory setting. The results of experiments showed that the established system not only addressed the challenge of deploying Digital Twin on local hardware with limited resources but also relieved the computational pressure on the cloud and reduced the overall task latency. © 2023 IEEE.

关键词： Artificial Intelligence Edge Digital Twin Edge-Cloud Collaborative Industrial Internet of Things Intelligent Communication

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Integrative approach for predicting drug-target interactions via matrix factorization and broad learning systems

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Mathematical Biosciences and engineering 2024年第2期21卷 2608-2625页

作者： Xu, Wanying Yang, Xixin Guan, Yuanlin Cheng, Xiaoqing Wang, Yu College of Computer Science & Technology Qingdao University Qingdao266071 China School of Automation Qingdao University Qingdao266071 China Key Lab of Industrial Fluid Energy Conservation and Pollution Control Ministry of Education Qingdao University of Technology Qingdao266520 China School of Mechanical & Automotive Engineering Qingdao University of Technology Qingdao266520 China

In the drug discovery process, time and costs are the most typical problems resulting from the experimental screening of drug-target interactions (DTIs). To address these limitations, many computational methods have been developed to achieve more accurate predictions. However, identifying DTIs mostly rely on separate learning tasks with drug and target features that neglect interaction representation between drugs and target. In addition, the lack of these relationships may lead to a greatly impaired performance on the prediction of DTIs. Aiming at capturing comprehensive drug-target representations and simplifying the network structure, we propose an integrative approach with a convolution broad learning system for the DTI prediction (ConvBLS-DTI) to reduce the impact of the data sparsity and incompleteness. First, given the lack of known interactions for the drug and target, the weighted K-nearest known neighbors (WKNKN) method was used as a preprocessing strategy for unknown drug-target pairs. Second, a neighborhood regularized logistic matrix factorization (NRLMF) was applied to extract features of updated drug-target interaction information, which focused more on the known interaction pair parties. Then, a broad learning network incorporating a convolutional neural network was established to predict DTIs, which can make classification more effective using a different perspective. Finally, based on the four benchmark datasets in three scenarios, the ConvBLS-DTI’s overall performance out-performed some mainstream methods. The test results demonstrate that our model achieves improved prediction effect on the area under the receiver operating characteristic curve and the precision-recall curve. ©2024 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://***/licenses/by/4.0)

关键词： Learning systems

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ELOFS: An Extensible Low-Overhead Flash File System for Resource-Scarce Embedded Devices

ELOFS: An Extensible Low-Overhead Flash File System for Reso...

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作者： Zhang, Runyu Liu, Duo Chen, Xianzhang She, Xiongxiong Yang, Chaoshu Tan, Yujuan Shen, Zhaoyan Shao, Zili Qiao, Lei Chongqing400044 China Chongqing University College of Computer Science Chongqing400044 China Shandong University School of Computer Science and Technology Qingdao266237 China The Chinese University of Hong Kong Department of Computer Science and Engineering NT 999077 Hong Kong Beijing Institute of Control Engineering Beijing100190 China

Emerging applications like machine learning in embedded devices (e.g., satellites and vehicles) require huge storage space, which recently stimulates the widespread deployment of large-scale flash memory in IoT devices. However, existing embedded file systems fall short in managing large-capacity storage efficiently for two reasons. First, prior arts store data structures of file systems either in flash or in main memory, which severely magnifies the scarcity of computing and memory resources. Moreover, the fine-grained metadata management in the existing embedded file systems induces significant energy consumption for large-capacity storage. In this paper, we propose a novel embedded file system, ELOFS, to tackle the above issues and manage large-capacity NAND flash on resource-scarce devices. ELOFS is made efficient through three novel techniques. First, we redefine the space management granularity and streamline the metadata to speed up the mounting performance. In addition, we design hybrid file structures to adapt dissimilar access patterns of embedded devices. Furthermore, ELOFS provides opportunities for in-depth cooperation with application-specific systems. We implement ELOFS with Memory Technology Device (MTD) interfaces, and the experimental results show that ELOFS outperforms YAFFS and UBIFS in terms of write, read, and deletions with orders of magnitude reductions on memory footprint and mounting time. © 1968-2012 IEEE.

关键词： Metadata

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Enhancing 6G-Satellite Network Integration with Artificial Intelligence: A Future Communication Paradigm 22

Enhancing 6G-Satellite Network Integration with Artificial I...

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22nd International Learning and Technology Conference, L and T 2025

作者： Salah, Ibrahim Hussein, Aziza I. Wageh Lotfy, Mostafa Mabrook, Mohamed Mourad Almaaqal University College of Engineering Control and Computer Department Basrah61001 Iraq Effat University College of Engineering Energy and Technology Research Center Saudi Arabia Faculty of Technology and Education Beni-Suef University Dept. of Process Control Technology Beni-Suef Egypt Beni-Suef University Faculty of Navigation Science & Space Technology Space Communication Dept. Beni-Suef Egypt

ISBN: (纸本)9798331532215

The integration of 6G networks and satellite communications is set to revolutionize global connectivity, offering seamless coverage across terrestrial and non-terrestrial environments. Artificial Intelligence (AI) is essential for improving this integration, addressing challenges such as dynamic resource management, latency reduction, and network optimization. AI techniques like machine learning, deep learning, and reinforcement learning offer innovative solutions to handle the complexities of 6G-satellite networks. These advancements promise to significantly improve network efficiency, enhance data transmission reliability, and ensure seamless connectivity across different areas. Potential use cases include smart cities, autonomous vehicles, and Internet of Things (IoT) applications, where AI-driven 6G-satellite integration will be crucial. The proposed AI-enhanced 6G-satellite framework not only addresses current challenges but also lays the groundwork for a resilient, scalable, and globally interconnected communication infrastructure, offering a promising future. © 2025 IEEE.

关键词： Satellite communication systems

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Development of a Framework for Data-Driven Modeling with Cloud Services in the Process Industry

Development of a Framework for Data-Driven Modeling with Clo...

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2022 International Conference on Automation, Robotics and computer engineering, ICARCE 2022

作者： Polke, Dominik Diepers, Florian Ahle, Elmar Söffker, Dirk University of Applied Sciences Niederrhein Electrical Engineering and Computer Science Krefeld Germany University of Duisburg-Essen Dynamics and Control Duisburg Germany

ISBN: (纸本)9781665475488

The chemical process industry is currently undergoing a transformation to Chemistry 4.0, where digitalization, modularization, sustainability, and the circular economy are coming into focus. A growing interest in the use of process data with the aim of gaining a better understanding of the production process and conserving resources can be observed. Data-driven modeling is used in chemical industry when the production process is too complex to be described by chemical laws. Gaining knowledge of the chemical relationships can lead to resource-conserving production. In this paper, a framework to optimize the process of data-driven modeling in an industrial environment is presented. For generating data-driven models of industrial processes, many manual and time-consuming steps have to be carried out. This leads to delay in information acquisition and process optimization. Therefore, the presented framework automates these steps to accelerate the process of data-driven modeling. The steps are to extract the data from a process control system (PCS), make the data available for data-driven modeling, train the model, and deploy the model for predicting the process. To achieve high availability of the data and generate data-driven models, cloud services are used. The framework of this paper is applied to a high-throughput formulation system (HTFS) for coatings. In this paper, Gaussian processes are used for data-driven modeling. The evaluation of the framework shows the usefulness in this domain, but also the flexibility and scalability of this framework. © 2022 IEEE.

关键词： Chemical industry

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Special Session: Software-Based Self-Test Generation for RISC-V – Stuck-At Generation, Functional Cell-Aware Untestability, and FPGA Demonstration –

Special Session: Software-Based Self-Test Generation for RIS...

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IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems

作者： Tobias Faller Nikolaos I. Deligiannis Riccardo Cantoro Matteo Sonza Reorda Bernd Becker Department of Computer Science University of Freiburg Freiburg Germany Department of Control and Computer Engineering (DAUIN) Politecnico di Torino Turin Italy

ISBN: (数字)9798350366884

ISBN: (纸本)9798350366891

Software-Based Self-Tests (SBST) allow at-speed, native online-testing of processors by running software programs on the processor core, requiring no Design for Testability (DfT) infrastructure. Traditionally, the generation of such SBST programs requires time-consuming manual labor in combination with in-depth knowledge of the processor's architecture to target hard-to-test faults. In contrast, encoding the SBST generation task as a Bounded Model Checking (BMC) problem allows using sophisticated, state-of-the-art BMC solvers to automatically generate an SBST for a given fault model and, moreover, prove the untestability of certain faults. During generation, a constraint specification Validity Checker Module (VCM) ensures correct, functional SBST behavior. The operating conditions in the field and the processor and system-specific constraints are included in this specification, too, in a highly configurable form. In this paper, we present an intermediate VCM interface to generalize the functional constraint specification on RISC-V processors and apply it to two in-field test-related areas. First, we perform SBST generation for detecting permanent hardware faults (stuck-at) in the ALU and the register file of multiple RISC-V processors. Second, we perform functional untestability analysis for the cell-aware fault model on the same processors. Finally, we synthesize the largest processor core on an FPGA with user-controlled fault injection to demonstrate the subsequent detection via the generated stuck-at SBST to a non-technical audience.

关键词： Fault diagnosis Program processors Runtime Built-in self-test Very large scale integration Software Registers Test pattern generators Field programmable gate arrays Nanotechnology

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A distributed algorithm with network-independent step-size and event-triggered mechanism for economic dispatch problem

A distributed algorithm with network-independent step-size a...

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作者： Chen, Baitong Yang, Jianhua Lu, Wei Pedrycz, Witold Sun, Changhai School of Control Science and Engineering Dalian University of Technology Dalian China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Institute of Systems Engineering Macau University of Science and Technology SARTaipa 999078 China Research Center of Performance and Productivity Analysis Istinye University Istanbul Turkey School of Electrical Engineering Dalian University of Technology Dalian China

The economic dispatch problem (EDP) poses a significant challenge in energy management for modern power systems, particularly as these systems undergo expansion. This growth escalates the demand for communication resources and increases the risk of communication failures. To address this challenge, we propose a distributed algorithm with network-independent step sizes and an event-triggered mechanism, which reduces communication requirements and enhances adaptability. Unlike traditional methods, our algorithm uses network-independent step sizes derived from each agent's local cost functions, thus eliminating the need for detailed network topology knowledge. The theoretical derivation identifies a range of step size values that depend solely on the objective function's strong convexity and the gradient's Lipschitz continuity. Furthermore, the proposed algorithm is shown to achieve a linear convergence rate, assuming the event triggering threshold criteria are met for linear convergence. Numerical experiments further validate the effectiveness and advantages of our proposed distributed algorithm by demonstrating its ability to maintain good convergence characteristics while reducing communication frequency. © 2024 John Wiley & Sons Ltd.

关键词： Cost functions

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Modeling and Simulation of Two Axes Gimbal Using Fuzzy control

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computers, Materials & Continua 2022年第7期72卷 93-107页

作者： Ayman A.Aly Mohamed O.Elhabib Bassem F.Felemban B.Saleh Dac-Nhuong Le Department of Mechanical Engineering College of EngineeringTaif UniversityTaif21944Saudi Arabia Control and Mechatronics Division School of Electrical EngineeringUTMJohor Bahru81300Malaysia Institute of Research and Development Duy Tan UniversityDanang550000Vietnam School of Computer Science Duy Tan UniversityDanang550000Vietnam

The application of the guided missile seeker is to provide stability to the sensor’s line of sight toward a target by isolating it from the missile motion and *** main objective of this paper is not only to present the physical modeling of two axes gimbal system but also to improve its performance through using fuzzy logic controlling *** paper is started by deriving the mathematical model for gimbals motion using Newton’s second law,followed by designing the mechanical parts of model using SOLIDWORKS and converted to xml file to connect dc motors and sensors using MATLAB/***,a Mamdani-type fuzzy and a Proportional-Integral-Derivative(PID)controllers were designed using MATLAB *** performance of both controllers was evaluated and tested for different types of input *** simulation results showed that self-tuning fuzzy controller provides better performance,since no overshoot,small steady-state error and small settling time compared to PID controller.

关键词： Gimbal system self-tuning fuzzy proportional-integral-derivative(PID)control cross coupling

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Delayed Transitions in GPenSIM 1st

Delayed Transitions in GPenSIM

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1st International Symposium on Systems Modelling and Simulation, SMS 2024

作者： Feng, Yuming Samolej, Slawomir Davidrajuh, Reggie School of Computer Science and Engineering Chongqing Three Gorges University Wenzhou China Department Computer and Control Engineering Rzeszow University of Technology Rzeszow Poland Department Electrical Engineering and Computer Science University of Stavanger Stavanger Norway

ISBN: (纸本)9789819646128

The General-purpose Petri Net Simulator (GPenSIM) is a tool for modeling, simulation, and performance analysis of discrete event systems. GPenSIM is specially designed to model real-life industrial systems. Hence, the transitions in GPenSIM represent real-life events, such as machines. However, this induces a problem, namely that an enabled transition consumes tokens from its input places immediately. This act of an enabled transition immediately consuming tokens gives only monetarily visibility to the tokens, which can be a problem for certain cases where we need to see the tokens in their input places for a while. This paper proposes a method to delay an enabled transition ("delayed transitions") so that the tokens it is supposed to consume from its input places will be visible for a while. This paper, after presenting the theory and the method, also presents an application (the cat and mouse problem) of the delayed transitions. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Discrete event simulation

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