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Metaheuristic Optimization for Mobile Robot Navigation Based on Path Planning

computers, Materials & Continua 2022年第11期73卷 2241-2255页

作者： El-Sayed M.El-kenawy Zeeshan Shafi Khan Abdelhameed Ibrahim Bandar Abdullah Aloyaydi Hesham Arafat Ali Ali E.Takieldeen Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Science Department College of Engineering and Computer ScienceMustaqbal UniversityBuraidahSaudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Mechanical Engineering Qassim UniversityBuraidah51452Saudi Arabia

Recently,the path planning problem may be considered one of the most interesting researched topics in autonomous *** is why finding a safe path in a cluttered environment for a mobile robot is a significant requisite.A promising route planning for mobile robots on one side saves time and,on the other side,reduces the wear and tear on the robot,saving the capital *** route planning methods for the mobile robot have been developed and *** to our best knowledge,no method offers an optimum solution among the existing *** Swarm Optimization(PSO),a numerical optimization method based on the mobility of virtual particles in a multidimensional space,is considered one of the best algorithms for route planning under constantly changing environmental *** the researchers,reactive methods are increasingly common and extensively used for the training of neural networks in order to have efficient route planning for mobile *** paper proposes a PSO Weighted Grey Wolf Optimization(PSOWGWO)*** is a hybrid algorithm based on enhanced Grey Wolf Optimization(GWO)with *** order to measure the statistical efficiency of the proposed algorithm,Wilcoxon rank-sum and ANOVA statistical tests are *** experimental results demonstrate a 25%to 45%enhancement in terms of Area Under Curve(AUC).Moreover,superior performance in terms of data size,path planning time,and accuracy is demonstrated over other state-of-the-art techniques.

关键词： Mobile robot swarm optimization robot route planning neural networks

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Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis 2

Complex Permeability Determination for EE Core Based on Flex...

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2nd China Power Supply Society Electromagnetic Compatibility Conference, CPEMC 2024

作者： Jie, Huamin Zhao, Zhenyu Chang, Yongqi Wang, Changdong Jiang, Shiqi Gao, Richard Xian-Ke See, Kye Yak School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Institute of High Performance Computing A*STAR Singapore Singapore

ISBN: (纸本)9798331509552

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz. ©2024 IEEE.

关键词： Magnetic flux

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Finite Sample Analysis for a Class of Subspace Identification Methods 63

Finite Sample Analysis for a Class of Subspace Identificatio...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： He, Jiabao Ziemann, Ingvar Rojas, Cristian R. Hjalmarsson, Hakan Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden University of Pennsylvania PhiladelphiaPA19104 United States

ISBN: (纸本)9798350316339

While subspace identification methods (SIMs) are appealing due to their simple parameterization for MIMO systems and robust numerical realizations, a comprehensive statistical analysis of SIMs remains an open problem, especially in the non-asymptotic regime. In this work, we provide a finite sample analysis for a class of SIMs, which reveals that the convergence rates for estimating Markov parameters and system matrices are O(1 / SN), in line with classical asymptotic results. Based on the observation that the model format in classical SIMs is non-causal because of a projection step, we choose a parsimonious SIM that bypasses the projection step and strictly enforces a causal model to facilitate the analysis, where a bank of ARX models are estimated in parallel. Leveraging recent results from a finite sample analysis of an individual ARX model, we obtain a union error bound for an array of ARX models and proceed to derive error bounds for system matrices using robustness results for the singular value decomposition. © 2024 IEEE.

关键词： Singular value decomposition

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Adaptive Fault Detection Scheme Using an Optimized Self-healing Ensemble Machine Learning Algorithm

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CSEE Journal of Power and Energy Systems 2022年第4期8卷 1145-1156页

作者： Levent Yavuz Ahmet Soran AhmetÖnen Xiangjun Li S.M.Muyeen Electrical and Computer Engineering Department in Abdullah Gül University Kayseri 38080Turkey Department of Electrical and Computer Engineering College of EngineeringSultan Qaboos UniversityAl-KhoudMuscat123Oman Department of Electrical Engineering Qatar UniversityDoha 2713Qatar State Key Laboratory of Control and Operation of Renewable Energy and Storage Systems China Electric Power Rescarch InstituteBeijing 100192China

This paper proposes a new cost-efficient,adaptive,and self-healing algorithm in real time that detects faults in a short period with high accuracy,even in the situations when it is difficult to *** than using traditional machine learning(ML)algorithms or hybrid signal processing techniques,a new framework based on an optimization enabled weighted ensemble method is developed that combines essential ML *** the proposed method,the system will select and compound appropriate ML algorithms based on Particle Swarm Optimization(PSO)*** this purpose,power system failures are simulated by using the PSCA D-Python *** of the salient features of this study is that the proposed solution works on real-time raw data without using any pre-computational techniques or pre-stored ***,the proposed technique will be able to work on different systems,topologies,or data *** proposed fault detection technique is validated by using PSCAD-Python co-simulation on a modified and standard IEEE-14 and standard IEEE-39 bus considering network faults which are difficult to detect.

关键词： Decision tree(DT) ensemble machine learning algorithm fault detection islanding operation k-Nearest Neighbor(kNN) linear discriminant analysis(LDA) logistic regression(LR) Naive Bayes(NB) self-healing algorithm

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Editorial: The Second International Workshop on Artificial Intelligence Systems in Education - AIxEDU 2

Editorial: The Second International Workshop on Artificial I...

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2nd International Workshop on Artificial INtelligent Systems in Education, AIxEDU 2024

作者： Casalino, Gabriella Limongelli, Carla Schicchi, Daniele Taibi, Davide Temperini, Marco Department of Computer Science University of Bari Aldo Moro Bari Italy Department of Civil Computer Science and Aeronautical Technologies Engineering Roma Tre University Rome Italy Institute for Educational Technology Italian National Research Council CNR-ITD Palermo Italy Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

The Second International Workshop on Artificial Intelligence Systems in Education (AIxEDU) marks its 2024 edition in conjunction with the 23rd International Conference of the Italian Association for Artificial Intelligence (AIxIA), held from 25-28 November 2024 in Bolzano, Italy. This workshop brings together Artificial Intelligence and Education experts to explore the latest innovations and best practices in applying AI to educational contexts. Participants discuss recent trends, research initiatives, and emerging developments in AI technologies that aim to enhance teaching methodologies, support personalized learning, and address pressing educational challenges. The workshop emphasizes a multidisciplinary approach to understanding how AI systems can promote inclusion, improve learning outcomes, and empower educators while addressing ethical considerations and ensuring equitable access to education aligned with global sustainable development goals. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Adversarial machine learning

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High Speed Machining for Linear Paths Blended with G3 Continuous Pythagorean-Hodograph Curves

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Journal of Systems Science & Complexity 2022年第4期35卷 1586-1607页

作者： ZHAO Kai LI Shurong College of Control Science and Engineering China University of Petroleum(East China)Qingdao266580China College of Computer Science and Information Engineering Anyang Institute of TechnologyAnyang455000China School of Artificial Intelligence Beijing University of Posts and TelecommunicationsBeijing100876China

Previously,many studies have illustrated corner blend problem with different parameter *** a few of them take a Pythagorean-hodograph(PH)curve as the transition arc,let alone corresponding real-time interpolation *** this paper,an integrated corner-transition mixing-interpolation-based scheme(ICMS)is proposed,considering transition error and machine tool ***,the ICMS smooths the sharp corners in a linear path through blending the linear path with G3 continuous PH transition *** obtain optimal PH transition curves globally,the problem of corner smoothing is formulated as an optimization problem with *** order to improve optimization efficiency,the transition error constraint is deduced analytically,so is the curvature extreme of each transition *** being blended with PH transition curves,a linear path has become a blend ***,the ICMS adopts a novel mixed interpolator to process this kind of blend curves by considering machine tool *** mixed interpolator can not only implement jerk-limited feedrate scheduling with critical points detection,but also realize self-switching of two interpolation ***,two patterns are machined with a carving platform based on *** l results show the effectiveness of ICMS.

关键词： Bézier control polygon corner transition jerk-limited scheduling mixed interpolation pythagorean-hodograph curve

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Design and Realization of Unmanned Vehicle Autonomous Navigation System Based on Binocular Camera 3

Design and Realization of Unmanned Vehicle Autonomous Naviga...

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3rd International Conference on computer Science, Electronic Information engineering and Intelligent control Technology, CEI 2023

作者： Guo, Tianxing Lin, Lianlei Liu, Huanyu Li, Junbao School of Electronics and Information Engineering Harbin Institute of Technology Department of Automatic Test and Control Harbin China Information Countermeasure Technique Institute School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350372052

Aiming at the navigation problem of unmanned vehicles in extreme environments such as communication interference and limited GPS signals, this study proposes an autonomous navigation method based on binocular cameras. The method enables the unmanned vehicle to complete the task of localization and map building using only binocular images, without the need for other sensors or signal sources. Meanwhile, this study also proposes a local path planning obstacle avoidance method based on depth map, which, when combined with global localization information, can take into account both local obstacle avoidance and global path navigation, and can cope with random environmental changes. The system uses a single sensor for autonomous obstacle avoidance and navigation, which reduces the computational requirements and ensures the low cost of the navigation system. In order to verify the reliability and effectiveness of the system under signal-constrained conditions, the system is evaluated in a simulation environment and a real field scenario, respectively. The experimental results show that the system is able to achieve reliable localization and path planning under signal-constrained conditions. © 2023 IEEE.

关键词： Cameras

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An Ensemble of UNet Frameworks for Lung Nodule Segmentation

An Ensemble of UNet Frameworks for Lung Nodule Segmentatio...

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International Conference on Actual Problems of Applied Mathematics and computer Systems, APAMCS 2022

作者： Gautam, Nandita Basu, Abhishek Kaplun, Dmitry Sarkar, Ram Department of Computer Science and Engineering Jadavpur University Kolkata India Department of Computer Science and Engineering National Institute of Technology Durgapur Durgapur India Department of Automation and Control Processes Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia

ISBN: (纸本)9783031341267

One of the most common types of cancer in the world is lung cancer, which is a cause of increasing mortality. It is most often discovered in the middle and later stages as it does not have obvious symptoms due to which its treatment is often missed. Studies show that most lung cancers are in the form of lung nodules, which can be categorized as benign or malignant. Thus, accurate early identification of malignant lung nodules that might later become cancerous is essential for the prevention of lung cancer. Computed Tomography (CT) images can be useful for identifying and segmenting these nodules. In this paper, we propose an ensemble model, called BUS-UNet++, to segment lung nodules using CT images. We use a combination of the ConvLSTM up-sampling architecture from BUS-UNet and skip connections in aggregation blocks from the UNet++ model to build the BUS-UNet++ ensemble. The dataset for this study is collected from the Lung Image Database Consortium Image Database Resource Initiative (LIDC-IDRI), where we have selected the modality of these images as CT images. These are further preprocessed to obtain nodule masks and nodule images, which constitute the Region of Interest (RoI). The accuracy achieved with the Adam Optimizer is 0.9731, the Intersection over Union (IoU) of about 0.8439, and the dice score coefficient (DSC) of about 0.958 are obtained by the proposed system. This ensemble model outperforms several state-of-the-art models used for the same purpose. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Image segmentation

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Shared-control design for robot-assisted surgery using a skill assessment approach

Shared-control design for robot-assisted surgery using a ski...

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作者： Song, Kai-Tai Hsieh, Ping-Jui Institute of Electrical and Control Engineering College of Electrical and Computer Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

In this article, a shared-control system with skill-based share weight allocation is proposed for a robot-assisted minimally invasive surgery (MIS) procedure. A convolution neural network (CNN) is trained for online skill assessment, and the result is used to generate the share weights of robot autonomy and the user remote control. The control system can ensure synchronization of the two commands from the surgeon and robot autonomy and combine them to determine the motion of the surgical instrument. In this work, a contour-tracking task is handled by the suggested shared controller to simulate a surgical cutting operation. Experimental results on a lab-built robotic platform are presented to show the effectiveness of the proposed method. Multiple contour-tracking experiments have been tested to compare the tracking performances of pure manual remote control and the proposed shared-control method. Experimental results show that the shared controller achieved 34.5% improvement in tracking accuracy in comparison with pure manual control. © 2021 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Remote control

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Sigma-Mixed Unscented Kalman Filter-Based Fault Detection for Traction Systems in High-Speed Trains

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Chinese Journal of Electronics 2023年第5期32卷 982-991页

作者： CHENG Chao WANG Weijun MENG Xiangxi SHAO Haidong CHEN Hongtian Department of Computer Science and Technology Changchun University of Technology Department of Mathematics and Statistics Changchun University of Technology Institute of System Research China Industrial Control Systems Cyber Emergency Response Team Department of Mechanical and Vehicle Engineering Hunan University Department of Chemical and Materials Engineering University of Alberta

Fault detection(FD) for traction systems is one of the active topics in the railway and academia because it is the initial step for the running reliability and safety of high-speed trains. Heterogeneity of data and complexity of systems have brought new challenges to the traditional FD methods. For addressing these challenges, this paper designs an FD algorithm based on the improved unscented Kalman filter(UKF) with consideration of performance degradation. It is derived by incorporating a degradation process into the state-space *** network topology of traction systems is taken into consideration for improving the performance of state estimation. We first obtain the mixture distribution by the mixture of sigma points in UKF. Then, the Lévy process with jump points is introduced to construct the degradation model. Finally, the moving average interstate standard deviation(MAISD) is designed for detecting *** the proposed methods via a traction systems in a certain type of trains obtains satisfactory results.

关键词： Degradation Network topology Fault detection Rail transportation State-space methods Safety Kalman filters

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