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7th Edition Global Conference on Wireless and Optical Technologies, GCWOT 2024

作者： Shaikh, Muhammad Zakir Baro, Enrique Nava Baloch, Yaqoob Ali Hussain, Tanweer Uqaili, Mohammad Aslam Chowdhry, Bhawani Shankar School of Industrial Engineering University of Malaga Malaga Spain Jamshoro Pakistan Universidad de Malaga Departamento de Ingeniería de Comunicaciones Campus de Teatinos Malaga Spain National Center of Robotics and Automation Cms Lab Jamshoro Pakistan Mehran University of Engineering and Technology National Center of Robotics and Automation Cms Lab Department of Electrical Engineering Jamshoro Pakistan

ISBN: (纸本)9798331534271

Railway wheels are one of the most critical components of the railway infrastructure, functioning as the load carrier. They are exposed to various forms of damage, caused due to intense sliding friction and inadequate inspection procedures. This research introduces a real-time wheel fault detection system using YOLOv8, leveraging computer vision and AI-based object detection. The main contribution of this research is the utilization of a custom data acquisition setup for capturing wheel images and detecting faults with high accuracy and speed. Our results demonstrate an overall F1 score of 0.80, with precision and recall curves indicating strong wheel detection and moderate defect detection capabilities. This approach aims the reduction of inspection costs and the improvement of railway safety through automation and digitization. © 2024 IEEE.

关键词： Railroads

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A Survey of Underwater Multi-Robot Systems

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 1-18页

作者： Ziye Zhou Jincun Liu Junzhi Yu State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and RoboticsBeijing Innovation Center for Engineering Science and Advanced TechnologyCollege of EngineeringPeking UniversityBeijing 100871China College of Information and Electrical Engineering China Agricultural UniversityBeijing 100083China

As a cross-cutting field between ocean development and multi-robot system(MRS),the underwater multi-robot system(UMRS)has gained increasing attention from researchers and engineers in recent *** this paper,we present a comprehensive survey of cooperation issues,one of the key components of UMRS,from the perspective of the emergence of new *** specifically,we categorize the cooperation in terms of task-space,motion-space,measurement-space,as well as their ***,we analyze the architecture of UMRS from three aspects,i.e.,the performance of the individual underwater robot,the new functions of underwater robots,and the technical approaches of *** conclude,we have discussed related promising directions for future *** survey provides valuable insight into the reasonable utilization of UMRS to attain diverse underwater tasks in complex ocean application scenarios.

关键词： Cooperation formation control multi-robot systems(MRS) taxonomy underwater robots underwater tasks

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Low-Cost 3D Holographic Display with Gesture Control 6

Low-Cost 3D Holographic Display with Gesture Control

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6th Global Conference on Wireless and Optical Technologies, GCWOT 2023

作者： Bibi, Saima Imran, Ayesha Saud, Safwan Maheshwari, Mukesh Kumar Shankar Chowdhry, Bhawani Ejaz, Waleed Bahria University Karachi Campus Department of Electrical Engineering Karachi Pakistan Mehran University of Engineering & Technology National Center of Robotics & Automation Condition Monitoring Systems Lab Jamshoro Pakistan Lakehead University Department of Electrical Engineering BarrieON Canada

ISBN: (纸本)9798350333718

A way behind the past where teaching and learning were only by video, images, and 2D animations. Now we have live sessions where a classroom is bounded on just a laptop screen. What happened if that live session and 3D imaging are presented in the form of real sculpture by using Augmented Reality? In this paper, we are introducing a low-cost 3D display that presents both recorded and live sessions. Also, this display will be controlled with our fingertips. This application covers sectors of education, medical imaging, and advertisements with good effects and cheap cost. © 2023 IEEE.

关键词： Holograms

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Strictly Decentralized Approaches for Multi-Robot Grasp Coordination 19

Strictly Decentralized Approaches for Multi-Robot Grasp Coor...

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19th IEEE International Conference on automation Science and Engineering, CASE 2023

作者： Muthusamy, Rajkumar Kyrki, Ville Muthusamy, Praveen Kumar Taha, Tarek Hussain, Irfan Zweiri, Yahya Prattichizzo, Domenico Gan, Dongming Robotics Lab Dubai Future Labs Dubai United Arab Emirates Aalto University Intelligent Robotics Group Department of Electrical Engineering and Automation Finland Khalifa University of Science and Technology Abu Dhabi United Arab Emirates Istituto Italiano di Tecnologia Department of Advanced Robotics Genoa16163 Italy Purdue University United States

ISBN: (纸本)9798350320695

Grasp coordination is crucial for performing cooperative object manipulation tasks. Planning cooperative grasps among a group of decentralized robots is a new line of coordination problem that requires robots to simultaneously handle complex and large shaped and sized objects, a new level of difficulty that is rarely addressed in the literature. In this paper, we propose grasp coordination approaches for a decentralized group of robots facing explicit communication and sensing limitations. In particular, a scenario where robots with incomplete knowledge about each other's embodiments further lose the ability to 1. observe others' grasps occluded by the object's shape 2. exchange direct messages due to potential communication degradation resulting from the real-time planning and execution constraints. To tackle such a scenario, we introduce two baseline and two probabilistic approaches that are specifically designed for strict decentralization. The approaches analyze cooperative grasps using traditional grasp quality metrics and estimate cooperative grasps based on the assigned robot's priority. Simulation experiments demonstrate that the probabilistic approaches exhibit superior performance over the baseline approaches, reaching performance close to optimal for both homogeneous and heterogeneous groups. These approaches provide solutions to simulated multi-robot grasp coordination scenarios that have the potential to translate to real-world environments such as logistics, manufacturing, and services. © 2023 IEEE.

关键词： Industrial robots

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Reinforcement Fuzzy Q-Learning Incorporated with Genetic Kinematics Analysis for Self-organizing Holonomic Motion Control of Six-Link Stewart Platforms

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International Journal of Fuzzy Systems 2023年第3期25卷 1239-1255页

作者： Huang, Hsu-Chih Xu, Sendren Sheng-Dong Chen, Yu-Xiang Chen, Chien-Ming Department of Electrical Engineering National Ilan University Yilan260007 Taiwan Graduate Institute of Automation and Control National Taiwan University of Science and Technology Taipei106335 Taiwan Advanced Manufacturing Research Center National Taiwan University of Science and Technology Taipei106335 Taiwan

This paper contributes to the development of reinforcement fuzzy Q-learning incorporated with genetic kinematics analysis for self-organizing holonomic motion control of six-link Stewart platforms. The fuzzy theory is integrated with the Q-learning algorithm to develop a hybrid reinforcement learning strategy. Both the actions and the Q-functions in the classical Q-learning algorithm are inferred by means of fuzzy rules. The proposed hybrid reinforcement learning is then applied to self-organizing holonomic motion control of parallel Stewart platforms for industrial applications. After the kinematics analysis using a geometrical approach and genetic algorithm (GA)-based Newton–Raphson formulation, this study develops a practical control scheme that combines fuzzy Q-learning and proportional–integral–differential (PID) control scheme, called FQPID. In the proposed FQPID holonomic motion control method, the PID control gains are online-tuned via the fuzzy Q-learning computation process. An experimental Stewart platform consisting of six servo motors, adjustable links, and two platforms is constructed to illustrate the effectiveness of the presented methods. The experimental results are compared with some existing control methods using the same evaluation criterion. Through the experimental results and comparative works, the superiority of the proposed FQPID control scheme is presented and discussed. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.

关键词： Reinforcement learning

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Effect of Tine Shaped Furrow Opener on Dry Soil Using Discrete Element Modelling

Effect of Tine Shaped Furrow Opener on Dry Soil Using Discre...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Abdul Mohiz Fazal E Nasir Kamran Shah Department of Mechatronics Engineering University of Engineering & Technology Peshawar Pakistan Advanced Robotics & Automation Lab National Center of Robotics & Automation Peshawar Pakistan

Tillage of the soil is the most important consideration when it comes to the implementation of agricultural practices. Increases in crop yield has been achieved through a variety of agricultural practices thanks to the discoveries of various agricultural experts. The planting process is the one that has the greatest impact on the crop's overall health. The hull can be more precisely prepared for the seed-planting trench with the assistance of furrows. A variety of furrow openers are currently undergoing the implantation process. Studying dynamic systems that are discontinuous in nature can be done with the help of discrete element modelling. The simulation of a tine-shaped furrow opener using the EDEM package software was carried out for three different speeds. When the speed of an object increases, so does the force it exerts on it. Additionally, the length of an object has an effect on the force it exerts. Additionally, taken into consideration were the profiles that were generated in the soil. To carry out statistical validation of the results analysis of variation (ANOVA) was done. The results provided a basis for calculating a confidence level of 95%. For the furrow openers, it was suggested that a speed of 0.495 meters per second, which is equivalent to 1.76 kilometers per hour, be used.

关键词： Meters Industries automation Force Crops Soil Software

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Personalized Federated Learning with Collaborative Aggregation Networks for Multi-Site Brain Disorder Diagnosis 4

Personalized Federated Learning with Collaborative Aggregati...

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4th International Conference on Industrial automation, robotics and Control Engineering, IARCE 2024

作者： Si, Qian Li, Yang School of Cyber Science and Technology Beihang University Beijing China Department of Automation Science and Electrical Engineering The Beijing Advanced Innovation Center for Big Data and Brain Computing State Key Laboratory of Virtual Reality Technology and Systems Beijing China Advanced Institute of Information Technology Peking University Beijing China Beihang University Beijing China

ISBN: (纸本)9798350380323

In multi-site brain disease diagnosis studies, traditional centralized training methods necessitate sharing medical data, posing significant privacy risks. Federated learning (FL) offers a privacy-preserving solution by enabling global model training through aggregating locally trained models from multiple data centers without sharing raw data. However, current FL approaches rely on a server-based network topology, where central server failure disrupts training. Additionally, data heterogeneity across sites often slows convergence and reduces accuracy. To overcome these issues, we introduce a decentralized personalized federated learning collaborative aggregation network (pFedCAN). This framework has two core components: (1) separating local models into shared and personalized layers, and (2) forming a collaborative aggregation network via similarity detection in the shared layers. Specifically, each center trains its local model, then separates it into shared and personalized layers. The shared layer is exchanged with other centers, while the personalized layer remains local. Data centers analyze similarities in received shared layers to build a collaborative network, where shared layers from similar centers are aggregated to refine the model. This approach flexibly adapts to varying levels of data heterogeneity, enhancing model training efficiency. Validation on public datasets, ABIDE I and ADHD, shows that the proposed method outperforms current leading techniques. © 2024 IEEE.

关键词： Federated learning

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A Gamma Process Based Degradation Model with Fractional Gaussian Noise 16

A Gamma Process Based Degradation Model with Fractional Gaus...

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16th Annual Conference of the Prognostics and Health Management Society, PHM 2024

作者： Wang, Xiangyu Xi, Xiaopeng Orchard, Marcos E. College of Electrical Engineering and Automation Shandong University of Science and Technology Shandong Qingdao266590 China Advanced Center for Electrical and Electronic Engineering Universidad Técnica Federico Santa María Valparaíso Chile Department of Electrical Engineering Faculty of Mathematical and Physical Sciences Universidad de Chile Santiago Chile

ISBN: (纸本)9781936263059

In modern industrial and engineering systems, stochastic degradation models are widely used for reliability analysis and maintenance decision-making. However, due to imperfect sensors and environmental influences, it is difficult to directly observe the latent degradation states. Traditional degradation models typically assume that measurement errors have simple statistical properties, but this assumption often does not hold in practical applications. To address this issue, this paper constructs a degradation model based on the Gamma process (GP) and assumes that measurement noise can be characterized by the fractional Gaussian noise (FGN). Furthermore, this paper proposes a method combining Gibbs sampling with the stochastic expectation-maximization (SEM) algorithm to achieve efficient estimation of the model parameters and accurate inference of the latent degradation states. Simulation results demonstrate that the proposed model, validated solely through numerical simulations, exhibits improved generalizability compared to the GP model with Gaussian noise. © 2024 Prognostics and Health Management Society. All rights reserved.

关键词： Reliability analysis

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Diagnosis of Localized Bearing Defects using Texture Analysis of Vibration Envelope Signals and Machine Learning

Diagnosis of Localized Bearing Defects using Texture Analysi...

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2023 International Conference on robotics and automation in Industry, ICRAI 2023

作者： Nguyen, Cong Dai Nasir, Fazal E. Khan, Shahbaz Khan, Sheraz Ali Kim, Jong-Myon Le Quy Don Technical University Faculty of Radio-Electronic Engineering Hanoi Viet Nam Advanced Robotics and Automation Lab National Center for Robotics and Automation Peshawar Pakistan Institute of Manufacturing University of Engineering and Applied Sciences Swat Pakistan University of Engineering and Technology Department of Mechatronics Engineering Peshawar Pakistan University of Ulsan Department of IT Convergence Ulsan Korea Republic of PD Technology Ulsan Korea Republic of

ISBN: (纸本)9781665464727

Bearings are important because they play a critical role in the operation of many machines and devices by reducing friction and enabling smooth motion between two moving parts. They are commonly used in rotating machinery, such as electric motors, turbines, pumps, and gearboxes, where they support and guide the rotating shafts. The primary cause of failure in wind turbines and induction motors is bearing faults, resulting in significant downtime and economic losses. Detecting these faults accurately and promptly is crucial to preventing unexpected shutdowns. Most of the existing methods for bearing fault detection rely on envelope analysis, which involves filtering and demodulating the raw signal, and Fourier analysis of the envelope signal to identify defect frequencies. Recent research has focused on improving the visibility of these frequencies by selecting an optimal band for filtering, using sub-band analysis and spectral kurtosis, which is a complex process and can be time-consuming. This paper presents a new approach to envelope signal analysis using texture analysis of the envelope signals that are projected as 2D grayscale images where each fault generates a unique texture. These textures are encoded using the local binary pattern operator and then used for fault classification. The method is tested on a publicly available seeded fault dataset. © 2023 IEEE.

关键词： Signal analysis

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Backstepping-Based Adaptive Cooperative Control For Multiple Euler-Lagrange Systems Under Unknown Harmonic Disturbances

Backstepping-Based Adaptive Cooperative Control For Multiple...

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2023 China automation Congress, CAC 2023

作者： Chen, Ying Zhao, Zi-Yi Sun, Peng Guo, Xiang-Gui Wang, Jian-Liang Coutinho, Daniel School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing Engineering Research Center of Industrial Spectrum Imaging Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Hangzhou Innovation Institute of Beihang University Collaborative Flying Robotics HangZhou China Universidade Federal de Santa Catarina Department of Automation and Systems Florianópolis Brazil

ISBN: (纸本)9798350303759

This paper studies cooperative control problem for multiple Euler-Lagrange systems with unknown harmonic disturbances, where the disturbances are the superposition of sinusoidal components with unknown amplitude, phase, and frequency. A novel adaptive disturbance observer without requiring the disturbance frequency information is designed to estimate the disturbances. Over the directed network topology, a cooperative control scheme is proposed based on backstepping techniques, so that the tracking error is ultimately uniformly bounded. The scheme developed can be used to reject the harmonic disturbances in a uniform way, which means the characteristics of the disturbances can be described as a fixed parameter vector. Finally, an application is presented to demonstrate the effectiveness of the proposed control strategy in the context of a two-link manipulator system. © 2023 IEEE.

关键词： Backstepping

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