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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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OFF-CLIP: Improving Normal Detection Confidence in Radiology CLIP with Simple Off-Diagonal Term Auto-Adjustment

arXiv

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arXiv 2025年

作者： Park, Junhyun Moon, Chanyu Lee, Donghwan Kim, Kyungsu Hwang, Minho Department of Robotics and Mechatronics Engineering DGIST Korea Republic of Department of Electrical Engineering and Computer Science DGIST Korea Republic of Seoul National University Korea Republic of

Contrastive Language-Image Pre-Training (CLIP) has enabled zero-shot classification in radiology, reducing reliance on manual annotations. However, conventional contrastive learning struggles with normal case detection due to its strict intra-sample alignment, which disrupts normal sample clustering and leads to high false positives (FPs) and false negatives (FNs). To address these issues, we propose OFF-CLIP, a contrastive learning refinement that improves normal detection by introducing an off-diagonal term loss to enhance normal sample clustering and applying sentence-level text filtering to mitigate FNs by removing misaligned normal statements from abnormal reports. OFF-CLIP can be applied to radiology CLIP models without requiring any architectural modifications. Experimental results show that OFF-CLIP significantly improves normal classification, achieving a 0.61 Area under the curve (AUC) increase on VinDr-CXR over CARZero, the state-of-the-art zero-shot classification baseline, while maintaining or improving abnormal classification performance. Additionally, OFF-CLIP enhances zero-shot grounding by improving pointing game accuracy, confirming better anomaly localization. These results demonstrate OFF-CLIP’s effectiveness as a robust and efficient enhancement for medical vision-language models. Copyright © 2025, The Authors. All rights reserved.

关键词： Radiology

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Parking Lines and Indoor Structural Feature-based SLAM with 2D LiDAR and AVM for Indoor Autonomous Parking

Parking Lines and Indoor Structural Feature-based SLAM with ...

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International Conference on Control, Automation and Systems ( ICCAS)

作者： Sekang Oh Taehyun Lim Yonggu Kang Seonghan Kim Department of Intelligent Mechatronics Engineering Sejong University Seoul Korea Department of Artificial Intelligence and Robotics Sejong University Seoul Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

Accurate localization is essential to achieve Automated Valet Parking (AVP) without collisions. However, indoor parking facilities where the use of GPS is restricted are usually lack of maps. This study proposes a Simultaneous Localization And Mapping (SLAM) approach that combines parking line information detected by Around View Monitor (AVM) with the scan data by a 2D LiDAR. The parking line information is extracted using a parking slot detection model and then fused with the scan data. Finally, an indoor map that includes parking spaces is created based on the fused scan data. The proposed method results in low computational requirements, and the generated map contains information such as parking lines, pillars, and walls, which enables accurate real-time localization. This generated map can be utilized in future AVP research to navigate from one location in the parking facility to an available parking space.

关键词： Location awareness Simultaneous localization and mapping Laser radar Accuracy Navigation Feature extraction Real-time systems Data mining Monitoring Global Positioning System

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Self-Aware AI-Based Anomaly Detection for AI IoT Enabled Smart Healthcare System

Self-Aware AI-Based Anomaly Detection for AI IoT Enabled Sma...

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Computing and Information Technology (ICCIT-1441), 2020 International Conference on

作者： Yusra Shereen Muhammad Farrukh Shahid Muhammad Hassan Tanveer School of Computing FAST - NUCES Karachi Pakistan Department of Robotics & Mechatronics Engineering Kennesaw State University Marietta GA USA

ISBN: (数字)9798350353839

ISBN: (纸本)9798350353846

The Internet of Things (IoT) based smart healthcare systems can significantly enhance the quality of patient care. These systems can enable healthcare providers to monitor patient conditions in real time. IoT-based smart healthcare systems have the potential to revolutionize the way we provide care. Anomaly detection is crucial in IoT-based smart healthcare systems due to numerous reasons. It plays a dominant role in proactive health-care analysis, especially in brain diseases. In brain Magnetic Res-onance Imaging (MRI), anomaly detection helps in identifying several abnormalities, such as cysts, strokes, infections, vascular and developmental malformations, and neurological disorders like Alzheimer's and multiple sclerosis. The existing approaches of brain MRI anomaly detection, and anomaly detection in IoT-based smart healthcare systems utilizes static AI models. Conventional AI based models can be trained once and cannot tackle the changes in real time. The population health and the nature of disease consistently change, and conventional AI based models can't adapt to those changes. Conventional AI based system cannot tackle the changes caused by variations like diseases and public health and become ineffective over the time. Self-aware AI models can address these issues as they can learn and adapt to their environment. Self-aware AI-based systems have the potential to change lives through their ability to learn, adapt, and improve over time. In this paper, we proposed a novel approach to anomaly detection based on self-aware AI in IoT-based smart healthcare systems. Additionally, an algorithm for anomaly detection in MRI images, namely Self-Aware AI based Anomaly Detection (SAAD) is proposed. Our proposed system can detect anomalies in brain MRI images. We achieved 98% accuracy and 0.99 precision and recall, outperforming the existing approaches. The proposed self-aware AI based anomaly detection framework for IoT-based smart healthcare systems has the potential

关键词： Adaptation models Magnetic resonance imaging Medical services Brain modeling Real-time systems Internet of Things Artificial intelligence Public healthcare Anomaly detection Self-aware

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Evaluation of Perceived Intelligence for a Collaborative Manipulator Sharing its Workspace with a Human Operator

Evaluation of Perceived Intelligence for a Collaborative Man...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Inara Tusseyeva Artemiy Oleinikov Anara Sandygulova Matteo Rubagotti Department of Robotics and Mechatronics School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan

This paper studies the perception of robot intelligence for a manipulator that shares its workspace with a human operator, while the two execute independent tasks. Four different motion planning algorithms were employed to plan the robot motion in four subsequent experimental sets for 48 participants, and the order with which these algorithms were used was changed, obtaining all possible combinations. While guaranteeing safety, each of the four algorithms exhibited a different level of adaptability and reactivity, in terms of real-time motion planning abilities and of speed reduction based on heart rate feedback. We analyzed how perceived intelligence was influenced by the employed algorithm, by the order of execution and by the previous experience of the participants working with robots. In conclusion, perceived intelligence resulted being significantly lower in the first experimental set compared to the following ones, which showed a positive effect of habituation on perceived intelligence. On the other hand, neither the use of different motion planning algorithms nor the previous participants’ experience significantly influenced perceived intelligence.

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Au-Based Biocompatible Capacitive Strain Sensor

Au-Based Biocompatible Capacitive Strain Sensor

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IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS)

作者： Mugeun Lee Hwajoong Kim Jinho Kim Minji Jeong Jaehong Lee Department of robotics and mechatronics engineering Daegu Gyeongbuk Institute of Science and Technology Daegu Korea

Various strain sensors have been developed due to their capability to monitor a piece of basic physiological information. However, a lot of existing strain sensor is based on planar soft sensors, which have a few critical challenges such as structural mismatch and stable fixation on the target organ. Here, we present a 1-dimensional and biocompatible capacitive fiber strain sensor. The fiber strain sensor comprises a conductive fiber electrode based on Au, a representative biocompatible material. The structure of the fiber strain sensor is a double helix. The sensor shows high sensitivity of ~9.8 and high stability.

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Dynamic Modelling and Task-space Control of Vine-like Soft Growing Robots

Dynamic Modelling and Task-space Control of Vine-like Soft G...

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SICE Annual Conference

作者： Haitham El-Hussieny Department of Mechatronics and Robotics Engineering Egypt-Japan University of Science and Technology Alexandria Egypt

Soft-growing robots are promising for a variety of applications, such as navigating and inspecting confined and challenging environments. These robots can elongate up to tens of meters and have morphological adaptation and tip-extension capabilities. However, evaluating their performance across various design aspects or environmental conditions can be difficult due to their long manufacturing times. In this paper, we present a computationally efficient dynamics model derived using the Euler-Lagrange equation for a class of soft-growing robots known as “vine robots.” alongside a PD feedback control with gravity compensation. We have performed simulation experiments to validate both the dynamics model and the PD feedback control. The results of these experiments can provide valuable insights for future model-based feedback control design and simulation-based performance evaluation.

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Cost-Effective Pressure Glove to Measure Forces & Orientation from a Chiropractor

Cost-Effective Pressure Glove to Measure Forces & Orientatio...

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Opportunity Research Scholars Symposium (ORSS)

作者： Carolyn Butler Iti Shah Jacob Kish Muhammad Salman Robotics & Mechatronics Kennesaw State University Department of Mechanical Engineering Kennesaw State University

Currently, there is no affordable, everyday use chiropractic force sensor. Devices that are used to teach chiropractic students, such as activators and drop tables, assist students in learning but do not give adequate feedback. Our design will be implementing the cheapest materials to make the most reliable force sensing glove which chiropractors can use for their daily work needs. Materials needed to complete this project include pressure sensors, electrical wires, resistors, a breadboard, Raspberry Pi Pico W, a laptop with Thonny software installed, and an analog to digital converter. Our design of the chiropractic force sensor glove will help reduce the amount of confusion when determining the correct amount of force to apply to a chiropractor’s patient. This research will also help to dramatically reduce any severe pain resulting from misplaced forces and pressure applied to chiropractic patients.

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Control Simulation of Proportional-Integral and Sliding Mode Control for Precision Seed Planters

Control Simulation of Proportional-Integral and Sliding Mode...

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International Conference on robotics and Artificial Intelligence (ICRAI)

作者： Yasir Nawaz Muhammad Usman Qadir Muhammad Awais Khan Izhar Ul Haq Kamran Shah Tahir Khan Department of Mechatronics Advanced Robotics & Automation Lab University of Engineering and Technology Peshawar Pakistan

The desired development and design of an electric control system (ECS) for a precision planter is one of the most crucial elements in evaluating the efficacy of applicators for plant production. The seeds would be sown using this approach. Years have been invested in the continuous development of a range of application methods and metering systems, each of which offers specific advantages for applying the required system with a high degree of precision. Researchers worldwide have been trying to make electric-driven seed meters (EDSM) for planters, but they haven't succeeded. This study looks into the current state of installing seed metering systems for precision planters. Proportional-integral (PI) and sliding mode control (SMC) designs of the control system have been implemented to improve the planting quality of the planters. We want to highlight the electrically driven control system (EDCS) using these designs. An overview of the noteworthy features and limitations of past research is given. We also discuss several future directions for future research, concentrating on the knowledge gaps in this area.

关键词： Meters Industries PI control Automation System performance Production Robustness

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Low level position control for 4-DOF arm robot using fuzzy logic controller and 2-DOF PID controller

Low level position control for 4-DOF arm robot using fuzzy l...

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2021 International Mobile, Intelligent, and Ubiquitous Computing Conference, MIUCC 2021

作者： El-Khatib, Mohamed Fawzy Maged, Shady A. Faculty of Engineering Mechatronics and Robotics Engineering Department Badr City Cairo Egypt Ain Shams University Faculty of Engineering Mechanical and Mechatronics Engineering Department Cairo Egypt

ISBN: (纸本)9781665412438

The various types of applications for arm robots have made it one of the most important topics within the field. An important step to be considered is the application of a suitable control algorithm that takes into account the complex nonlinear dynamics. However, nonlinear control methods can still face difficulties due to the complexity of implementation. In this paper, four degrees of freedom (4-DOF) robot arm model is considered. Simple linear control methods are proposed to be used in the control of the angle of robotjoints. For this purpose, the fuzzy logic controller (FLC) and the two degree of freedom PID (2-DOF PID) controller are applied to control the joint angles of robot arm and in order to improve the response speed and reduce overshoot. The system simulation was performed using the MATLAB/Simulink software package. Simulation results show that the FLC has a faster response with a better rise time compared to the 2-DOF PID controller. © 2021 IEEE.

关键词： Fuzzy logic

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