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e-Journal of Nondestructive Testing 2023年第1期28卷

作者： Klimek, Zbigniew Paćko, Pawel Cracow branch Warsaw Poland AGH University of Science and Technology Faculty of Mechanical Engineering and Robotics Department of Robotics and Mechatronics Krakow Poland

This paper discusses challenges, limitations and problems arising in currently employed acoustic emission testing systems, sensors and signal processing algorithms. Main factors influencing and compromising accuracy and reliability of the classically used methods are briefly analyzed. Next, metamaterials and their dynamic properties are outlined with the aim and focus on their potential in manipulating energy flow. Several applications of metamaterials in acoustic emission are presented that indicate their potential in acoustic emission. Finally, possibilities of designing a new type of sensor for acoustic emission using metamaterials is discussed. As a consequence, it is expected to increase sensitivity and accuracy of source localization with smaller number of sensors used during measurements. © 2023 The Authors.

关键词： Metamaterials

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A Top-View Hand Gesture Recognition System for IoT Applications

A Top-View Hand Gesture Recognition System for IoT Applicati...

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International Conference on Smart Systems and Inventive Technology (ICSSIT)

作者： William J. Wisener Jorge Diaz Rodriguez Ammy Ovando Christopher Woolford Kishan Patel Dept. of Robotics & Mechatronics Engineering Department of Physics Kennesaw State University Atlanta Georgia

Gesture recognition integrated into Internet of Things (IoT) systems is a growing field with opportunities for improvement. Identifying hand gestures from vertical angles with a cooperative network of cameras can enable a broader collection of control methods for controlling IoT devices within residential and commercial environments. Integrating this smart home framework with other IoT control methodologies also creates a more user-friendly experience. To generate a proof of concept of the effectiveness with this control framework, a convolutional neural network was created using the YOLOv7 deep learning architecture and Roboflow software. This image detection network was connected to a simulated IoT device via Home Assistant home automation software and communicates using the MQTT protocol. The gesture detection system was tested on different camera setups to evaluate the importance of camera position and data sharing within a smart-home device network.

关键词： Protocols Deep architecture Gesture recognition Smart homes Cooperative systems Cameras Software

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Kinematic and Dynamic Analysis of a 3-■US Spatial Parallel Manipulator

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Chinese Journal of Mechanical engineering 2020年第1期33卷 114-130页

作者： Mervin Joe Thomas M.L.Joy A.P.Sudheer Mechatronics/Robotics Lab Department of Mechanical EngineeringNational Institute of Technology CalicutKozhikodeIndia

Parallel Kinematic Machines(PKMs)are being widely used for precise applications to achieve complex motions and variable poses for the end effector *** are found in medical,assembly and manufacturing industries where accuracy is *** is often desired to have a compact and simple architecture for the robotic *** this paper,the kinematic and dynamic analysis of a novel 3-PRUS(P:prismatic joint,R:revolute joint,U:universal joint,S:spherical joint)parallel manipulator with a mobile platform having 6 Degree of Freedom(Do F)is *** kinematic equations for the proposed spatial parallel mechanism are formulated using the Modified Denavit-Hartenberg(DH)technique considering both active and passive *** kinematic equations are used to derive the Jacobian matrix of the mechanism to identify the singular points within the workspace.A Jacobian based sti ness analysis is done to understand the variations in sti ness for different poses of the mobile platform and further,it is used to decide trajectories for the end effector within the singularity free *** analytical model of the robot dynamics is presented using the Euler-Lagrangian approach with Lagrangian multipliers to include the system *** gravity and inertial forces of all links are considered in the mathematical *** analytical results of the dynamic model are compared with ADAMS simulation results for a pre-defined trajectory of the end effector.

关键词： Parallel manipulator Kinematic modelling Workspace analysis Euler-Lagrangian modelling Singularity analysis Stiffness analysis

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Towards Autonomous Robotic Grasping: 3D Point Cloud Analysis with Stereo Cameras in Unpredictable Environments

Towards Autonomous Robotic Grasping: 3D Point Cloud Analysis...

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IEEE Southeastcon

作者： Shrey Patel Aiden Kovarovics Aaditya More Carrington Chun Montreal Fletcher M. Hasan Tanveer Sumit Chakravarty Razvan Voicu Dept. of Robotics & Mechatronics Engineering Kennesaw State University Marietta USA Dept. of Electrical and Computer Engineering Kennesaw State University Marietta USA

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

Current robotic arm systems typically depend on pretrained models or function within controlled environments using known positions or fiducial markers for object manipulation. Although these methods achieve high accuracy, they face limitations due to lengthy training processes and the need for carefully controlled setups. This research introduces a methodology that leverages stereo cameras to develop a generalized algorithm aimed at overcoming these constraints and enhancing robotic manipulation in uncontrolled environments. The proposed solution utilizes an Intel RealSense stereo camera in conjunction with YOLO segmentation models for initial object identification. It combines segmentation meshes with the camera's depth values to create a detailed three-dimensional point cloud of the target object's surface. This point cloud is analyzed through Random Sample Consensus (RANSAC) and geometry-based feature extraction techniques, which allow the algorithm to approximate the object's shape as a combination of fundamental 3D forms, such as cuboids, cylinders, and spheres. A grasp point is then estimated by identifying suitable surfaces for grasping with a two-pronged gripper, followed by calculating an optimal approach angle and position kinematics for the robotic arm. This innovative approach enables robotic arm systems to autonomously adapt to various objects in uncontrolled environments, significantly expanding their practical applications. For example, the methodology could support modular robotic systems designed for sample collection in extraterrestrial missions, where adaptability and autonomous operations are essential. Ultimately, this research aims to enhance the efficiency and capabilities of robotic systems in dynamic and unpredictable settings.

关键词： Point cloud compression YOLO Training Three-dimensional displays Robot vision systems Grasping Manipulators Cameras Feature extraction Object recognition

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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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A Novel Design of Low Pass Filter in Disturbance Observer for Speed Tracking of Permanent Magnet Synchronous Motors

A Novel Design of Low Pass Filter in Disturbance Observer fo...

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International Conference on Power Electronics (ICPE)

作者： Kanat Suleimenov Ton Duc Do Department of Robotics and Mechatronics School of Engineering and Digital Sciences (SEDS) Nazarbayev University Astana Kazakhstan

This work proposes an approach to find an appropriate bandwidth of a first-order low pass filter (LPF) used in a DOBC. It is established that an observer in the DOBC can guarantee precise estimation if its bandwidth is set as high as possible in order to reject disturbances in a broad frequency range. On the other hand, there is an upper bandwidth limitation due to the system robustness and potential noises; hence, the bandwidth is required to set to be smaller than the limit. In this work, we propose a method of selecting proper bandwidth for the LPF in the DOBC. To show the effectiveness of the proposed method the experimental studies are carried out using the permanent magnet synchronous motor (PMSM)..

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A Single Scale Doesn’t Fit All: Adaptive Motion Scaling for Efficient and Precise Teleoperation

arXiv

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arXiv 2025年

作者： Yoon, Jeonghyeon Park, Sanghyeok Park, Hyojae Kim, Cholin Park, Sihyeoung Hwang, Minho Department of Robotics and Mechatronics Engineering DGIST Daegu42988 Korea Republic of School of Undergraduate Studies DGIST Daegu42988 Korea Republic of

Teleoperation is increasingly employed in environments where direct human access is difficult, such as hazardous exploration or surgical field. However, if the motion scale factor(MSF) intended to compensate for workspace-size differences is set inappropriately, repeated clutching operations and reduced precision can significantly raise cognitive load. This paper presents a shared controller that dynamically applies the MSF based on the user’s intended motion scale. Inspired by human motor skills, the leader arm trajectory is divided into coarse(fast, large-range movements) and fine(precise, small-range movements), with three features extracted to train a fuzzy C-means(FCM) clustering model that probabilistically classifies the user’s motion scale. Scaling the robot’s motion accordingly reduces unnecessary repetition for large-scale movements and enables more precise control for fine operations. Incorporating recent trajectory data into model updates and offering user feedback for adjusting the MSF range and response speed allows mutual adaptation between user and system. In peg transfer experiments, compared to using a fixed single scale, the proposed approach demonstrated improved task efficiency(number of clutching and task completion time decreased 38.46% and 11.96% respectively), while NASA-TLX scores confirmed a meaningful reduction(58.01% decreased) in cognitive load. This outcome suggests that a user-intent-based motion scale adjustment can effectively enhance both efficiency and precision in teleoperation. Copyright © 2025, The Authors. All rights reserved.

关键词： NASA

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Analysis and Design Optimization of Surface Permanent Magnet Motor to Improve Torque Density and Ripple 11

Analysis and Design Optimization of Surface Permanent Magnet...

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11th International Conference on Power Electronics - ECCE Asia, ICPE 2023-ECCE Asia

作者： Shakhin, Yussuf Talapiden, Kulash Minh Thao, Nguyen Gia Bagheri, Mehdi Duc Do, Ton Department of Robotics and Mechatronics AstanaZ05H0P9 Kazakhstan Toyota Technological Institute Graduate School of Engineering Japan Department of Electrical and Computer Engineering AstanaZ05H0P9 Kazakhstan

ISBN: (纸本)9788957083505

Small-scale permanent magnet motor to reach high torque density and low torque ripple is discussed in this research. To increase the torque density, meanwhile making the motor size smaller and lighter, the motor axial length within a constrained diameter is optimized in view of various pole-slot configurations. Different slot-poles are selected and various combinations are studied, and the stator windings are optimized. To compare the torque density and ripple of new designs, precise models are created and simulated through ANSYS Maxwell 2D FEA under constant operational conditions, such as rated speed, torque, and power. Over the new designs, the influence of loss and temperature distribution variations in motor elements are analyzed. The simulation results show that the proposed 20-pole 18-slot motor design will obtain superior torque density and lower torque ripple compared to the baseline design. The final design provides a 30.7 % improvement of the torque density within the same rated torque condition. © 2023 The Korean Institute of Power Electronics.

关键词： Finite element method

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Fully Tunable Fabry-Pérot Cavity on Silicon Photonic MEMS with 10 nW Static Power Consumption

Fully Tunable Fabry-Pérot Cavity on Silicon Photonic MEMS w...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Young J. Park Man J. Her Dong U. Kim Dong J. Choi Min G. Lim Myung S. Hong Sangyoon Han Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology Daegu Republic of Korea

We report on a fully tunable Fabry-Pérot cavity on the silicon photonic MEMS having only 10nW static power. Its resonance wavelength is tunable over the full FSR, and its transmissivity is tunable up to 3.8dB.

ISBN: (纸本)9781957171258

关键词： Microelectromechanical systems Optical components Optical directional couplers Resonance Silicon Waveguide modes

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DEVELOPMENT OF 3D PRINTED SOFT PNEUMATIC HAND MOTION SENSORS

DEVELOPMENT OF 3D PRINTED SOFT PNEUMATIC HAND MOTION SENSORS

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ASME 2022 International Mechanical engineering Congress and Exposition, IMECE 2022

作者： Papendorp, Sky Iyun, Olukayode Schneider, Christian Tekes, Ayse Ashuri, Turaj Amiri Moghadam, Amir Ali Robotics and Mechatronics Department Kennesaw State University MariettaGA United States Mechanical Engineering Department Kennesaw State University MariettaGA United States

ISBN: (纸本)9780791886663

This paper reports on the design, fabrication, and evaluation of a novel 3D printed vacuum based soft sensor and its application as hand motion sensor. Soft sensors are an integral part of soft robotics as an emerging field of science that enables safe and easy human to machine interaction. The conventional sensors used to interface with humans in robotic systems are mechanically incompliant. Because of this mechanical compliance mismatch, these sensors cause unsafe interactions with humans. Recent advancements in 3D printing technology have allowed fabrication of complex geometries with soft polymers, perfect for more delicate and user-friendly sensors. While the existing soft pneumatic sensors work based on the positive pressure due to deformation, the proposed sensor in this work works based on vacuum due to deformation. In comparison with the similar positive pressure sensor, our vacuum-based sensor is much softer and has minimum interference with hand motion. Finite element analysis (FEA) is used to analyze the design. Also, a kinematic model of the hand is developed using Matlab to visualize the hand motion based on the sensor data. This could show the potential application of the soft hand motion sensor in virtual reality and telehealth. Copyright © 2022 by ASME.

关键词： Finite element method

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