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Noise-Optimized Signal Processing for TENG-Based Touch Sensing Using I2C Integrated Circuits

IEEE Sensors Journal 2025年

作者： Moger, Gourav Kakim, Alibek Mubarak, Assem Bushanov, Yersaiyn Kalimuldina, Gulnur Yeshmukhametov, Azamat Nazarbayev University Department of Robotics Engineering Astana Kazakhstan Nazarbayev University School of Engineering and Digital Sciences Department of Mechanical and Aerospace Engineering Astana Kazakhstan LLP MiraiTech Astana Kazakhstan Nazarbayev University Institute of Smart Systems and Artificial Intelligence Advanced Robotics and Mechatronics System laboratory Astana Kazakhstan

Triboelectric nanogenerator (TENG) sensors efficiently convert mechanical stimuli into electrical signals, making them well-suited for touch sensing due to their high sensitivity, durability, and self-powered operation. However, conventional signal acquisition methods introduce noise, affecting measurement accuracy. This paper presents a compact, Inter-Integrated Circuit (I2C)-based signal processing circuit designed to enhance signal fidelity while minimizing noise interference. The system’s performance was evaluated by analyzing sensor response across varying contact areas (50 mm^² to 576 mm^²) and drop heights, demonstrating a consistently high signal-to-noise ratio (SNR) across impact conditions. A high-frequency impact experiment further confirmed the PCB’s ability to distinguish sensor output from noise. Comparison with direct analog acquisition showed a significant enhancement in SNR, validating the PCB’s effectiveness in noise reduction. The system exhibited a rise time of 3.27 milliseconds, ensuring rapid detection of mechanical stimuli. Additionally, the measured latency of 88.9 ms between impact and signal detection falls within acceptable limits for realtime applications. These results establish the proposed PCB-based signal processing method as a practical solution for improving TENG sensor performance in touch-sensing applications requiring high accuracy and noise resilience. The compact, low-power design further enhances its suitability for integration into wearable electronics, interactive surfaces, and space-constrained systems where conventional bulky processing units are impractical. © 2001-2012 IEEE.

关键词： I2C protocol Integrated circuits Noise filtering Noise reduction Sensor optimization Signal processing Signal-to-Noise Ratio Touch sensing Triboelectric nanogenerators

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A Simple Mask Detection Model Based on A Multi-Layer Perception Neural Network

A Simple Mask Detection Model Based on A Multi-Layer Percept...

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2021 International Conference of Technology, Science and Administration, ICTSA 2021

作者： Saleh, Nagmy A.A. Ertunc, H. Metin Saleh, Radhwan A. A. Rassam, Murad A. Kocaeli University Mechatronics Engineering Turkey Taiz University Mechatronics Robotics Eng Taiz Yemen

ISBN: (纸本)9781665428620

A global health crisis is appeared due to the rapid transmission of the COVID-19 pandemic. According to the World Health Organization (WHO), one of the effective ways to decrease this transmission is wearing masks in crowded places. However, monitoring people by police is a weary and difficult process. Thanks to the improvement in technology and artificial intelligence that make task became easier. In this paper, a simple mask recognition model based on texture and color moments features is proposed. This model is deployed in two stages: first, texture and color moments features from the face image (31 features) are extracted using a hybridization between texture features and color moments features techniques. In order to extract the texture features, the image transformed into Gray Level Co-Occurrence Matrix (GLCM) then 22 statistical metrics were calculated. So as to extract the color moments features, the first, second and third moments have been calculated from each layer of the RGB image. Second, based on the extracted features, the images are classified using a Multi-Layer Perceptron model (MLP). The dataset used in this research consists of 1787 real images with masks and 1918 without masks. The obtained results showed that the accuracy achieved by the proposed model is 90.58% and the time complexity is 6.7379 seconds for training and 0.0023 seconds for prediction. © 2021 IEEE.

关键词： COVID-19

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Human-Centric Concept for a Reconfigurable Robotic System Enabling Low-Volume Assembly of Photonic and Quantum Modules

Human-Centric Concept for a Reconfigurable Robotic System En...

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IEEE/SICE International Symposium on System Integration

作者： Andreas Wicht Tobias Franke Alina Hahn Nils Håkansson Christian Kürbis Robert Smol Thomas Hulin Thomas Eiband Peter Lehner Maximilian Mühlbauer Korbinian Nottensteiner Richard Pietschmann Bernhard Thaler Diana Thaler Jürgen Bosse Ferdinand-Braun-Institut (FBH) Berlin Germany Institute of Robotics and Mechatronics German Aerospace Center (DLR) Wessling Germany Centre for Tactile Internet with Human-in-the-Loop (CeTI) Germany Sensor Based Robotic Systems and Intelligent Assistance Systems Technical University of Munich Garching Germany Robo-Technology GmbH Puchheim Germany Thaler Engineering GmbH Eichenau Germany Coherent Munich GmbH & Co. KG Gilching Germany

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

This paper presents a novel concept for a reconfigurable robotic system specifically designed to meet the demands of hybrid integration for miniaturized photonic and quantum System-in-Packages (SiPs). The proposed solution introduces a distinctive approach to ultra-high-resolution, multi-telerobotic assembly and inspection. By integrating key Industry 5.0 principles, it establishes a human-centric control framework that minimizes both physical and cognitive stress while ensuring the human operator remains in full control at all *** robotic system features eight robots working simultaneously within a compact footprint of just 5×10 cm 2 . A comprehensive digital twin framework constitutes a central element of the robotic system. It encompasses the robotic workcell, the SiP under assembly, and the components to be integrated, ensuring precise adherence to design specifications. Key functionalities include automated path planning in a multi-robotic environment, collision avoidance in a densely packed workcell, and virtual fixtures to guide teleoperation, enhancing the operator’s control and interaction through advanced and intuitive human-machine interfaces (HMI). The proposed system meets the critical demands of ultra-high-resolution assembly for complex, high-value SiPs, providing high flexibility and ease of operation for small-batch manufacturing.

关键词： System-in-package Service robots Robot kinematics Fixtures System integration Digital twins Collision avoidance Fifth Industrial Revolution Assembly Photonics

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Experimental and modeling study of surface topography generation considering tool-workpiece vibration in high-precision turning

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Chinese Journal of Aeronautics 2023年第7期36卷 194-212页

作者： Xingying ZHOU Henan LIU Tianyu YU Ruiyang GUO Guangzhou WANG Yazhou SUN Mingjun CHEN State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China

High-precision turning(HPT)is a main processing method for manufacturing rotary high-precision components,especially for metallic ***,the generated vibration between tool tip and workpiece during turning may seriously deteriorate the surface ***,exploring the effect of vibration on turning surface morphology and quality of copper parts using 3D surface topography regeneration model is crucial for predicting HPT *** developed model can update the machined surface topology in real *** this study,the effects of tool arc radius,feed rate,radial vibration,axial vibration and tangential vibration on the surface topography and surface roughness were *** results show that the effect of radial vibration on surface topography is greater than that of axial vibration and tangential *** radial vibration frequency is also *** vibration frequency changes,the surface topography profile presents three different types:the standard sinusoidal curve,the sinusoidal curve whose lowfrequency signal envelopes high-frequency signal,and the oscillation curve whose low-frequency signal superimposes high-frequency *** addition,HPT experiment was carried out to validate the developed *** surface roughness obtained in the experiment was Ra=53 nm,while the roughness obtained by the simulation was Ra=46 nm,achieving a prediction accuracy of 86.7%.Received 4 September 2022;revised 3 October 2022;accepted 17 October 2022.

关键词： High-precision turning Machining vibration Modeling Surface roughness Surface topography

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Spectral and Morphological Classification of Celestial Objects using Physics Informed Machine Learning 3

Spectral and Morphological Classification of Celestial Objec...

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3rd IEEE International Conference on robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Siddiquee, Md Fairuz Hasan, Md Mehedi University of Dhaka Department of Robotics and Mechatronics Engineering Dhaka Bangladesh

ISBN: (纸本)9798331534400

The classification of celestial objects has traditionally relied on spectral analysis, which involves identifying unique patterns in the light emitted or absorbed by the objects. In this study, we present a novel approach to categorizing celestial objects based on their spectral properties and morphological structures, leveraging physics-informed machine learning (PIML) techniques to enhance the classification accuracy and efficiency. In the spectral analysis, using Sloan Digital Sky Survey (SDSS) dataset, we classified stars, galaxies, and quasars, focusing on redshift and near-infrared values with i and z filters. Our analysis employed three machine learning models (K-Neighbors, SVM, Random Forest), and the performances were verified to be resilient applying hyperparameter tuning and cross-validation. The best-performing model, Random Forest Classifier, achieved 98% accuracy. In the morphological analysis, the YOLO v5 model was utilized on a customized dataset of astronomical images to further classify the Galaxy Class into five distinct categories and the YOLOv5 model detected those with an average precision of 92.6% and recall of 68.9%. In addition, the interpretability of the model is enhanced by the incorporation of physical knowledge, allowing astronomers to gain deeper insights into the underlying processes. Integrating physical knowledge into these ML models enhances interpretability, facilitating automated real-time analysis of big astronomical data and advancing our understanding of the cosmos. © 2024 IEEE.

关键词： Random forests

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Solar-based hybrid electric vehicles for low CO2 emission

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International Journal of Sustainable engineering 2025年第1期18卷

作者： Islam, Md. Ariful Kar, Pankaj Chandra Deowan, Shamim Ahmed Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh Department of Information and Communication Technology Comilla University Cumilla Bangladesh Department of Computer Science and Engineering Stamford University Bangladesh Dhaka Bangladesh

This study investigates the impact of greenhouse gas and (Formula presented.) emissions from conventional vehicles (CVS) in Bangladesh and proposes a renewable energy and battery storage-based hybrid electric vehicle (HEV) to mitigate these emissions. The proposed HEV focuses on fuel economy, driving range, performance and cost-efficiency. It integrates hybrid batteries with ultra-capacitors for improved acceleration and energy storage, along with fuel cells, flywheels and regenerative braking. The propulsion system, combining electric, mechanical, chemical and electronics engineering, is a key challenge affecting vehicle design and performance. Additionally, the study develops an automatic solar power system with maximum power point tracking (MPPT) to optimise solar energy generation by considering sunrise and sunset times, panel size, charging duration, load profiling and power loss. The solar-based HEV, with an average speed of 60 km/h, can operate for 3.4 h or 204 km solely on solar power. Findings indicate a significant reduction in (Formula presented.) emissions, with solar HEVs emitting approximately 17,775,012.2 g and 13,825,009.5 g less (Formula presented.) than petrol and diesel vehicles, respectively. The study advocates for government adoption to promote a cleaner, more sustainable transportation sector in Bangladesh. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： Hybrid vehicles

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A Simple Manufactured Hardness Sensor Based on Multi-Layer Liquid Metal Sensing for Surgical robotics

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Advanced Electronic Materials 2025年

作者： Yue, Tao Zhang, Yuyin Gan, Yuanjie Hu, Chengzhi Wang, Yue School of Mechatronics Engineering and Automation Shanghai University Shangda Road 99 Shanghai 200436 China Shanghai Institute of Intelligent Science and Technology Tongji University Siping Road 1239 Shanghai 200092 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen 518055 China School of Future Technology Shanghai University Shangda Road 99 Shanghai 200436 China

Tactile information, serving as the most intricate form of data humans gather from the external environment, has long been a significant area of focus for wearable flexible sensors. The advancement of wearable technology and robotics in healthcare has spurred research into integrating thin, compact flexible sensors into robotic systems for mimicking human tactile tissue manipulation during surgery and data collection. Here, a continuous injection method is used to fabricate a multi-layer liquid metal sensor. By laminating multiple PDMS microfluidic layers, the two parameters of pressure and deformation are simultaneously measured in a decoupled manner. The compact and thin design of the sensor facilitates its integration into fingers or robotic digits, enabling assistance by deforming upon contact with materials and identifying their hardness through applied pressure. Separate performance tests of the two sensors show that the strain and pressure functions are decoupled from each other, and their ratios can identify and classify the hardness of different contact materials (glass, PDMS, and silicone). The hardness sensor can assist robots in operating human tissues during medical surgeries. The demonstrated fabrication and integration approaches provide a path toward tactile sensor applications in medical treatment, rehabilitation, services, and other processes. © 2025 The Author(s). Advanced Electronic Materials published by Wiley-VCH GmbH.

关键词： flexible sensor hardness sensor liquid metal

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FFT-UAVNet: FFT Based Human Action Recognition for Drone Surveillance System 5

FFT-UAVNet: FFT Based Human Action Recognition for Drone Sur...

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5th International Conference on Sustainable Technologies for Industry 5.0, STI 2023

作者： Chowdhury, Abdul Monaf Imran, Ahsan Hasan, Md Mehedi University of Dhaka Dept. of Robotics and Mechatronics Engineering Bangladesh

ISBN: (纸本)9798350394290

Unmanned aerial vehicles (UAVs) have emerged as a transformative technology for human action recognition, providing a birds-eye view and unlocking new possibilities for precise and comprehensive support in surveillance systems. While substantial advances in ground-based human action recognition have been achieved, the unique characteristics of UAV footage present new challenges that require tailored solutions. Specifically, the reduced scale of humans in aerial perspectives necessitates the development of specialised models to accurately recognize and interpret human actions. Our research focuses on modifying the well-established C3D model and incorporating Fast Fourier Transform (FFT)-based object disentanglement (FO) and space-time attention (FA) mechanisms. By leveraging the power of FFT, our model effectively disentangles the human actors from the background and captures the spatio-temporal dynamics of human actions in UAV footage, enhancing the discriminative capabilities and enabling accurate action recognition. Through extensive experimentation on a subset of the UAV-Human dataset, our proposed FFT-UAVNet (m-C3D+FO&FA+FC) model demonstrates remarkable improvements in performance. We achieve a Top-1 accuracy of 64.86% and a Top-3 accuracy of 83.37%, surpassing the results obtained by the standard C3D and X3D methods, which achieve only a Top-1 accuracy of 28.05% and 31.33%, respectively. These findings underscore the efficacy of our approach and emphasize the significance of the proposed model for UAV datasets in maximizing the potential of UAV-based human action recognition. © 2023 IEEE.

关键词： Computer vision

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Data-driven System Decoupling Algorithm with Transfer Function Decoupling Matrix 49

Data-driven System Decoupling Algorithm with Transfer Functi...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Yoon, Jegwon Kong, Taejune Jung, Hanul Oh, Sehoon Dgist Department of Robotics and Mechatronics Engineering Daegu Korea Republic of

ISBN: (纸本)9798350331820

A Multi-Input-Multi-Output (MIMO) system has complex interactions between inputs and outputs, resulting in a coupling effect that can lead to undesired motions. To effectively control MIMO systems, decoupling is necessary. This paper introduces a decoupling method that uses a transformation matrix modeled as a transfer function using Frequency Response Function (FRF). Unlike the conventional decoupling method uses constant transformation matrix obtained through Canonical Polyadic Decomposition (CPD) and shows performance degradation in certain frequency bands, the proposed method creates transformation matrix as a transfer function and demonstrates better decoupling performance across the entire frequency band. The performance of the proposed method is validated through simulations on a hybrid dual-drive gantry stage. © 2023 IEEE.

关键词： Transfer functions

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Development of an Accelerometer-based Data Acquisition System for Hand Gesture Recognition 3

Development of an Accelerometer-based Data Acquisition Syste...

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3rd IEEE International Conference on robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Tajwar, Atique Haque, Md. Ettashamul Hasan, Md Mehedi University of Dhaka Department of Robotics and Mechatronics Engineering Dhaka Bangladesh

ISBN: (纸本)9798331534400

This study presents a novel approach to Human-Robot Interaction (HRI) by employing gesture recognition to control robotic systems, such as bionic arms or manipulators, through accelerometer-based data collection. Using a low-cost glove equipped with an ESP32 microcontroller and accelerometer, data was gathered from 22 participants performing five distinct gestures: a clockwise circle, square, triangle, double tap, and the letter S. After filtering, these gestures were translated into features that trained a small neural network model designed for low-storage microcontrollers like the ESP32. With a performance accuracy of 90.4%, the neural network outperformed existing ensemble learning models, demonstrating its suitability for real-time gesture recognition tasks in embedded robotic systems. This highly efficient model enables seamless and intuitive control of robotic devices by facilitating responsive and natural HRI through gesture recognition. Designed specifically for compact and resource-limited environments, the model addresses the challenges associated with limited computational resources and restricted hardware capabilities. It provides a robust and scalable solution that can be easily integrated into various robotics applications, where gesture-based control is advantageous. © 2024 IEEE.

关键词： Accelerometers

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