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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Ramkumar, S. Venusamy, Kanagaraj Eswaran, A. Jeevitha, N. Ramyapriya, G. Kannadhasan, S. Rajalakshmi Engineering College Department of Robotics and Automation Thandalam Chennai India Rajalakshmi Engineering College Department of Mechatronics Engineering thandalam Chennai India Roever Engineering College Department of Electrical and Electronics Engineering Perambalur India Study World College of Engineering Department of Electronics and Communication Engineering Coimbatore Chennai India

ISBN: (纸本)9798350335095

The automation scenario in the current industrial as well as domestic applications has seen an exponential growth over the decade. Robot plays an important role in industrial automation but in some cases, it needs some extent of human intervention in quality inspection. This paper focuses on solving problems related to defect identification and segregation of fruits using 3-DOF articulated robot configuration with the integration of machine vision system and deep learning algorithms. To perceive the features of object, A USB camera is utilized. The machine vision algorithm will next use a variety of methods for processing digital images to extract the relevant data and decide whether to continue processing the product, redirect it to a different stage of production, or just throw it away. In recent days, the advancement in deep learning leads to the phenomenal growth in computer vision. There are many state-of-the-art object detection algorithms available in deep learning technology and we are using Inception-V3 algorithm that can be used for the machine vision operation in our solution. Based on the results from the algorithm, segregation operation is carried out successfully. © 2023 IEEE.

关键词： Fruits

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Minimalistic Soft Exosuit for Assisting the Shoulder via Biomechanics-Aware Optimization 21

Minimalistic Soft Exosuit for Assisting the Shoulder via Bio...

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2022 IEEE-RAS 21st International Conference on Humanoid Robots, Humanoids 2022

作者： Joshi, Sagar Beck, Irene Seth, Ajay Santina, Cosimo Della Mechanical Maritime and Materials Engineering Faculty TU Delft Delft Netherlands Robotics and Mechatronics Department Munich Germany

ISBN: (纸本)9798350309799

Soft exosuits can help to prevent work-related musculoskeletal disorders by offloading human muscles through the application of external forces across the human joints. Many exosuits achieve this through tension producing elements called as exotendons. However, the design of these devices is based on intuition and experience. This leads to potentially sub-optimal or even harmful designs that could cause discomfort or injury to the wearer. This paper deals with automatically finding appropriate attachments and routing locations for exotendons. We propose to do that by accurate musculoskeletal modeling and design parameter optimization of soft exosuits. We focus here on a soft exosuit with a single passive exotendon to assist the shoulder. Using three arm raising-lowering and internal-external rotation motions as examples, we optimize the attachment point and rest-length of the exotendon to reduce overall muscle effort. We then fabricate the exosuit and validate the model predictions by testing with six participants. Supporting the predictions from simulations, measured muscle activity shows reductions in the deltoid and trapezius muscles. This work represents the first instance of explicitly optimizing functional and geometric parameters of exotendons in wearable assistive devices for minimizing human effort. © 2022 IEEE.

关键词： Muscle

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Wheelchair Control by Users' Eye Movements Using Signals Acquired in OpenBCI

Wheelchair Control by Users' Eye Movements Using Signals Acq...

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2023 IEEE International Symposium on Robotic and Sensors Environments, ROSE 2023

作者： Rexha, Genta Pajaziti, Arbnor Bajrami, Xhevahir Kola, Jozef Capi, Genci Pongthanisorn, Goragod Polytechnic University of Tirana Department of Electronics and Telecommunications Tirana Albania Faculty of Mechanical Engineering Department of Mechatronics Prishtina Serbia Albanian University Department of Engineering Tirana Albania Hosei University Assistive Robotics Laboratory Tokyo Japan

ISBN: (纸本)9798350308044

In this study is presented a wheelchair with a control mechanism driven by the user's eye movements. The wheelchair's functionality is enabled through two stepper motors, a driver DMA860H, and an Arduino Uno microcontroller. The objective of the research is that the EEG signals are read and by means of these signals we perform certain tasks or control various processes. OpenBCI (Brain Computer Interface) board has been used to measure and record electrical activity produced by the brain and is compatible with standard EEG (Electroencephalogram) *** user's eye movements will be used to operate the stepper motors. The OpenBCI Cyton plus Daisy biosensing board samples the signals, which are then processed in Matlab before relaying the motions to Arduino Uno. The wheelchair can move left, right, backward, and forward, based on eye movements. © 2023 IEEE.

关键词： Wheelchairs

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A Robust Control Technique for Pitch Control of an Aeropendulum 6

A Robust Control Technique for Pitch Control of an Aeropendu...

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6th International Conference on robotics, Control and Automation engineering, RCAE 2023

作者： Tanveer, M. Hassan Koduru, Charles Roy, Rupam Gupta Lakhekar, Girish V. Chun, Cary Kennesaw State University Department of Robotics and Mechatronics Engineering MariettaGA30067 United States National Institute of Technology Department of Electronics and Instrumentation Engineering Agartala Barjala Jirania Tripura Agartala India College of Engineering Department of Instrumentation Engineering Maharashtra Pune India

ISBN: (纸本)9798350315301

Pitch control of an aviation system presents a plethora of control complications, such as nonlinear effects, parameter uncertainties, disturbances, etc. In the face of parametric uncertainties and disturbances, as well as communication limits in an auditory medium, it is difficult to create efficient control algorithms that can accomplish precise path-following tasks and effective resilient control actions. This paper presents the Second Order Sliding Mode Control method for regulating the pitch angle in an aero-pendulum mechatronic system. The fundamental purpose of this study is to develop a reliable controller capable of minimising the system error between the regulated signal and the planned signal that corresponds to the pitch angle of the vehicle. By employing the proposed approach, both the prevalence of chattering and the control efficiency can be greatly improved. A comparison is given between the proposed model and the classical technique now in use, such as the classical Sliding Mode Controller. © 2023 IEEE.

关键词： Sliding mode control

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AgileVision Academy: Indoor Drone Navigation and Obstacle Avoidance 14

AgileVision Academy: Indoor Drone Navigation and Obstacle Av...

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14th International Conference on Information Technology in Medicine and Education, ITME 2024

作者： Jiang, Haolong Gu, Lingdan Wang, Jiayu Lan, Xiao Liu, Qinyao Wang, Fanxin Xi'an Jiaotong Liverpool University University of Liverpool School of Advanced Technology Department of Electrical and Electronic Engineering Suzhou China Xi'an Jiaotong Liverpool University School of Robotics Department of Intelligence Robotics Engineering With Contemporary Entrepreneurialism Suzhou China Xi'an Jiaotong Liverpool University School of Advanced Technology Department of Information and Computer Science Suzhou China Xi'an Jiaotong Liverpool University School of Advanced Technology Department of Electrical and Electronic Engineering Suzhou China Xi'an Jiaotong Liverpool University School of Advanced Technology Department of Mechatronics and Robotics Suzhou China

ISBN: (纸本)9798350356670

Navigating cluttered indoor environments presents a significant challenge for aerial robots, requiring agility, speed, and a high level of reliability to avoid collisions. This project aims to address this challenge by developing advanced algorithms for lightweight drones, enabling them to reach target location and carrying out delivery efficiently and safely. Utilizing camera data to map and avoid obstacles, we create a system that not only maps and perceives the environment but also navigates its path to the destination. Included in the educational content, this project demonstrates the effectiveness of the technology through practical applications and real-world testing, helping the next generation of engineers accumulate technical experience and broaden their understanding of drone navigation algorithms and applications in system integration. It has a milestone impact on education and development of the drone field. © 2024 IEEE.

关键词： Drones

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Applying CNN Models with Stereo Camera for Object Detection and Distance Estimation in Automatic Micro Electric Vehicle (MEVi) 1

Applying CNN Models with Stereo Camera for Object Detection ...

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1st International Conference on Smart mechatronics, ICSMech 2024

作者： Harimanto, Farrell Putra Hasanah, Nurul Pradana, Muhammad Khristamto Aditya Puji, Muhammad Nurul Binus Aso School of Engineering Bina Nusantara University Automotive & Robotics Program Computer Engineering Department Jakarta11480 Indonesia National Research and Innovation Agency Kst Samaun Samadikun Research Center for Smart Mechatronics Bandung40135 Indonesia

ISBN: (纸本)9798350368918

Technological advancements in the automotive industry are currently focused on autonomous driving systems or driver assistance systems. Depth estimation is also an important feature of the autonomous driving system as it can accurately estimate the distance to the detected objects. In current developments technologies such as stereo cameras are more popular for a more accurate depth estimation. The process for object detection consists of a combination of classification, localization, and segmentation. Deep convolutional neural networks are the basis of object detection. The methods for object detection are divided into two categories namely the Region Proposal-based method such as RCNN, and the Classification-based method which provides for methods such as YOLO and MobileNet. As a part of the research conducted by the National Research and Innovation Agency (BRIN) on Automatic Micro Electric Vehicles or MEVi, this paper analyzed and compared the performance of several CNN models for object detection as well as the performance of depth sensing using ZED stereo camera which was used for the autonomous system in MEVi. Among several models that had been compared, YOLO v8 model demonstrates high accuracy and moderate speed as indicated by its high mAP (0.50) and FPS (38.46). Based on depth sensing results, the accuracy of distance measurement also depended on brightness and environment with the average of accuracy achieved indoors was 98.2% and outdoors was 96.3%. © 2024 IEEE.

关键词： Automotive industry

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The Manipulation of Four-Wave Mixing in a Fully Tunable MEMS Photonic Molecule

The Manipulation of Four-Wave Mixing in a Fully Tunable MEMS...

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Frontiers in Optics + Laser Science 2023, FiO, LS 203: Part of Frontiers in Optics + Laser Science 2023

作者： Lim, Min G. Choi, Dong J. Kim, Dong U. Park, Young J. Yu, Kyoungsik Han, Sangyoon Jeong, Kwang-Yong Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology Daegu42988 Korea Republic of Daejeon34141 Korea Republic of Jeju63243 Korea Republic of

We demonstrated the manipulation of four-wave mixing (FWM) in a fully tunable photonic molecule implemented on low-power silicon photonic MEMS. A seeded FWM with a conversion efficiency of −56dB at 7.3dBm pump power w... 详细信息

ISBN: (纸本)9781957171296

关键词： Four wave mixing Frequency combs Microelectromechanical systems Silicon Waveguide modes Wavelength conversion

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Prediction of directivity characteristics of piezoelectric macro-fiber composite interdigital transducers: a semi-analytical approach

e-Journal of Nondestructive Testing

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e-Journal of Nondestructive Testing 2024年第7期29卷

作者： Raorane, Siddhesh Ambrozinski, Lukasz Stepinski, Tadeusz Packo, Pawel Department of Robotics and Mechatronics Faculty of Mechanical Engineering and Robotics AGH University of Science and Technology Krakow30-059 Poland

The employment of guided waves for structural health monitoring applications has attracted substantial attention in recent years. Piezoelectric transducers are frequently employed in these systems for elastic wave generation and acquisition. Their dynamic properties, i.e., direction-dependent frequency characteristics such as directivity patterns, are an important feature for designing a reliable monitoring strategy. Although analysis of the transducer directivity pattern can be performed using finite element models, these usually tend to be computationally very expensive, especially for parametric and optimization studies. In this paper, a semi-analytical framework is proposed that can predict the far-field directivity patterns of complex transducers of arbitrary shape and structure mounted on a substrate. The framework described in this paper integrates analytical far-field predictions with a local finite element model evaluating the traction field produced by the transducer. Consequently, the FE model accurately captures near-field responses, whereas the analytical component predicts the far-field responses. The implementation of this semi-analytical framework requires the development of analytical and numerical approaches. The former includes computation of dispersion curves of the inspected plate, the stress and displacement profiles of wave modes, and ultimately, the excitability relations, while the latter includes estimation of the traction field between the transducer and the plate using the FE model. Owing to the popularity of piezoelectric macro-fiber composite (MFC) transducers, in this paper, we apply the proposed method to predict the directivity patterns of MFC M2807-P2 transducer. To validate the reliability of the proposed method, the predicted patterns are compared with experimental results obtained using Laser Doppler Vibrometer. © 2024, NDT. net GmbH and Co. KG. All rights reserved.

关键词： Forecasting

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Advances of triboelectric and piezoelectric nanogenerators toward continuous monitoring and multimodal applications in the new era

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International Journal of Extreme Manufacturing 2025年第1期7卷 174-205页

作者： Jianlong Hong Xiao Wei Huiyun Zhang Yukun Xiao Chongguang Meng Yuqi Chen Jiahui Li Ling Li Sanghoon Lee Qiongfeng Shi Jun Wu Interdisciplinary Research Center School of Electronic Science and EngineeringSoutheast UniversityNanjing 211189People’s Republic of China Department of Robotics&Mechatronics Engineering Daegu Gyeongbuk Institute of Science&TechnologyDaegu 42899Republic of Korea

Benefiting from the widespread potential applications in the era of the Internet of Thing and metaverse,triboelectric and piezoelectric nanogenerators(TENG&PENG)have attracted considerably increasing *** outstanding characteristics,such as self-powered ability,high output performance,integration compatibility,cost-effectiveness,simple configurations,and versatile operation modes,could effectively expand the lifetime of vastly distributed wearable,implantable,and environmental devices,eventually achieving self-sustainable,maintenance-free,and reliable ***,current triboelectric/piezoelectric based active(***-powered)sensors still encounter serious bottlenecks in continuous monitoring and multimodal applications due to their intrinsic limitations of monomodal kinetic response and discontinuous transient *** work systematically summarizes and evaluates the recent research endeavors to address the above challenges,with detailed discussions on the challenge origins,designing strategies,device performance,and corresponding diverse ***,conclusions and outlook regarding the research gap in self-powered continuous multimodal monitoring systems are provided,proposing the necessity of future research development in this field.

关键词： triboelectric piezoelectric continuous monitoring multimodal sensing internet of thing

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A Driving Direction Estimation Algorithm for Obstacle Avoidance of a Wheel-less Snake Robot

A Driving Direction Estimation Algorithm for Obstacle Avoida...

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International Conference on mechatronics Technology (ICMT)

作者： Seunghyun Lim Jinhyeok Song Dongwon Yun Department of Robotics and Mechatronics Engineering DGIST Daegu Republic of Korea

This paper describes a driving direction estimation algorithm of a wheel-less snake robot and verifies that the algorithm allows the robot to locomote as desired in ROS-based simulation. Snake robots have serious operational difficulties since their driving directions are not intuitive. Therefore, a driving direction should be estimated for autonomous locomotion, such as path tracking and obstacle avoidance. A driving direction estimation algorithm based on the kinematics of the snake robot is used with path planning and tracking algorithms. The suggested driving direction estimation algorithm allowed straightness improvement and path tracking in the simulation environment.

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