检索结果-内蒙古大学图书馆

International Conference on Information Technologies in engineering Education (Inforino)

作者： Delshan Deeb Igor Merkuryev Vasily Pakhomov Department of Robotics Mechatronics Dynamics and Strength of Machines Moscow Power Engineering Institute Moscow Russian Federation

ISBN: (数字)9798350371369

ISBN: (纸本)9798350371376

The development and integration of robotics education encompass a multifaceted approach that combines theoretical knowledge with practical application. The educational process is geared toward producing highly qualified specialists and supporting the development of innovative mechatronic modules and robotic systems. The article introduces new practice-oriented educational technologies designed to train specialists in mechatronics and robotics, with a focus on creating robotic systems for competitions and human interaction. The study has started at the Moscow Power engineering Institute in 1931 with the activities of student design and engineering bureaus. Improving the professional level of graduates led to winning several international competitions, which had the greatest role in the formation of the Technology Support Center for Education in 2012. Scientific research continues to this day in the field of designing robots and finding optimal methods for their implementation. Ultimately, this study suggests prioritizing sponsorship and enhancing competition, offering additional technological and material resources to students and researchers, and formulating long-term strategies to anticipate and address technological obstacles. The article concluded by examining the step-by-step advancement of technical education in preparing skilled professionals in robotics and mechatronics, and highlighting the potential future prospects and obstacles for educating students in this field.

关键词： Training mechatronics Educational robots Service robots Prototypes Educational technology Robots

来源：评论

学校读者我要写书评

暂无评论

Development of a low-cost microfluidic chip for hyaluronidase-free oocyte denudation in mammals

Biotechnology Notes

引用

Biotechnology Notes 2025年 6卷 133-142页

作者： Dessouky, Ashraf Hisham El-Hussieny, Haitham El-Sherry, Taymour Mohammed Parque, Victor Fath El-Bab, Ahmed M.R. Department of Mechatronics and Robotics Engineering Egypt-Japan University of Science and Technology (E-JUST) Alexandria Alexandria 21934 Egypt Mechanical Engineering Department Helwan University Cairo Cairo 11792 Egypt Department of Theriogenology Veterinary Hospital Faculty of Veterinary Medicine Assiut University Assiut Assiut Egypt of Advanced Science and Engineering Hiroshima University Hiroshima HigashiHiroshima 739-8527 Japan

Infertility in mammals is one of the most intricate medical issues requiring non-traditional interventions. In Vitro Fertilization (IVF) is one of the modern medical technologies currently used to treat infertility. However, current IVF procedures are inaccessible and unaffordable to the majority due to the high cost, the complexity of the procedure, and the reliance on highly qualified operators. For successful IVF, oocyte denudation, the process of removing cumulus cells from oocytes, is often performed. Here, microfluidics offers the potential to enhance denudation procedures and to minimize operator variability. In this paper, we propose the configuration of a microfluidic chip for oocyte denudation whose structure hybridizes inner jagged surfaces and expansion units. The jagged surface units have the role of removing the cumulus cells surrounding the oocyte by using the wall shear stress principle, and the (rounded) expansion units have the role of rotating the cumulus cells for further deployment in subsequent jagged surfaces. The proposed device can be manufactured at a low cost (<1 USD)) by the engraving of CO₂ laser machine on PMMA material, and is able to circumvent the use of enzymatic components such as hyaluronidase. Experiments using computational simulations and manufactured microfluidic chips evaluated distinct geometry configurations of the jagged surfaces and identified the suitable flow rates for maximal shear stress and denudation performance. Manufactured samples of the proposed microfluidic devices have shown the denudation performance of 96.7 % and yield rate of 90 % at a constant flow rate of 1 ml/min. © 2025 The Authors

关键词： CO2 laser In vitro fertilization Microfluidics Oocyte denudation

来源：评论

学校读者我要写书评

暂无评论

Wheeled Mobile Robots on Rough Terrains as Stochastic Nonholonomic Systems

Wheeled Mobile Robots on Rough Terrains as Stochastic Nonhol...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Vaughn Gzenda Robin Chhabra Mechanical and Aerospace Engineering Department Autonomous Space Robotics and Mechatronics Laboratory Carleton University Ottawa ON Canada

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In this paper, we investigate the motion of wheeled mobile robots on rough terrains modeled as noisy nonholonomic constraints. Such constraints are the natural extension of ideal nonholonomic constraints when the Stratonovich process is directly introduced in the constraint equations. The resulting stochastic model can capture motion on rough surfaces, random deformation in the wheel-ground contact, or stochastic loss/gain of traction. We study a differential robot with ideal noisy and affine noisy constraints, where each case models a certain aspect of motion on rough terrains. We then investigate their corresponding stochastic dynamics and the propagation of mean and covariance through Monte-Carlo simulations. The proposed model for roving rough terrains has the potential to serve as the stochastic model employed in model-based motion planning, pose estimation, and control of rover systems. The main challenge will be dealing with the nonlinear appearance of the noise and its feedback in the equations of motion.

关键词： Deformation Noise Dynamics Stochastic processes Mathematical models Surface roughness Rough surfaces Noise measurement Mobile robots Surface treatment

来源：评论

学校读者我要写书评

暂无评论

Intelligent Deep Learning Enabled Human Activity Recognition for Improved Medical Services

引用

Computer Systems Science & engineering 2023年第2期44卷 961-977页

作者： E.Dhiravidachelvi M.Suresh Kumar L.D.Vijay Anand D.Pritima Seifedine Kadry Byeong-Gwon Kang Yunyoung Nam Department of Electronics and Communication Engineering Mohamed Sathak A.J.College of EngineeringChennai603103India Department of Information Technology Sri Sairam Engineering CollegeChennai602109India Department of Robotics Engineering Karunya Institute of Technology and SciencesCoimbatore641114India Department of Mechatronics Engineering Sri Krishna College of Engineering and TechnologyCoimbatore641008India Deparmtent of Applied Data Science Noroff University CollegeKristiansandNorway Department of Information and Communication Engineering Soonchunhyang UniversityAsanKorea Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea

Human Activity Recognition(HAR)has been made simple in recent years,thanks to recent advancements made in Artiﬁcial Intelligence(AI)*** techniques are applied in several areas like security,surveillance,healthcare,human-robot interaction,and *** wearable sensor-based HAR system includes in-built sensors,human activities can be categorized based on sensor ***,it can also be employed in other applications such as gait diagnosis,observation of children/adult’s cognitive nature,stroke-patient hospital direction,Epilepsy and Parkinson’s disease examination,***-developed Artiﬁcial Intelligence(AI)techniques,especially Deep Learning(DL)models can be deployed to accomplish effective outcomes on HAR *** this motivation,the current research paper focuses on designing Intelligent Hyperparameter Tuned Deep Learning-based HAR(IHPTDL-HAR)technique in healthcare *** proposed IHPTDL-HAR technique aims at recogniz-ing the human actions in healthcare environment and helps the patients in mana-ging their healthcare *** addition,the presented model makes use of Hierarchical Clustering(HC)-based outlier detection technique to remove the ***-HAR technique incorporates DL-based Deep Belief Network(DBN)model to recognize the activities of ***,Harris Hawks Opti-mization(HHO)algorithm is used for hyperparameter tuning of DBN ***,a comprehensive experimental analysis was conducted upon benchmark dataset and the results were examined under different *** experimental results demonstrate that the proposed IHPTDL-HAR technique is a superior per-former compared to other recent techniques under different measures.

关键词： Artiﬁcial intelligence human activity recognition deep learning deep belief network hyperparameter tuning healthcare

来源：评论

学校读者我要写书评

暂无评论

Feedforward Backpropagation Artificial Neural Network for Modeling the Forward Kinematics of a Robotic Manipulator

Feedforward Backpropagation Artificial Neural Network for Mo...

引用

2023 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2023

作者： Bouzid, Rania Narayan, Jyotindra Gritli, Hassene Higher Institute of Information and Communication Technologies Tunis1164 Tunisia Indian Institute of Technology Guwahati Mechatronics and Robotics Laboratory Department of Mechanical Engineering Guwahati781039 India National Engineering School of Tunis Tunis1002 Tunisia

ISBN: (纸本)9798350307771

Determining an end-effector position and orientation, known as forward kinematics (FK), is a crucial aspect of robotic manipulation. This research addresses the FK problem using a Feedforward Backpropagation Artificial Neural Network (FFBP-ANN) and examines the network's performance with different hyperparameters. The input of the FFBP-ANN is primarily formed using three different datasets: fixed-step values, random values, and sinusoidal-signal based values, for a 2-DOF robotic manipulator. The output of the FFBP-ANN is evaluated using FK formulation of the robot manipulator. Thereafter, the FFBP-ANN is trained utilizing the input-output training dataset using The Neural Network Toolbox for MATLAB. The network's potential is investigated by varying the critical hyperparameters, including the number of hidden neurons and the number of hidden layers. Moreover, the effectiveness of the proposed FFBP-ANN is investigated with three different training optimizers including the utilization of Levenberg-Marquardt, Bayesian Regularization, and Scaled Conjugate Gradient optimization algorithms. During training, by adjusting the network's weights and biases iteratively, the backpropagation technique allows the network to effectively learn and comprehend the relationship between joint positions and Cartesian coordinates. The comparative results offer valuable insights into the strengths and limitations of different ANN architectures when applied to solving FK problems. In this way, this study focuses on exploring the application of the FFBP-ANN in resolving FK challenges and assisting in the identification of appropriate network types for path-planning tasks. © 2023 IEEE.

关键词： End effectors

来源：评论

学校读者我要写书评

暂无评论

Development of a Throwbot with Shock Absorption Structure

Development of a Throwbot with Shock Absorption Structure

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Jaeyeong Keum Jaemin Kim Changgi Lee Seunghyun Lim Insung Ju Dongwon Yun Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu South Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In this study, a throwing robot equipped with an shock absorbing structure, utilizing paired-Cross Flexural Hinge (p-CFH) and an airbag, was fabricated and validated to assess the effectiveness of its impact absorption mechanism. This robot was developed in anticipation of situations where direct human intervention for life rescue would be challenging. Throwing robots can be broadly categorized into ball type, wheel type, and hybrid type. The hybrid type combines the advantages of both: the ease of throwing from ball type, due to its low air resistance coefficient, and the versatile mobility of the wheel type in diverse environments. However, hybrid type throwing robots are more vulnerable to external impacts due to the complexity of their internal structure, resulting in a lower maximum drop height compared to wheel type *** address these challenges, this research proposes a the Throwbot that combines the easy throwing capability of ball type with the obstacle overcoming ability of the wheel type, while also addressing the low free fall height drawback inherent in hybrid types. To achieve this, we developed a Throwbot with a ball to wheel transform structure, p-CFH mechanism, and airbag based impact absorption system. Additionally, materials were selected based on simulation results to refine the Throw-bot. The performance of the proposed robot was evaluated through various assessments, including free fall experiments and obstacle overcoming tests. Through this research, the proposed Throwbot effectively addresses the shortcomings of existing throwing robots, establishing a novel approach to throwing robot design.

关键词： Absorption Electric shock Simulation Wheels Transforms Reconnaissance Mobile robots Robots Intelligent robots Immune system

来源：评论

学校读者我要写书评

暂无评论

Analytical and Deep Neural Network Based Hybrid Modelling of Single-Segment Continuum Robot

Analytical and Deep Neural Network Based Hybrid Modelling of...

引用

International Conference on Industrial Instrumentation and Control,ICI2C 2021

作者： Bhattacherjee, Saptak Chattopadhyay, Sudipta Sengupta, Aparajita Bhaumik, Subhasis School of Mechatronics and Robotics Indian Institute of Engineering Science and Technology Howrah Shibpur India Department of Electrical Engineering Indian Institute of Engineering Science and Technology Howrah Shibpur India

ISBN: (纸本)9789811670107

Hyper-redundancy and ability to propagate through complex curvilinear pathways have made the continuum robots immensely popular in different fields of application. Precise control of continuum robot position relies on the accurate knowledge of the manipulator kinematics. However, the inverse kinematic model of continuum robots based on analytical modelling fails to include the unmodeled dynamics and effect of disturbances due to gravity and friction resulting in low accuracy in modelling and control. On the other hand, purely data driven continuum models require huge amount of data and time for training and suffer from high inaccuracy in modelling as well. Hybrid modelling in this scenario has been perceived to achieve better accuracy by combining the advantages of these two modelling approaches. Therefore, in the present work, we focus on the inverse kinematics of the single-segment continuum robot by using the analytical and deep neural network based hybrid modelling approach. Experimental results indicate that the proposed method increases the modelling accuracy and also at the same time it reduces the network training time significantly. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Design and Analysis of a Novel Hybrid Grasping Mode Microgripper for High Precision Tasks 9

Design and Analysis of a Novel Hybrid Grasping Mode Microgri...

引用

9th IEEE International Women in engineering (WIE) Conference on Electrical and Computer engineering, WIECON-ECE 2023

作者： Das, Tilok Kumar Shahrear, Rifat Das, Arpita Shirinzadeh, Bijan Dept. of Mechanical Engineering Chattogram Bangladesh Temple University Dept. of Electrical and Computer Engineering PhiladelphiaPA United States Monash University Robotics and Mechatronics Research Laboratory Dept. of Mechanical and Aerospace Engineering MelbourneVIC Australia

ISBN: (纸本)9798350319651

This paper represents a novel piezoelectric actuated flexure-based compliant microgripper which can perform both parallel and angular grasping regardless of the geometric surface of the objects. Two compliant bridge-type mechanisms along with two symmetrical microgripper jaws at the end of the two side arms are accommodated to construct the microgripper. The two side arms of the microgripper act as lever-type amplification mechanisms. Simultaneous actuation of two bridge-type mechanisms is needed to perform linearized parallel grasping. The symmetric design is adopted to maintain better stability. The Finite Element Analysis (FEA) has been performed to evaluate the performance of the microgripper. FEA shows that each jaw of the microgripper can achieve a displacement of 141.72 μm resulting in a total displacement of 283.44 μm with an amplification ratio of 10.7 and 0.715% parasitic motion in y-direction of the X -axis displacement during parallel grasping. Also, each jaw can achieve a displacement of 283.88 μm which results in a total displacement of 567.76 μm with an amplification ratio of 21.5 and 5.17 mrad angular rotation about the Z-axis during angular grasping. The FEA suggests that the microgripper is capable of both parallel and angular grasping/releasing tasks. © 2023 IEEE.

关键词： Piezoelectric actuators

来源：评论

学校读者我要写书评

暂无评论

GripFlexer: Development of hybrid gripper with a novel shape that can perform in narrow spaces

GripFlexer: Development of hybrid gripper with a novel shape...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Donghyun Kim Sunghyun Choi Bongsub Song Jinhyeok Song Jingon Yoon Dongwon Yun Department of Robotics and Mechatronics Engineering Daegu Gyeongbuk Institute of Science and Technology (DGIST) Daegu South Korea

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

In recent years, the role of robots across industries has become increasingly diverse, and they are now required to perform complex missions beyond simple repetitive tasks. However, robots used in confined spaces that humans cannot reach or in disaster field missions have challenges in performing various tasks due to their small size. In this study, we developed a compact hybrid gripper that fuses a multi-finger gripper and a jamming gripper to perform various tasks in a confined environment. Such a hybrid gripper can have both the strengths of a multi finger gripper that can perform various tasks and a jamming gripper that can effectively handle irregular small objects. In this study, we developed a hybrid gripper "GripFlexer" based on theoretical analysis and confirmed its performance through experiments by taking the task of turning a circular doorknob, which is one of the most difficult tasks in disaster sites, as the final target task. We also confirmed that the two grippers of GripFlexer can interact by showing performance improvement effects when two grippers are operated simultaneously.

关键词： Torque Service robots Shape Disasters Space missions Force Production Turning Grippers Jamming

来源：评论

学校读者我要写书评

暂无评论

i-Glove: An Intelligent Glove System Based on Deep Learning to Support Deaf-blind Individuals in Recognizing Banknotes

i-Glove: An Intelligent Glove System Based on Deep Learning ...

引用

robotics, Automation, Artificial-intelligence and Internet-of-Things (RAAICON), 2019 IEEE International Conference on

作者： Fahad Mohammad Hossain Rafit Alavi Yeamin Safat Gobinda Chandra Sarker Nafisa Noor Ekram Hossain Department of Computer Science and Engineering Mymensingh Engineering College Mymensingh Bangladesh Department of Robotics and Mechatronics Engineering University of Dhaka Dhaka Bangladesh

ISBN: (数字)9798331534400

ISBN: (纸本)9798331534417

The deaf-blind community faces significant challenges in identifying banknotes due to simultaneous hearing and vision impairments, which complicate their ability to conduct daily financial transactions. Recent advances in Artificial Intelligence (AI)-based assistive technologies offer promising potential to address these challenges. This study presents the "i-Glove," a wearable device specifically developed to assist the deaf-blind community in Bangladesh with accurate banknote identification. The i-Glove is designed to recognize nine common Bangladeshi banknotes (e.g., BDT 20, 50, 100) through a camera module integrated on the palmar side of the glove, which captures real-time images of the banknotes. These images are then processed by a convolutional neural network (CNN) model to accurately classify each banknote. Identified notes are translated into unique vibration patterns that are delivered to the user through a shaftless vibration motor embedded in the glove, providing intuitive, non-visual communication. Compared to previous approaches, our model demonstrates superior performance even with a compact dataset, achieving an overall F1-score accuracy of 96.55%, with class-specific precision, recall, and F1-score metrics ranging from 90% to 100%. Additionally, a dedicated application is developed which supports real-time banknote detection and interfaces seamlessly with the glove. The proposed system represents a significant step forward in assistive technology for the deaf-blind community, empowering the users with greater autonomy in financial transactions.

关键词： Vibrations Visualization Accuracy Image recognition Tactile sensors Assistive technologies Motors Real-time systems Convolutional neural networks Wearable devices

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：