检索结果-内蒙古大学图书馆

IEEE International Conference on automation Science and Engineering (CASE)

作者： Osama Tasneem Roel Pieters Cognitive Robotics Group Unit of Automation Technology and Mechanical Engineering Tampere University Tampere Finland

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

Visual inspection is a crucial yet time-consuming task across various industries. Numerous established methods employ machine learning in inspection tasks, necessitating specific training data that includes predefined inspection poses and training images essential for the training of models. The acquisition of such data and their integration into an inspection framework is challenging due to the variety in objects and scenes involved and due to additional bottlenecks caused by the manual collection of training data by humans, thereby hindering the automation of visual inspection across diverse domains. This work proposes a solution for automatic path planning using a single depth camera mounted on a robot manipulator. Point clouds obtained from the depth images are processed and filtered to extract object profiles and transformed to inspection target paths for the robot end-effector. The approach relies on the geometry of the object and generates an inspection path that follows the shape normal to the surface. Depending on the object size and shape, inspection paths can be defined as single or multi-path plans. Results are demonstrated in both simulated and real-world environments, yielding promising inspection paths for objects with varying sizes and shapes. Code and video are open-source available at: https://***/CuriousLad1000/Auto-Path-Planner

关键词： Point cloud compression Training Visualization Shape Robot vision systems Training data Inspection Cameras Path planning Hardware

来源：评论

学校读者我要写书评

暂无评论

Prediction of compressive strength of concrete using multilayer perception network, generalized feedforward network, principal component analysis network, time lagged recurrent network, recurrent network

引用

Asian Journal of Civil Engineering 2025年第1期26卷 431-450页

作者： Pathak, Sudhanshu S Mane, Sachin J Vesmawala, Gaurang R Sarnobat, Sandeep S Department of Civil Engineering D Y Patil College of Engineering Pune Akurdi India Department of Civil Engineering Sardar Vallabhbhai National Institute of Technology Gujarat Surat India Department of Robotics and Automation D Y Patil College of Engineering Pune Akurdi India

The present work aimed to study the artificial neural network (ANN) and its effectiveness for prediction of compressive strength (fc). Genetic algorithm (GA) was used for optimization of five different types of ANN ne... 详细信息

The present work aimed to study the artificial neural network (ANN) and its effectiveness for prediction of compressive strength (f_c). Genetic algorithm (GA) was used for optimization of five different types of ANN networks viz. multilayer Perception network (MLP), generalized feedforward network (GFF), principal component analysis network (PCA), time lagged recurrent networks (TLRN), recurrent networks (RN). A 272 data set of f_c was obtained from the various literatures and used for training, testing and validation. Mean square error (MSE), mean absolute error (MAE) and correlation coefficient (R) used as validation criteria. Water to cement (w/c) ratio, maximum size of aggregate, curing days and cement content etc. were used as input parameter for prediction of f_c. The result reveals that MLP has more precise compared with GFF, PCA, TLRN, RN, the observed values of R is 0.97, MSE is 42.30 and MAE is 5.57, which indicates the model is best fir for prediction of f_c. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Artificial neural network Compressive strength Genetic algorithm Multilayer perception

来源：评论

学校读者我要写书评

暂无评论

Application of artificial neural network for prediction of fracture energy of concrete

引用

Asian Journal of Civil Engineering 2025年第6期26卷 2629-2644页

作者： Pathak, Sudhanshu Mane, Sachin Pataskar, Smita Vemawala, Gaurang Shiyekar, Sandeep Sarnobat, Sandeep Department of Civil Engineering D Y Patil College of Engineering Akurdi Pune India Department of Civil Engineering Sardar Vallabhbhai National Institute of Technology Gujarat Surat India Department of Robotics and Automation D Y Patil College of Engineering Akurdi Pune India

The analysis of fracture parameters of concrete drawing the researchers attention and getting popular day by day. Every concrete structure undergoes crack formation, initiation and propagation phase, to understand the kind and severity of crack study the fracture mechanics is very much needed. Fracture energy (G_f) is one the main characteristic amongst numerous fracture parameters. The different parameters such as water to cement (w/c) ratio, compressive strength (fc), diameter of aggregates, testing age of specimens etc. play essential role in understanding the G_f. In present work, G_f of concrete is measured by replacing cement with nano TiO₂ (NT) at 1, 2, 3, and 4% of the concrete mix, as well as fly ash (FA) and ground granulated blast furnace slag (GGBS) at 10, 20, 30, and 40%. The G_f was investigated using the size effect technique (SEM), and the notched beams were subjected to a three-point bend test. According to the experimental results, the NT4FA40 mix had the maximum G_f, while mixtures including FA out performed than GGBS mixes. Furthermore, an attempt was made to anticipate G_f using the soft computing method in light of the current necessity. The G_f is predicted using an ANN. The literature database, which includes 193 fracture tests, was gathered from earlier research in addition to the data from the current experimental investigation. Furthermore, the formula proposed by Bažant and Becq-Giraudon was utilized to make predictions based on a number of characteristics, including compressive strength, maximum aggregate size, and w/c ratio. compressive strength, maximum aggregate size, and water to cement ratio are among the characteristics that are trained, verified, and tested for ANN. The ANN model developed using literature-based data, Bažant and Becq-Giraudon equation derived data and experimental data gives promising results with R values 0.999, 0.981, 0.984 respecti

关键词： Artificial neural network Fly ash Fracture energy Ground granulated blast furnace slag Nano TiO2

来源：评论

学校读者我要写书评

暂无评论

Robot Vacuum Cleaner Using SLAM and ROS

Robot Vacuum Cleaner Using SLAM and ROS

引用

Knowledge Engineering and Communication Systems (ICKECS), International Conference on

作者： M Arjun Cliff Andrew Oliver Anju Mary Joseph Dept. of Robotics and Automation Adi Shanakara Institute of Engineering and Technology Kalady Ernakulam India

ISBN: (数字)9798350359688

ISBN: (纸本)9798350359695

For the past few years, robot vacuum cleaners have made a huge impact on society. There are different types of robot vacuum cleaners, differentiated based on their method of operation. In this paper, we present a comprehensive framework for enhancing the autonomous capabilities of robot vacuum cleaners by integrating the Robot Operating System (ROS) and Simultaneous Localization and Mapping (SLAM) techniques. Our robot uses laser mapping to map the entire environment and is faster than other robot vacuum cleaners. Our approach not only enhances the performance of robot vacuum cleaners but also provides a foundation for future research and development in the field of domestic service robots. The ROS and SLAM integration framework presented in this paper can be extended to other robotic applications, advancing the state of the art in autonomous navigation and perception for household robotics.

关键词： Productivity Simultaneous localization and mapping Vacuum systems Service robots Motors Cleaning Sensors

来源：评论

学校读者我要写书评

暂无评论

Magnetically Driven Capsule Robot for Multi-Targeted Biopsy and Drug Delivery in Stomach

Magnetically Driven Capsule Robot for Multi-Targeted Biopsy ...

引用

2023 IEEE International Conference on robotics and Biomimetics, ROBIO 2023

作者： Xu, Zhihui Wei, Tanyong Li, Zongze Huang, Ding Liu, Shoubin Hu, Chengzhi Southern University of Science and Technology Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy Engineering Shenzhen China Southern University of Science and Technology Guangdong Prov. Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Shenzhen China Harbin Institute of Technology School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350325706

Capsule robots have emerged as a promising solution for non-invasive and painless screening of gastrointestinal diseases, offering significant advantages in patient comfort and reduced risk of cross-infection. Despite these advantages, existing capsule robots fall short in their ability to conduct targeted biopsies and deliver drugs to specific gastric lesions. To address this limitation, this paper presents the design and development of a magnetically driven capsule robot that leverages visual feedback to achieve accurate targeting for biopsy and drug administration in gastric lesions. Internal magnets, responsive to an external gradient magnetic field, enable the controlled propulsion of the capsule robot. A kinetic model of the capsule robot is analyzed, allowing it to recognize lesion contours through the endoscopic camera. This recognition determines the rotation angle or small adjustments required for the capsule robot's attitude and positioning. Experimental results in a simplified in vitro stomach model showcase the capability of the capsule robot to achieve targeted biopsy and drug delivery. These results highlight the potential feasibility of the proposed capsule robot in enhancing diagnostic accuracy and treatment efficacy with broader applications within the realm of gastric healthcare. © 2023 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Gaze Betray You: Abnormal Attention Detection from Human-Robot Interaction Dynamics

Gaze Betray You: Abnormal Attention Detection from Human-Rob...

引用

IEEE International Conference on robotics and Biomimetics

作者： Fengjun Mu Jingting Zhang Chaobin Zou Zonghai Huang Rui Huang Hong Cheng Center for Robotics School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Monitoring abnormal attention has a wide range of applications in Human-Robot Interaction systems, such as autonomous driving, virtual reality, and remote operation. Due to factors like fatigue, drowsiness, and distraction, human attention can deviate from tasks that require focus, resulting in abnormal attention during interactions. Monitoring for abnormal attention is essential to ensure the safety of human-robot interactions. However, existing methods often rely on un-explainable algorithms such as neural networks, making them difficult to trust in scenarios like autonomous driving, where explicit decision-making processes and mechanisms are required. This paper presents EyeAAD, an abnormal attention detection method based on dynamic system theory. This method uses gaze signals from a serious game designed to simulate human-robot interaction. We developed several attention-related features for interpretable modeling using a deterministic learning method. By analyzing the matching relationship between the gaze signal and the predicted status from the learned dynamic models, we can detect abnormal human attention patterns. To validate our approach, we designed a serious game for eye movement data acquisition in human-robot interaction. Our analysis showed that EyeAAD enables efficient, real-time monitoring of human attention.

关键词： Solid modeling Human-robot interaction Games Virtual reality Feature extraction Safety Pattern matching Monitoring Autonomous vehicles Robots

来源：评论

学校读者我要写书评

暂无评论

Enhancing Dynamic Parameter Identification for Supernumerary Robotic Limbs Through Uncertainty Compensation

Enhancing Dynamic Parameter Identification for Supernumerary...

引用

Chinese automation Congress (CAC)

作者： Lufeng Chen Jingwen Lan Qi'ao Zhan Zhinan Peng Wenjiang Li Jing Qiu Center for Robotics School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurate dynamic modeling is fundamental for wearable robotics, such as Supernumerary Robotic Limbs (SRLs), to ensure precise control and effective interaction with the environment. This paper presents an enhanced dynamic model for an SRL, incorporating uncertainty compensation to improve accuracy and robustness. The SRL dynamics are streamlined by linearizing the system and identifying a minimal set of inertia parameters. Using the Coot optimization algorithm, we refine the Fourier excitation trajectory parameters to optimize the condition number of the observation matrix, followed by parameter identification through the least squares method. To further reduce discrepancies between predicted and actual joint torques, an uncertainty term is introduced, validated through a neural network designed to predict torque variations. The method not only addresses but also compensates for uncertainties across various motion states of the SRL. Experimental results demonstrate that the proposed model improves prediction accuracy and robustness for our developed 6-DoF SRL compared to traditional methods.

关键词： Uncertainty Accuracy Torque Parameter estimation Computational modeling Predictive models Aerodynamics Robustness Trajectory Robots

来源：评论

学校读者我要写书评

暂无评论

Calibration Method of Industrial Robot Kinematic Parameters Based on Improved SSA Algorithm 6

Calibration Method of Industrial Robot Kinematic Parameters ...

引用

6th International Conference on Software Engineering and Computer Science, CSECS 2023

作者： Xu, Jialu Liu, Xiaonan Li, Pengchao Wang, Jintao Guo, Haibing School of Information Science and Engineering Shenyang University of Technology Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang China Tianjin SIASUN Robot & Automation Co. LTD. Tianjin China

ISBN: (纸本)9798350306378

The requirements of high-end manufacturing cannot be fulfilled by industrial robot absolute positioning accuracy. A study of algorithms for improving absolute positioning accuracy in industrial robots. An improved sparrow search algorithm (ISSA) incorporating a chaotic mapping initialization population, a butterfly global search strategy, a triangle wandering strategy, and a t-distribution perturbation is proposed to identify the kinematic parameters of industrial robots. First, a robot kinematics model is established based on modified Denavit-Hartenberg (MD-H) parameters. Secondly, verify the effectiveness of the ISSA algorithm. Finally, the kinematic parameters of four T6A-19 industrial robots were determined and adjusted for validation using the ISSA algorithm. The results of the experiment demonstrate an 85.39% improvement in the accuracy of the mean absolute positional error and an 83.36% improvement in the root mean square accuracy. These results support the effectiveness and practicality of the method used. © 2023 IEEE.

关键词： Industrial robots

来源：评论

学校读者我要写书评

暂无评论

Augmented Reality-based Robot Control for Laparoscopic Surgery

Augmented Reality-based Robot Control for Laparoscopic Surge...

引用

作者： Kunz, Christian Maierhofer, Pascal Gyenes, Balázs Franke, Nikolai Younis, Rayan Müller-Stich, Beat-Peter Wagner, Martin Mathis-Ullrich, Franziska Health Robotics and Automation Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe76131 Germany Department for General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg69120 Germany

Minimally invasive surgery is the standard for many abdominal interventions, with an increasing use of telemanipulated robots. As collaborative robots enter the field of medical interventions, their intuitive control needs to be addressed. Augmented reality can thereby support a surgeon by representing the surgical scene in a natural way. In this work, an augmented reality based robot control for laparoscopic cholecystectomy is presented. A user can interact with the virtual scene to clip the cystic duct and artery as well as to manipulate the deformable gallbladder. An evaluation was performed based on the SurgTLX and system usability scale. © 2022 by Walter de Gruyter Berlin/Boston.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Preface: Third International Conference on Advancements in automation, robotics and Sensing (ICAARS 2022)

引用

AIP Conference Proceedings 2024年第1期3035卷 010001-010001页

作者： Vinod, B. Subashini, G. Suresh, M. Department of Robotics and Automation Engineering PSG College of Technology Coimbatore India

Preface: Third International Conference on Advancements in automation, robotics and Sensing (ICAARS 2022), AIP Conference Proceedings, Volume 3035, Issue 1, 4 M

关键词：

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：