检索结果-内蒙古大学图书馆

IEEE SENSORS

作者： Elisabetta Leogrande Francesco Dell'Olio Stefano Mazzoleni Calogero Maria Oddo Mariangela Filosa Department of Electrical and Information Engineering Polytechnic University of Bari Italy Department of Excellence in Robotics & AI The BioRobotics Institute Sant' Anna School of Advanced Studies Pisa Italy Interdisciplinary Research Center Health Science Sant’ Anna School of Advanced Studies Pisa Italy

ISBN: (数字)9798350363517

ISBN: (纸本)9798350363524

The field of collaborative robotics is constantly growing given the central role that safe human-robot interactions are gaining in the current era of Industry 4.0. To act and interact, robotic systems are increasingly being either natively equipped with or adapted to house sensing devices. In this scenario, tactile sensors are fundamental to detect impacts, accurately manipulate objects and enable learning from demonstration strategies. The development of such systems requires technological efforts in terms of both design, for their seamless integration in robots, and software programming, for achieving reliable and prompt reactions to relevant events. In this study, an edge AI algorithm deployed on an embedded device for the recognition of contacts on an FBG (Fiber Bragg Grating)-based e-skin is presented. A Convolutional Neural Network has been trained offline to localize touch events occurred on the e-skin. The performance of the algorithm assessed on the test set reached a mean absolute error on the three cartesian coordinates of less than 4 mm. The algorithm has been then ported to a microcontroller board for real-time testing of both simulated and concurrent contacts. The achievements of this work pave the way to new opportunities for collaborative robotics applications through intelligent FBG-based artificial tactile skins.

关键词： Service robots Robot kinematics Software algorithms Tactile sensors Collaboration Edge AI Fiber gratings Software Software reliability Testing

来源：评论

学校读者我要写书评

暂无评论

Handling Collaborative Robot System for Grasping Medical Cotton Cloth Porous with Bernoulli Gripper

Handling Collaborative Robot System for Grasping Medical Cot...

引用

IEEE International Conference on Mechatronics and Automation

作者： Kitti Suwanratchatamanee Hideyuki Sawada Shuji Hashimoto Department of Engineering Robotics Research and Development Center Golden Robot Co. Ltd Banchang Rayong Thailand Department of Applied Physics Graduate School of Advanced Science and Engineering Faculty of Science and Engineering Waseda University Tokyo Japan Waseda University Tokyo Japan

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

This paper presents the handling collaborative robot (Cobot) system for grasping the medical cotton cloth porous that were arranged in matching layers from one point to another point by arranged them in matching layers again. The important is to not grasping all layer objects together in once, but must be separately for each layer by layer. As the object to be grasped is the cotton cloth porous to be used in the medical purpose, thus the cleanness and must not leave any wrinkles or marks when handled the fabric are necessity required before packaging process. The proposed handling collaborative robot system contains the novel tooling called "Bernoulli Gripper" can achieve this handling task perfectly with 100% success rate of experiments. This gripper was developed to lifts the porous fabric sheet up in such a way that it does not grasping touch by utilizing four points Bernoulli principle elements like no other grippers that need to do the touching forces and always leave wrinkles or marks when handled the fabric, such as pneumatic suction cup, robot hand and fingers. Moreover, the research objective is to produce the handling robot system that can achieve the non-contact grasping and do collaborative tasks together with human in the same environment. As the result, our proposed system can be used for working together with human worker as the collaborative partner to arrange these medical cotton cloth porous products with about 6.5 seconds per sheet in the real production line suitably.

关键词： Mechatronics Grasping Collaborative robots Production Pneumatic systems Packaging Fabrics

来源：评论

学校读者我要写书评

暂无评论

Autoencoder-XGBoost Classifier (AeXGB) for Predicting Severity Level of Parkinson's Disease from Spontaneous Speech

Autoencoder-XGBoost Classifier (AeXGB) for Predicting Severi...

引用

2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Wai, Thiri Liao, Yu-Shan Liao, Ting-Yun Lin, Chin-Hsien Hung, Chi-Sheng Fu, Li-Chen National Taiwan University Department of Computer Science and Information Engineering Taipei Taiwan Graduate Institute of Biomedical Engineering College of Medical Science and Technology Taipei Medical University National Taiwan University Hospital Bei-Hu Branch Department of Neurology Taipei Taiwan Institute of Molecular Medicine College of Medicine National Taiwan University Taipei Taiwan National Taiwan University Hospital and National Taiwan University College of Medicine Department of Internal Medicine Taipei Taiwan and Advanced Robotics Taiwan

ISBN: (纸本)9781665410205

Parkinson's disease (PD) is the cause of the gradual decline of nerve cells that control movement disorder disease, which is most common among the elderly in the US after Alzheimer's disease. There are several studies on detecting Parkinson's disease from speech using machine learning techniques;however, most of them focus on classifying healthy patients (HC) against Parkinson's disease (PD). This paper focuses on developing a screening system that could detect healthy (HC) vs. mild Parkinson's (MP) vs. severe Parkinson's (SP) from spontaneous speech. Four acoustic feature sets were compared for the screening system. Our proposed AeXGB was also compared with six different classifying approaches. The result has shown that extracting the phonation features and using AeXGB could achieve an accuracy of 92% for classifying HC vs. MP vs. SP, which outperforms the traditional machine learning approach for three class classifications of Parkinson's severity level from spontaneous speech. © 2024 IEEE.

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

IMPROVING CROSS-DOMAIN FEW-SHOT CLASSIFICATION WITH MULTILAYER PERCEPTRON

arXiv

引用

arXiv 2023年

作者： Bai, Shuanghao Zhou, Wanqi Luan, Zhirong Wang, Donglin Chen, Badong Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China School of Electrical Engineering Xi’an University of Technology Xi’an China Westlake University Institute of Advanced Technology Westlake Institute for Advanced Study China

Cross-domain few-shot classification (CDFSC) is a challenging and tough task due to the significant distribution discrepancies across different domains. To address this challenge, many approaches aim to learn transferable representations. Multilayer perceptron (MLP) has shown its capability to learn transferable representations in various downstream tasks, such as unsupervised image classification and supervised concept generalization. However, its potential in the few-shot settings has yet to be comprehensively explored. In this study, we investigate the potential of MLP to assist in addressing the challenges of CDFSC. Specifically, we introduce three distinct frameworks incorporating MLP in accordance with three types of few-shot classification methods to verify the effectiveness of MLP. We reveal that MLP can significantly enhance discriminative capabilities and alleviate distribution shifts, which can be supported by our expensive experiments involving 10 baseline models and 12 benchmark datasets. Furthermore, our method even compares favorably against other state-of-the-art CDFSC algorithms. Copyright © 2023, The Authors. All rights reserved.

关键词： Multilayer neural networks

来源：评论

学校读者我要写书评

暂无评论

Autonomous Exploration of Unknown 3D Environments Using a Frontier-Based Collector Strategy

Autonomous Exploration of Unknown 3D Environments Using a Fr...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Iván D. Changoluisa Caiza Ana Milas Marco A. Montes Grova Francisco Javier Pérez-Grau Tamara Petrovic University of Zagreb Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia Advanced Center for Aerospace Technologies (CATEC) Aerospace Technology Park of Andalusia Seville Spain

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Autonomous exploration using unmanned aerial vehicles (UAVs) is essential for various tasks such as building inspections, rescue operations, deliveries, and warehousing. However, there are two main limitations to previous approaches: they may not be able to provide a complete map of the environment and assume that the map built during exploration is accurate enough for safe navigation, which is usually not the case. To address these limitations, a novel exploration method is proposed that combines frontier-based exploration with a collector strategy that achieves global exploration and complete map creation. In each iteration, the collector strategy stores and validates frontiers detected during exploration and selects the next best frontier to navigate to. The collector strategy ensures global exploration by balancing the exploitation of a known map with the exploration of unknown areas. In addition, the online path replanning ensures safe navigation through the map created during motion. The performance of the proposed method is verified by exploring 3D simulation environments in comparison with the state-of-the-art methods. Finally, the proposed approach is validated in a real-world experiment.

关键词： Three-dimensional displays Video on demand Navigation Warehousing Buildings Inspection Web sites

来源：评论

学校读者我要写书评

暂无评论

An Integrated Timetable Optimization and Automatic Guided Vehicle Dispatching Method in Smart Manufacturing

An Integrated Timetable Optimization and Automatic Guided Ve...

引用

International Conference on Intelligent Transportation

作者： Jiarong Yao Rong Su Chaopeng Tan School of Electrical and Electronic Engineering Nanyang Technological University Singapore Centre for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Transport and Planning Delft University of Technology Delft Netherlands

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Automatic guided vehicle (AGV) fleet management always plays a significant role in smart manufacturing, which is widely studied as a representative nondeterministic polynomial-hard combinatorial optimization problem. With more smart factories featuring specialization in production line and human-robot interaction, AGVs are commonly bound with specific tracks, loading and unloading stations, which makes the current routing algorithms fail to play their path searching ability in complicated network topology. Thus, an integrated timetable optimization and AGV dispatching (TOAD) model is proposed aimed at such case, shifting the emphasis of routing to station selection and route selection from the perspective of timetable designing, while still considering the mixed directivity of layout, conflict avoidance, AGV availability and charging requirements. Targeted at makespan minimization, an improved genetic algorithm (GA) is used for solution with a heuristic operator to seek a better solution within shorter time. The proposed method is evaluated using an empirical factory case study with field data as input, with a comparison with the exact algorithm and standard GA. Results show that a smaller makespan and a shorter computation time can be obtained by the proposed TOAD model in large-scale scenarios, demonstrating a promising application prospect.

关键词： Job shop scheduling Computational modeling Transportation Routing Dispatching Production facilities Tuning Standards Smart manufacturing Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Goal-Conditioned Reinforcement Learning Approach for Autonomous Parking in Complex Environments

Goal-Conditioned Reinforcement Learning Approach for Autonom...

引用

International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Taeyoung Kim Taemin Kang Seungah Son Kuk Won Ko Dongsoo Har CCS Graduate School of Mobility Korea Advanced Institute of Science and Technology(KAIST) Daejeon Rep. of Korea The Robotics Program Korea Advanced Institute of Science and Technology(KAIST) Daejeon Rep. of Korea Department of Future Mobility Engineering Halla University Wonju Rep. of Korea

ISBN: (数字)9798331507022

ISBN: (纸本)9798331507039

In complex urban environments, autonomous vehicle parking is challenged by irregularly parked cars, static obstacles, and narrow spaces. Traditional parking methods are often limited to well-structured parking lots and fail to adapt to unstructured scenarios like alleyways with obstacles and randomly positioned vehicles. This paper addresses this limitation by applying goal-conditioned reinforcement learning to enable autonomous vehicles to park in congested environments based on specified target positions and orientations. A custom simulation environment is developed using Pygame to simulate parking scenarios across four progressive levels of difficulty, with obstacles to test adaptability. Three RL algorithms, SAC, HER, and an improved HER variant, are implemented to compare the performance in the simulation environment. Experimental results demonstrate that the proposed approach significantly improves parking success rates and trajectory efficiency in complex scenarios, contributing to robust, adaptable parking solutions for autonomous vehicles in real-world applications.

关键词： Training Space vehicles Three-dimensional displays Urban areas Reinforcement learning Trajectory Reliability Vehicle dynamics Autonomous vehicles Testing

来源：评论

学校读者我要写书评

暂无评论

The Impact of SBOM Generators on Vulnerability Assessment in Python: A Comparison and a Novel Approach

arXiv

引用

arXiv 2024年

作者： Benedetti, Giacomo Cofano, Serena Brighente, Alessandro Conti, Mauro Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Italy IMT School for Advanced Studies Lucca Italy Department of Mathematics University of Padua Italy Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Netherlands

The Software Supply Chain (SSC) security is a critical concern for both users and developers. Recent incidents, like the SolarWinds Orion compromise, proved the widespread impact resulting from the distribution of compromised software. The reliance on open-source components, which constitute a significant portion of modern software, further exacerbates this risk. To enhance SSC security, the Software Bill of Materials (SBOM) has been promoted as a tool to increase transparency and verifiability in software composition. However, despite its promise, SBOMs are not without limitations. Current SBOM generation tools often suffer from inaccuracies in identifying components and dependencies, leading to the creation of erroneous or incomplete representations of the SSC. Despite existing studies exposing these limitations, their impact on the vulnerability detection capabilities of security tools is still unknown. In this paper, we perform the first security analysis on the vulnerability detection capabilities of tools receiving SBOMs as input. We comprehensively evaluate SBOM generation tools by providing their outputs to vulnerability identification software. Based on our results, we identify the root causes of these tools' ineffectiveness and propose PIP-sbom, a novel pip-inspired solution that addresses their shortcomings. PIP-sbom provides improved accuracy in component identification and dependency resolution. Compared to best-performing state-of-the-art tools, PIP-sbom increases the average precision and recall by 60%, and reduces by ten times the number of false positives. © 2024, CC BY-SA.

关键词： Input output programs

来源：评论

学校读者我要写书评

暂无评论

Evolution of Iron-Based Metallic Glass Composite Coating with Enhanced Corrosion Resistance and Biocompatibility

引用

Arabian Journal for Science and engineering 2024年第8期49卷 10547-10559页

作者： Ibrahim, Mahmoud Z. Sarhan, A.A.D. Kuo, T.Y. Yusof, Farazila Hamdi, M. Chang, C.P. Lee, T.M. Chien, C.S. Department of Mechanical Engineering Faculty of Engineering Ain Shams University Cairo 11517 Egypt Advanced Manufacturing & Material Processing (AMMP) Research Centre Department of Mechanical Engineering Faculty of Engineering University of Malaya Kuala Lumpur 50603 Malaysia Department of Mechanical Engineering Faculty of Engineering University of Malaya Kuala Lumpur 50603 Malaysia Department of Mechanical Engineering King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Interdisciplinary Research Centre for Intelligent Manufacturing & Robotics King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Department of Mechanical Engineering Southern Taiwan University of Science and Technology Tainan 701 Taiwan Department of Medical Research Chimei Medical Centre Tainan 710 Taiwan Institute of Oral Medicine National Cheng Kung University Tainan 701 Taiwan Department of Orthopaedics Chimei Foundation Hospital Tainan 710 Taiwan

Metallic glasses are a new class of metallic alloys that attract increasing attention in bone implants due to their ultrahigh wear resistance and hardness, high toughness and superior strength. However, their cytotoxicity and biocorrosion resistance are still under investigation. In this research, the cytotoxicity and biocorrosion resistance of iron-based metallic glass composite coating are explored. To approach real-life conditions, the biocorrosion resistance of the proposed coating in phosphate buffer saline (PBS) is evaluated via immersion test for 30 days followed by an electrochemical corrosion test. Then, human bone cells (MG-63) are cultured on corroded samples and the cell viability is determined using MTT assay, in addition to cell attachment examination. The results revealed the formation of a metallic glass composite layer with 78.76% amorphous content. Additionally, the metallic glass composite demonstrated excellent and stable corrosion resistance in PBS over 30 days compared to the substrate. The MTT assay has shown that the cytotoxicity of iron-based metallic glass composite is within the permitted levels according to ISO 10993–5, Part 5 vol 2009. The cells were well attached to the surface besides, showing a healthy growth after 7 days of culture. These results confirm the in vitro biocompatibility of iron-based metallic glass composite coating for biomedical implant applications. © 2023, King Fahd University of Petroleum & Minerals.

关键词： Biocorrosion Coating Cytotoxicity Iron-based metallic glass composite Joint replacement applications

来源：评论

学校读者我要写书评

暂无评论

NANO-SLAM: Natural Gradient Gaussian Approximation for Vehicle SLAM

arXiv

引用

arXiv 2025年

作者： Zhang, Tianyi Cao, Wenhan Liu, Chang Zhang, Feihong Wu, Wei Li, Shengbo Eben School of Vehicle and Mobility Tsinghua University Beijing China Department of Advanced Manufacturing and Robotics College of Engineering Peking University Beijing China School of Vehicle and Mobility College of Artificial Intelligence Tsinghua University Beijing China

Accurate localization is a challenging task for autonomous vehicles, particularly in GPS-denied environments such as urban canyons and tunnels. In these scenarios, simultaneous localization and mapping (SLAM) offers a more robust alternative to GPS-based positioning, enabling vehicles to determine their position using onboard sensors and surrounding environment’s landmarks. Among various vehicle SLAM approaches, Rao-Blackwellized particle filter (RBPF) stands out as one of the most widely adopted methods due to its efficient solution with logarithmic complexity relative to the map size. RBPF approximates the posterior distribution of the vehicle pose using a set of Monte Carlo particles through two main steps: sampling and importance weighting. The key to effective sampling lies in solving a distribution that closely approximates the posterior, known as the sampling distribution, to accelerate convergence. Existing methods typically derive this distribution via linearization, which introduces significant approximation errors due to the inherent nonlinearity of the system. To address this limitation, we propose a novel vehicle SLAM method called Natural Gradient Gaussian Approximation (NANO)-SLAM, which avoids linearization errors by modeling the sampling distribution as the solution to an optimization problem over Gaussian parameters and solving it using natural gradient descent. This approach improves the accuracy of the sampling distribution and consequently enhances localization performance. Experimental results on the long-distance Sydney Victoria Park vehicle SLAM dataset show that NANO-SLAM achieves over 50% improvement in localization accuracy compared to the most widely used vehicle SLAM algorithms, with minimal additional computational cost. © 2025, CC BY.

关键词： SLAM robotics

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：