检索结果-内蒙古大学图书馆

7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Chen, Haonan Liu, Xianda Wang, Tianyu Zhang, Xuejing College of Information Science and Engineering Northeastern University Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Beijing China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Beijing China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783030786083

As an important part of guard system, intrusion detection systems have great significance to the security of industrial control systems. Cause the industrial control systems of the on-site environment is often very complicated, the process data extracted on-site have a wide variety of features, and they always have complex associations and are not independent. The intrusion detection algorithms for traditional industrial control systems often do not solve this problem, which results in a decrease in the accuracy, precision and high false negative rate (FNR), false positives rate (FPR). Aiming at solving the current problems, this paper proposes an algorithm combining the Fast Independent Principal Component Analysis (FastICA) and Support Vector Machine (SVM). Finally compared with the SVM and PCA-SVM algorithms, the experimental results show that the accuracy rate has been significantly improved and slight FPR. © 2021, Springer Nature Switzerland AG.

关键词： Intrusion detection

来源：评论

学校读者我要写书评

暂无评论

Preface

Mechanisms and Machine Science

引用

Mechanisms and Machine Science 2024年 167 MMS卷 v-vi页

作者： Tuleshov, Amandyk Ceccarelli, Marco Laboratory of Intelligent Robotics Systems Joldasbekov Institute of Mechanics and Engineering Almaty Kazakhstan Department of Industrial Engineering University of Rome Tor Vergata Rome Italy

来源：评论

学校读者我要写书评

暂无评论

A Shadowcasting-Based Next-Best-View Planner for Autonomous 3D Exploration

arXiv

引用

arXiv 2021年

作者： Batinovic, Ana Ivanovic, Antun Petrovic, Tamara Bogdan, Stjepan University of Zagreb Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems Unska 3 Zagreb10000 Croatia

—In this paper, we address the problem of autonomous exploration of unknown environments with an aerial robot equipped with a sensory set that produces large point clouds, such as LiDARs. The main goal is to gradually explore an area while planning paths and calculating information gain in short computation time, suitable for implementation on an on-board computer. To this end, we present a planner that randomly samples viewpoints in the environment map. It relies on a novel and efficient gain calculation based on the Recursive Shadowcasting algorithm. To determine the Next-Best-View (NBV), our planner uses a cuboid-based evaluation method that results in an enviably short computation time. To reduce the overall exploration time, we also use a dead end resolving strategy that allows us to quickly recover from dead ends in a challenging environment. Comparative experiments in simulation have shown that our approach outperforms the current state-of-the-art in terms of computational efficiency and total exploration time. The video of our approach can be found at https://***/playlist?list=PLC0C6uwoEQ8ZDhny1V dmFXLeTQOSBibQl. © 2021, CC BY-SA.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Sim2Air - Synthetic Aerial Dataset for UAV Monitoring

arXiv

引用

arXiv 2021年

作者： Barisic, Antonella Petric, Frano Bogdan, Stjepan The University of Zagreb Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems Unska 3 Zagreb10000 Croatia

In this paper we propose a novel approach to generate a synthetic aerial dataset for application in UAV monitoring. We propose to accentuate shape-based object representation by applying texture randomization. A diverse dataset with photo-realism in all parameters such as shape, pose, lighting, scale, viewpoint, etc. except for atypical textures is created in a 3D modelling software Blender. Our approach specifically targets two conditions in aerial images where texture of objects is difficult to detect, namely challenging illumination and objects occupying only a small portion of the image. Experimental evaluation of YOLO and Faster R-CNN detectors trained on synthetic data with randomized textures confirmed our approach by increasing the mAP value (17 and 3.7 percentage points for YOLO;20 and 1.1 percentage points for Faster R-CNN) on two test datasets of real images, both containing UAV-to-UAV images with motion blur. Testing on different domains, we conclude that the more the generalisation ability is put to the test, the more apparent are the advantages of the shape-based representation. © 2021, CC BY-NC-SA.

关键词： robotics

来源：评论

学校读者我要写书评

暂无评论

Dynamics of a single free-settling spherical particle driven by a laser-induced bubble near a rigid boundary

引用

Physical Review Fluids 2021年第9期6卷 093602-093602页

作者： Shengji Wu Bo Li Zhigang Zuo Shuhong Liu State Key Laboratory of Hydroscience and Engineering and Department of Energy and Power Engineering Tsinghua University Beijing 100084 China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou 310027 China College of Robotics Beijing Union University Beijing 100020 China

In view of the mechanism of the enhanced cavitation erosion of hydraulic machinery operating in sand-laden water, we carry out a systematic investigation on the interaction between a laser-induced cavitation bubble and a free-settling spherical particle near a rigid boundary. We document different types of particle-bubble interactions and experimentally discover two important phenomena where the particle ends up impacting on the boundary at a relatively high velocity, driven by the explosive growth of the bubble and the microjet of the nonspherical bubble collapse respectively. By combining numerical and analytical analyses with experiments, we identify two limiting conditions of the particle-bubble bounce and the particle-boundary impact respectively in terms of the initial relative distance between the particle and the bubble, and the stand-off distance of the bubble against the boundary. These results provide guidance in controlling the particle-bubble dynamics in applications, such as alleviating cavitation erosions in sand-laden water, improving the efficiency of surface cleaning and drug delivery by cavitation and other means.

关键词： Cavitation Drops & bubbles Fluid-particle interactions

来源：评论

学校读者我要写书评

暂无评论

Adaptive-LIO: Enhancing Robustness and Precision through Environmental Adaptation in LiDAR Inertial Odometry

arXiv

引用

arXiv 2025年

作者： Zhao, Chengwei Hu, Kun Xu, Jie Zhao, Lijun Han, Baiwen Wu, Kaidi Tian, Maoshan Yuan, Shenghai The State Key Laboratory of Robotics and Systems Harbin Institute of Technology HeiLongJiang Harbin150001 China Hangzhou Qisheng Intelligent Techology Co. Ltd. 4083 Jianshe Fourth Road Zhejiang Hangzhou311217 China The School of Mechatronic Engineering China University of Mining and Technology JiangSu Xuzhou221116 China The School of Mechanical and Electrical Engineering University of Electronic Science And Technology Sichuan Chengdu611731 China The School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue 639798 Singapore

The emerging Internet of Things (IoT) applications, such as driverless cars, have a growing demand for high-precision positioning and navigation. Nowadays, LiDAR inertial odometry becomes increasingly prevalent in robotics and autonomous driving. However, many current SLAM systems lack sufficient adaptability to various scenarios. Challenges include decreased point cloud accuracy with longer frame intervals under the constant velocity assumption, coupling of erroneous IMU information when IMU saturation occurs, and decreased localization accuracy due to the use of fixed-resolution maps during indoor-outdoor scene transitions. To address these issues, we propose a loosely coupled adaptive LiDAR-Inertial-Odometry named Adaptive-LIO, which incorporates adaptive segmentation to enhance mapping accuracy, adapts motion modality through IMU saturation and fault detection, and adjusts map resolution adaptively using multi-resolution voxel maps based on the distance from the LiDAR center. Our proposed method has been tested in various challenging scenarios, demonstrating the effectiveness of the improvements we introduce. The code is open-source on GitHub: Adaptive-LIO. © 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

Model-Based Shape Estimation and Closed-Loop Control of Magnetic Continuum Robot Based on Monocular Vision

Model-Based Shape Estimation and Closed-Loop Control of Magn...

引用

IEEE International Conference on robotics and Biomimetics

作者： Junfeng Zhu Yuanrui Huang Jian Chen Hongbin Liu State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences (CASIA) Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Centre of AI and Robotics Hong Kong Institute of Science Innovation Chinese Academy of Sciences School of Biomedical Engineering and Imaging Sciences King's College London UK

ISBN: (数字)9798331509644

ISBN: (纸本)9798331509651

Magnetic continuum robots (MCRs) show promising potential for applications in narrow lumens, such as vascular interventions. Accurate shape sensing of these robots is crucial for the success of interventional surgeries. However, the submillimeter dimensions of MCRs poses significant challenges for integrating additional sensors. An alternative approach is shape estimation from images, yet the lack of precise MCR kinematics can make this process time-consuming. In this work, we propose a novel MCR design featuring a rectangular tip capable of specific planar bending, along with a corresponding kinematic model and a mechanical model. Additionally, we introduce a model-based shape estimation method that enables the estimation of the MCR's shape from a single-view image without the need for external markers. Experimental results demonstrate that our method can estimate an MCR's shape with a mean absolute error (MAE) of $\mathbf{0.58}\pm \mathbf{0.41}\mathbf{mm}$ within 85ms, facilitating real-time application. Furthermore, closed-loop control based on this method has achieved an end position error below 11% of the tip's total length, highlighting the accuracy and practicality of our approach for surgical interventions.

关键词： Solid modeling Shape Computational modeling Magnetic resonance imaging Estimation Kinematics Robot sensing systems Real-time systems Continuum robots Magnetosphere

来源：评论

学校读者我要写书评

暂无评论

Joint moment estimation for hip exoskeleton control: A generalized moment feature generation method

引用

Biomimetic Intelligence and robotics 2025年

作者： Yuanwen Zhang Jingfeng Xiong Haolan Xian Chuheng Chen Xinxing Chen Haipeng Liang Chenglong Fu Yuquan Leng State Key Laboratory of Robotics and Systems School of Biomedical Engineering Harbin Institute of Technology Shenzhen 518055 China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen 518055 China School of Engineering and Materials Science Queen Mary University of London London E1 4NS UK

Hip joint moments during walking are the key foundation for hip exoskeleton assistance control. Most recent studies have shown estimating hip joint moments instantaneously offers a lot of advantages compared to generating assistive torque profiles based on gait estimation, such as simple sensor requirements and adaptability to variable walking speeds. However, existing joint moment estimation methods still suffer from a lack of personalization, leading to estimation accuracy degradation for new users. To address the challenges, this paper proposes a hip joint moment estimation method based on generalized moment features (GMF). A GMF generator is constructed to learn GMF of the joint moment which is invariant to individual variations while remaining decodable into joint moments through a dedicated decoder. Utilizing this well-featured representation, a GRU-based neural network is used to predict GMF with joint kinematics data, which can easily be acquired by hip exoskeleton encoders. The proposed estimation method achieves a root mean square error of 0.1180 ± 0.0021 Nm/kg under 28 walking speed conditions on a treadmill dataset, improved by 6.5% compared to the model without body parameter fusion, and by 8.3% for the conventional fusion model with body parameter. Furthermore, the proposed method was employed on a hip exoskeleton with only encoder sensors and achieved an average 20.5% metabolic reduction ( p < 0 . 01 ) for users compared to assist-off condition in level-ground walking.

关键词： Lower-limb exoskeleton Hip joint moment estimation Deep learning

来源：评论

学校读者我要写书评

暂无评论

Multi-Robot System for Autonomous Cooperative Counter-UAS Missions: Design, Integration, and Field Testing

Multi-Robot System for Autonomous Cooperative Counter-UAS Mi...

引用

IEEE International Workshop on Safety, Security, and Rescue robotics (SSRR)

作者： Antonella Barisic Marlan Ball Noah Jackson Riley McCarthy Nasib Naimi Luca Strässle Jonathan Becker Maurice Brunner Julius Fricke Lovro Markovic Isaac Seslar David Novick Jonathan Salton Roland Siegwart Stjepan Bogdan Rafael Fierro Laboratory for Robotics and Intelligent Control Systems (LAR-ICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia Electrical and Computer Engineering Department University of New Mexico Albuquerque NM USA ETH Zurich Autonomous Systems Lab (ASL) Zurich Switzerland Sandia National Laboratories Albuquerque New Mexico USA

ISBN: (纸本)9781665456814

With the rapid development of technology and the proliferation of uncrewed aerial systems (UAS), there is an immediate need for security solutions. Toward this end, we propose the use of a multi-robot system for autonomous and cooperative counter-UAS missions. In this paper, we present the design of the hardware and software components of different complementary robotic platforms: a mobile uncrewed ground vehicle (UGV) equipped with a LiDAR sensor, an uncrewed aerial vehicle (UAV) with a gimbal-mounted stereo camera for air-to-air inspections, and a UAV with a capture mechanism equipped with radars and camera. Our proposed system features 1) scalability to larger areas due to the distributed approach and online processing, 2) long-term cooperative missions, and 3) complementary multimodal perception for the detection of multirotor UAVs. In field experiments, we demonstrate the integration of all subsystems in accomplishing a counter-UAS task within an unstructured environment. The obtained results confirm the promising direction of using multi-robot and multi-modal systems for C-UAS.

关键词： Scalability Robot vision systems Autonomous aerial vehicles Cameras Software Safety Security

来源：评论

学校读者我要写书评

暂无评论

Enhancing Force Sensing Capabilities in Exoskeleton Interfaces Using Compliant Actuator-Sensor Units - A User Study

Enhancing Force Sensing Capabilities in Exoskeleton Interfac...

引用

IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Hosam Alagi Nikola Fischer Kai Behrends Iris Ftirst-Walter Jürgen Becker Michael Beigl Franziska Mathis-Ullrich Björn Hein Intelligent Process Automation and Robotics Laboratory (IPR) Institute for Anthropomatics and Robotics (IAR) Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Institute of Telematics (TM) - Pervasive Computing Systems (TECO) at Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Institut fuer Technik der Informationsverarbeitung (ITIV) at Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Department Artificial Intelligence in Biomedical Engineering (AIBE) Friedrich-Alexander University Erlangen-Nürnberg (FAU) Erlangen Germany Karlsruhe University of Applied Sciences Karlsruhe Germany

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Reliable interaction force sensing between an exoskeleton and the human body is crucial for personalized support and efficient control. Poor donning and disturbances during movement lead to lower force measurement quality and thus to unfavorable use. In this work, we present an active smart human-robot interface by utilizing compliant actuator-sensor units (CASUs) that can be worn over clothing. These units combine capacitive force sensing and actuation using Shape-Memory Alloy (SMA) to actively compensate disturbances and improve force measurement by tightening the interface and reestablishing optimal contact. We present a pilot user study with five subjects, investigating the performance of an exoskele-ton interface featuring three integrated CASUs to compensate for non-ideal donning configurations and displacements during daily activities of walking, sitting down, and climbing the stairs. The results for a passive interface show a decrease in holding forces and force signal quality during activities. Our active interface, on the other hand, effectively compensates for disturbances, restoring high signal quality by the mean of peak-to-peak value up to 300% which leads to more distinct signals.

关键词： Legged locomotion Force measurement Cooling Force Exoskeletons Metals Stairs Robot sensing systems Sensors Reliability

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：