检索结果-内蒙古大学图书馆

Versatile Tasks on Integrated Aerial Platforms Using Only Onboard Sensors: Control, Estimation, and Validation

IEEE Transactions on Robotics 2025年 41卷 3518-3538页

作者： Wang, Kaidi Lai, Ganghua Yu, Yushu Du, Jianrui Sun, Jiali Xu, Bin Franchi, Antonio Sun, Fuchun Beijing Institute of Technology School of Mechatronical Engineering Beijing100081 China Beijing Institute of Technology School of Mechanical Engineering Beijing100081 China University of Twente Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics and Computer Science Enschede7500 AE Netherlands Tsinghua University Department of Computer Science and Technology China

Connecting multiple aerial vehicles to a rigid central platform through passive spherical joints holds the potential to construct a fully-actuated aerial platform. The integration of multiple vehicles enhances efficiency in tasks like mapping and object reconnaissance. This paper proposes a control and state estimation framework for the Integrated Aerial Platform (IAP), enabling it to perform versatile tasks like object reconnaissance and physical interactive tasks with only onboard sensors. In the framework, the 6D motion control serves as the low-level controller, while the high-level controller comprises a 6D admittance filter and a perception-aware attitude correction module. The 6D admittance filter, serving as the interaction controller, is adaptable for aerial interaction tasks. The perception-aware attitude correction algorithm is carefully designed by adopting a geometric Model Predictive Controller (MPC). This algorithm, incorporating both offline and online calculations, proves to be well-suited for the intricate dynamics of an IAP. A 6D direct wrench controller is also developed for the IAP. Notably, both the interaction controller and the direct wrench controller operate without reliance on force/torque sensors. Instead, a wrench observer algorithm is devised, considering external disturbances. Additionally, based on the kinematics constraints of the multiple aerials in the platform, a fusion algorithm for multiple Visual-Inertial Odometry (VIO) and kinematics constraints is developed, providing more accurate localization. A prototype of the IAP is constructed, and its capabilities are demonstrated through experiments including perception-aware object reconnaissance, aerial mapping, aerial peg-in-hole task, and 6D contact wrench generation. All experiments are conducted exclusively with onboard sensors. These tasks exemplify the merits of the proposed IAP and validate the effectiveness of the proposed control framework and fusion algorithm. © 2004-2012

关键词： State estimation

来源：评论

学校读者我要写书评

暂无评论

ACbot:an IIoT platform for industrial robots

引用

Frontiers of computer Science 2025年第4期19卷 13-27页

作者： Rui WANG Xudong MOU Tianyu WO Mingyang ZHANG Yuxin LIU Tiejun WANG Pin LIU Jihong YAN Xudong LIU School of Computer Science and Engineering Beihang UniversityBeijing 100191China Zhongguancun Laboratory Beijing 100194China School of Software Beihang UniversityBeijing 100191China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Engineering China University of GeosciencesBeijing 100083China

As the application of Industrial Robots(IRs)scales and related participants increase,the demands for intelligent Operation and Maintenance(O&M)and multi-tenant collaboration *** methods could no longer cover the requirements,while the Industrial Internet of Things(IIoT)has been considered a promising ***,there’s a lack of IIoT platforms dedicated to IR O&M,including IR maintenance,process optimization,and knowledge *** this context,this paper puts forward the multi-tenant-oriented ACbot platform,which attempts to provide the first holistic IIoT-based solution for O&M of *** on an information model designed for the IR field,ACbot has implemented an application architecture with resource and microservice management across the cloud and multiple *** this basis,we develop four vital applications including real-time monitoring,health management,process optimization,and knowledge *** have deployed the ACbot platform in real-world scenarios that contain various participants,types of IRs,and *** date,ACbot has been accessed by 10 organizations and managed 60 industrial robots,demonstrating that the platform fulfills our ***,the application results also showcase its robustness,versatility,and adaptability for developing and hosting intelligent robot applications.

关键词： IIoT platform industrial robots cloud-edge collaboration intelligent applications

来源：评论

学校读者我要写书评

暂无评论

DeepRice: A deep learning and deep feature based classification of Rice leaf disease subtypes

引用

Artificial Intelligence in Agriculture 2024年第1期11卷 34-49页

作者： P.Isaac Ritharson Kumudha Raimond X.Anitha Mary Jennifer Eunice Robert Andrew J Department of CSE Karunya Institute of Technology and Sciences CoimbatoreTamilnaduIndia Department of Robotics Engineering Karunya Institute of Technology and SciencesCoimbatoreIndia Department of Mechatronics Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipalKarnataka 576104India Department of Computer Science and Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipalKarnataka 576104India

Rice stands as a crucial staple food globally,with its enduring sustainability hinging on the prompt detection of rice leaf ***,efficiently detecting diseases when they have already occurred holds paramount importance for solving the cost of manual visual identification and chemical *** the recent past,the identification of leaf pathologies in crops predominantly relies on manual methods using specialized equipment,which proves to be time-consuming and *** study offers a remedy by harnessing Deep Learning(DL)and transfer learning techniques to accurately identify and classify rice leaf diseases.A comprehensive dataset comprising 5932 self-generated images of rice leaves was assembled along with the benchmark datasets,categorized into 9 classes irrespective of the extent of disease spread across the *** classes encompass diverse states including healthy leaves,mild and severe blight,mild and severe tungro,mild and severe blast,as well as mild and severe brown *** meticulous manual labelling and dataset segmentation,which was validated by horticulture experts,data augmentation strategies were implemented to amplify the number of *** datasets were subjected to evaluation using the proposed tailored Convolutional Neural Networks *** performance are scrutinized in conjunction with alternative transfer learning approaches like VGG16,Xception,ResNet50,DenseNet121,Inception ResnetV2,and Inception *** effectiveness of the proposed custom VGG16 model was gauged by its capacity to generalize to unseen images,yielding an exceptional accuracy of 99.94%,surpassing the benchmarks set by existing state-of-the-art ***,the layer wise feature extraction is also visualized as the interpretable AI.

关键词： Rice leaf disease Deep learning CNN Crop yield Agriculture Food security

来源：评论

学校读者我要写书评

暂无评论

FRCD: Future Ready Career-Duck a Machine Learning-Driven Career Guidance for Students

FRCD: Future Ready Career-Duck a Machine Learning-Driven Car...

引用

2024 IEEE Silchar Subsection Annual Conference, SILCON 2024

作者： Paritosh, Priyanshu Yadav, Vedant Gupta, Dev Biswas, Ujjwal Indian Institute of Information Technology Bhagalpur Department of Mechatronics and Automation Engineering Bhagalpur India Indian Institute of Information Technology Bhagalpur Department of Computer Science and Engineering Bhagalpur India

ISBN: (纸本)9798331540821

In today's society, finding a suitable career is crucial. High school students frequently need to fully understand the notion of labor due to a lack of experience and practical knowledge in various disciplines. This renders students particularly vulnerable to external influences while deciding on a career path. As a result, students must carefully consider high-paying careers to ensure that they align with their interests and skills. Otherwise, students may end up in jobs they dislike or are not suited to. In response to this issue, we intend to develop a machine-learning framework capable of predicting career pathways. Students will receive career recommendation from our model based on their performance and potential. Students can confidently follow their chosen fields if they do well academically;if not, they can choose to change to other fields that better suit them. There are challenges in determining the metrics and improving prediction accuracy to quantify students' career paths and performance in teaching-learning. Best on the test results, the proposed model has a higher prediction accuracy. Also, this method is both reliable and portable, and it may be used to predict career paths in real time. © 2024 IEEE.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

Design and fabrication of a mobile robot for weed removal applications in agricultural fields 3

Design and fabrication of a mobile robot for weed removal ap...

引用

3rd International Conference on Artificial Intelligence For Internet of Things, AIIoT 2024

作者： Natesan, Nandan Arunkumar, V. Sathiyavathi, S. Kalaiarassan, G. Vellore Institute of Technology School of Computer Science and Engineering Chennai India Kongu Engineering College Perundurai Department of Mechatronics Engineering Erode India Vellore Institute of Technology School of Mechanical Engineering Vellore India

ISBN: (纸本)9798350372120

Agriculture is one of the most important aspects across the globe which is also a primary task for any country to lead their economic growth and to be a healthy country. The objective of agriculture is to produce various food materials, vegetables and fruits as an outcome of the process. But to provide the outcome from agriculture is not as simple as it looks, Farmers face many issues while making the outcome and they need to work separately to overcome this problem. One of the issues faced by the farmer is the weed management. Weed Management is that the method of dominant that the expansion and removal of the weeds in timely manner. The weeds present in the fields have a major impact on the farmers in terms of their reduction in yield and loss in the capital income. In all recent surveys, it is stated that Weeds present in the field causes almost 60 to 75 percentage loss in agriculture. In order to solve this problem and to give a tentative visioned solution, this project focuses on the development of a mobile robot which can identify the weeds in the field while traversing the field and also capable of differentiating the weeds with crops and other small plants and after the identification, weeds are removed by the weed remover. Apart from removing the weeds this project can also give the small summary of the traversed agricultural land. © 2024 IEEE.

关键词： Machine design

来源：评论

学校读者我要写书评

暂无评论

Robot assisted knee joint RoM exercise: A PID parallel compensator architecture through impedance estimation

引用

Cognitive Robotics 2024年第1期4卷 42-61页

作者： Akhtaruzzaman, M. Shafie, Amir A. Khan, Md Raisuddin Rahman, Md Mozasser Department of Computer Science and Engineering Military Institute of Science and Technology 1216 Dhaka Bangladesh Department of Mechatronics Engineering International Islamic University Malaysia Kuala Lumpur53100 Malaysia Faculty of Engineering Technology Universiti Tun Hussein Onn Malaysia 86400 Johor Malaysia

Knee joint rehabilitation exercise refers to a therapeutic procedure of a patient having dysfunctions in certain abilities to move knee joint due to some medical conditions like trauma or paralysis. The exercise is basically a series of repeated assistive physical movements within the range of motion (RoM) of the joint. Reflex action of limbs during RoM exercise causes inappropriate balance of load which may cause secondary injuries, such as damages of muscle or tendon tissues. Establishing correlation between impedance data and limb motions is important to solve this problem. This paper aims to design and modeling of a robotic arm with an original approach in control strategy which is developed based on the correlation in between the joint-impedances and joint-motion characteristics during exercise. The knee joint impedances are estimated based on the internal feedback of the system dynamics, that lead to design the torque compensator to improve the overall control signals in real time. This paper also demonstrates the characteristics of various responses of the system during exercise with human subject. Results have reflected good performances with low position and velocity tracking errors, ±0.02∘ and ***−1 during hold phase;and ±0.14∘ and ***−1 during motion phse. Though, the limitation of the prototype is its current RoM (limited to 0∘–25∘), the system has potential in the application of RoM exercise for paraplegic or monoplegic patients. © 2023

关键词： Human robot interaction

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Approach to Stock Trend Forecasting using CNNs with Technical Indicators 3

A Deep Learning Approach to Stock Trend Forecasting using CN...

引用

3rd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Yuvaraj, S. Chenni Kumaran, J. Bharathiraja, M. Krishna Kumar, K. Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University TamilNadu Chennai India Department of Mechatronics Engineering Bannari Amman Institute of Technology Tamil Nadu Sathyamangalam India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527549

The approach encompassed under this model introduces stock trend forecasting using a new approach that involves Convolutional Neural Networks (CNNs) supplemented with technical indicators like the Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), and Relative Strength Index (RSI). This study reacts to the limitations of traditional methods like ARIMA and GARCH due to their shortcomings with non-linear dependence on stock data. The robust solution for trend prediction closely follows the hierarchical learning of CNN. This model attains a remarkable accuracy of 99% in stock trend prediction using Convolutional Neural Networks, fine-tuning crucial but elaborate patterns for stock price movements. The forecast results categorize stock trends as Neutral, Bullish, and Bearish, with validation shown from high precision, recall, and F1-scores computed from complete classification reports and confusion matrices. The capability of forecasting provides tremendous assistance in making informed investment decisions. These results prove that CNNs more efficiently predict stocks if combined with technical analysis and give portions of insight to traders. This study shows the capacity to apply various deep learning techniques in finance to enhance stock trend predictions and shape on-the-ground investment strategies. The study fills an existing gap in research with the introduction of combining CNN with technical indicators in the prediction models for improvement with predictive power and accuracy. © 2025 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

引用

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

来源：评论

学校读者我要写书评

暂无评论

IoT data cleaning techniques: A survey

引用

Intelligent and Converged Networks 2022年第4期3卷 325-339页

作者： Xiaoou Ding Hongzhi Wang Genglong Li Haoxuan Li Yingze Li Yida Liu School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China School of Mechatronics Engineering Harbin Institute of TechnologyHarbin 150001China

Data cleaning is considered as an effective approach of improving data quality in order to help practitioners and researchers be devoted to downstream analysis and decision-making without worrying about data *** paper provides a systematic summary of the two main stages of data cleaning for Internet of Things(IoT)data with time series characteristics,including error data detection and data *** respect to error data detection techniques,it categorizes an overview of quantitative data error detection methods for detecting single-point errors,continuous errors,and multidimensional time series data errors and qualitative data error detection methods for detecting rule-violating ***,it provides a detailed description of error data repairing techniques,involving statistics-based repairing,rule-based repairing,and human-involved *** review the strengths and the limitations of the current data cleaning techniques under IoT data applications and conclude with an outlook on the future of IoT data cleaning.

关键词： Internet of Things(IoT) data quality data cleaning error detection data repairing

来源：评论

学校读者我要写书评

暂无评论

Web Based Lidar Point Cloud Visualization and Teleoperation Tool for Robots 14

Web Based Lidar Point Cloud Visualization and Teleoperation ...

引用

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

作者： Nukala, Suraj Sugaya, Midori Nagarajan, Seenu Hindustan Institute of Technology and Science Department of Mechatronics Engineering Tamil Nadu Chennai603103 India Shibaura Institute of Technology Department of Computer Science Tokyo135-8548 Japan Department of Mechatronics Engineering Tamil Nadu 603103 India

ISBN: (纸本)9798350335095

This paper presents the development of a teleoperation system designed for remote control of a ROS robot over the internet. While existing visualization tools like rvis are limited to the host system or local area network, this system aims to overcome those constraints. The system's primary objectives are remote motor control and lidar data visualization using point cloud and camera data, and it is compatible with any ROS system, tested with ROS2 *** system meets the following requirements:*** ability to work over the *** ability to visualize lidar and camera *** ability to control *** achieve this, the system relies heavily on ROSBridge, which is a ROS node that exposes ROS communication channels such as topics, services, and activities out to the internet using websockets. This enables any client to subscribe and publish data to and from the ROS communication *** user interface of envious incorporates various interactive elements, including the camera feed, motor controllers, and lidar data visualization. These components are implemented using roslibjs, react, and react three fiber, which leverages webgl and threejs libraries to create an abstraction layer for seamless integration with the web *** leveraging ROSBridge and modern web technologies, the proposed system offers the ability to control motors and visualize lidar and camera data remotely over the internet. It provides a user-friendly interface for interacting with the ROS system, facilitating teleoperation of robots from any location with an internet connection. This system expands the capabilities of ROS beyond local networks, opening up new possibilities for remote robotics applications and *** the capabilities of this system would opens up a world of exciting applications, one of which is a swarm mapping system that takes leverage of multiple interconnected robots to collaboratively map and explore an area © 2023 IEEE.

关键词： Remote control

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：