检索结果-内蒙古大学图书馆

arXiv 2024年

作者： Nguyen, Khang Dang, Tuan Huber, Manfred The Learning and Adaptive Robotics Laboratory Department of Computer Science and Engineering University of Texas at Arlington ArlingtonTX76013 United States

Perceiving a three-dimensional (3D) scene with multiple objects while moving indoors is essential for vision-based mobile cobots, especially for enhancing their manipulation tasks. In this work, we present an end-to-end pipeline with instance segmentation, feature matching, and point-set registration for egocentric robots with binocular vision and demonstrate the robot’s grasping capability through the proposed pipeline. First, we design an RGB image-based segmentation approach for single-view 3D semantic scene segmentation, leveraging common object classes in 2D datasets to encapsulate 3D points into point clouds of object instances through corresponding depth maps. Next, 3D correspondences of two consecutive segmented point clouds are extracted based on matched keypoints between objects of interest in RGB images from the prior step. In addition, to be aware of spatial changes in 3D feature distribution, we also weigh each 3D point pair based on the estimated distribution using kernel density estimation (KDE), which subsequently gives robustness with less central correspondences while solving for rigid transformations between point clouds. Finally, we test our proposed pipeline on the 7-DOF dual-arm Baxter robot with a mounted Intel RealSense D435i RGB-D camera. The result shows that our robot can segment objects of interest, register multiple views while moving, and grasp the target object. The source code is available at https://***/mkhangg/semantic scene perception. Copyright © 2024, The Authors. All rights reserved.

关键词： Pipelines

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition from Occluded Facial Images Using Deep Ensemble Model

引用

computers, Materials & Continua 2022年第12期73卷 4465-4487页

作者： Zia Ullah Muhammad Ismail Mohmand Sadaqat ur Rehman Muhammad Zubair Maha Driss Wadii Boulila Rayan Sheikh Ibrahim Alwawi Department of Computer Science The Brains InstitutePeshawar25000Pakistan School of Natural and Computing Sciences University of AberdeenAberdeenUK Department of Neurosciences KU Leuven Medical SchoolLeuven3000Belgium Security Engineering Laboratory CCISPrince Sultan UniversityRiyadh12435Saudi Arabia Robotics and Internet of Things Lab Prince Sultan UniversityRiyadh12435Saudi Arabia Department of Computer Science Robert Gordon UniversityAberdeenUK

Facial expression recognition has been a hot topic for decades,but high intraclass variation makes it *** overcome intraclass variation for visual recognition,we introduce a novel fusion methodology,in which the proposed model first extract features followed by feature ***,RestNet-50,VGG-19,and Inception-V3 is used to ensure feature learning followed by feature ***,the three feature extraction models are utilized using Ensemble Learning techniques for final expression *** representation learnt by the proposed methodology is robust to occlusions and pose variations and offers promising *** evaluate the efficiency of the proposed model,we use two wild benchmark datasets Real-world Affective Faces Database(RAF-DB)and AffectNet for facial expression *** proposed model classifies the emotions into seven different categories namely:happiness,anger,fear,disgust,sadness,surprise,and ***,the performance of the proposed model is also compared with other algorithms focusing on the analysis of computational cost,convergence and accuracy based on a standard problem specific to classification applications.

关键词： Ensemble learning emotion recognition feature fusion occlusion

来源：评论

学校读者我要写书评

暂无评论

High-precision Calibration of Camera and IMU on Manipulator for Bio-inspired Robotic System

引用

Journal of Bionic Engineering 2022年第2期19卷 299-313页

作者： Yinlong Zhang Wei Liang Sichao Zhang Xudong Yuan Xiaofang Xia Jindong Tan Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China The School of Computer Science and Technology Xidian UniversityXi’an 710071China Department of Mechanical Aerospace and Biomedical EngineeringUniversity of TennesseeKonxville 37996USA Department of Automation Technology ABB Corporate Research Sweden72178 VästerasSweden

Inspired by box jellyfish that has distributed and complementary perceptive system,we seek to equip manipulator with a camera and an Inertial Measurement Unit(IMU)to perceive ego motion and surrounding unstructured *** robot perception,a reliable and high-precision calibration between camera,IMU and manipulator is a critical *** paper introduces a novel calibration ***,we seek to correlate the spatial relationship between the sensing units and manipulator in a joint ***,the manipulator moving trajectory is elaborately designed in a spiral pattern that enables full excitations on yaw-pitch-roll rotations and x-y-z translations in a repeatable and consistent *** calibration has been evaluated on our collected visual inertial-manipulator *** systematic comparisons and analysis indicate the consistency,precision and effectiveness of our proposed calibration method.

关键词： Bio-inspired robotic system Monocular camera IMU Manipulator Calibration

来源：评论

学校读者我要写书评

暂无评论

Semi-Autonomous Assistance for Telesurgery Under Communication Loss

Semi-Autonomous Assistance for Telesurgery Under Communicati...

引用

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

作者： Hisashi Ishida Adnan Munawar Russell H. Taylor Peter Kazanzides Computer Science department Laboratory for Computational Sensing and Robotics Johns Hopkins University Baltimore Maryland USA

Telesurgery has a clear potential for providing high-quality surgery to medically underserved areas like rural areas, battlefields, and spacecraft; nevertheless, effective methods to overcome unreliable communication systems are still lacking. Furthermore, it is not well understood how users react at the moment of communication loss and also during the loss. In this paper, we aim to analyze human response by proposing a telesurgery simulation framework that models an environment incorporating local and remote sites. Furthermore, this framework generates structural data for human behavior analysis and can provide different forms of assistance during the communication failure and at the communication recovery. We investigated three different types of assistance: User-centered, Robot-centered and Hybrid. A 12-person user-study was carried out using the proposed telesurgery simulation where participants completed a peg transfer task with random communication loss. The collected data was used to analyze the human response to a communication failure. The proposed Hybrid method reduced temporal demand with no increase in completion time compared to the baseline control method where users were unable to move the input device during the communication loss. The Hybrid method also significantly reduced both the task completion time and workload compared to the other two proposed methods (User-centered and Robot-centered).

关键词：

来源：评论

学校读者我要写书评

暂无评论

Inverse Kinematics of Robotic Manipulators Using a New Learning-by-Example Method

Inverse Kinematics of Robotic Manipulators Using a New Learn...

引用

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

作者： Jacket Demby’s Ramy Farag Guilherme N. DeSouza Department of Electrical Engineering and Computer Science (EECS) Vision-Guided and Intelligent Robotics (ViGIR) Laboratory University of Missouri-Columbia Columbia Missouri

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Inverse Kinematics (IK) is one of the most fundamental challenges in robotics. It refers to the process of determining the joint configurations required to achieve the desired position and orientation (pose) of a robot end-effector. Although numerous Data-Driven (DD) IK solvers have demonstrated encouraging results, they have not achieved the same accuracy when compared to other IK methods for complex robot configurations (e.g., numerical methods for higher Degrees of Freedom (DoF)). In this work, we propose a new Learning-by-Example method, and show that such a scheme considerably improves the IK learning results when compared to other DD learners. In our approach, the network input incorporates an example of joint-pose pair along with the query pose to predict the desired robot joint configuration. We show that the example joint-pose pair does not need to be too close to the query – i.e. example and query can be as far as 20 degrees apart in the joint configuration space. Furthermore, we investigate the utilization of residual and dense skip connections in Multilayer Perceptron for DDIK solvers and employ the resulting networks for two redundant robotic manipulators: a 7-DoF-7R commensurate robot and a 7DoF-2RP4R incommensurate robot. Our experimental results show that the resulting DDIK solver can reliably predict IK solutions with accuracy better than 1mm in position and 1deg in orientation.

关键词： Hands Accuracy Kinematics Network architecture Multilayer perceptrons Numerical models Reliability Collision avoidance Robots Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

Toward Lung Ultrasound Automation: Fully Autonomous Robotic Longitudinal and Transverse Scans Along Intercostal Spaces

IEEE Transactions on Medical Robotics and Bionics

引用

IEEE Transactions on Medical robotics and Bionics 2025年第2期7卷 768-781页

作者： Lei, Long Hu, Yingbai Jiang, Zixing Miao, Juzheng Luo, Xiao Zhang, Yu Wang, Qiong Wang, Shujun Li, Zheng Heng, Pheng-Ann The Chinese University of Hong Kong Department of Computer Science and Engineering Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China The Chinese University of Hong Kong Multi-Scale Medical Robotics Centre Ltd. Hong Kong The Chinese University of Hong Kong Department of Surgery Hong Kong Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen518055 China The Hong Kong Polytechnic University Department of Biomedical Engineering Hong Kong Chow Yuk Ho Technology Centre for Innovative Medicine Li Ka Shing Institute of Health Sciences Multiscale Medical Robotics Centre Ltd. The Chinese University of Hong Kong Department of Surgery Hong Kong

Lung ultrasound scanning is essential for diagnosing lung diseases. The scan effectiveness critically depends on both longitudinal and transverse scans through intercostal spaces to reduce rib shadowing interference, as well as maintaining the probe perpendicular to pleura for pathological artifact generation. Achieving this level of scan quality often depends heavily on the experience of doctors. Robotic ultrasound scanning shows promise, but currently lacks a direct path planning method for intercostal scanning, and probe orientation does not consider imaging differences between lungs and solid organs. In this paper, we aim to fully automate two fundamental operations in lung ultrasound scanning: longitudinal and transverse scans. We propose pioneering path planning methods along intercostal spaces and innovative solutions for adaptive probe posture adjustment using real-time pleural line feedback, specifically addressing the unique characteristics of lung ultrasound scanning. This ensures the acquisition of high-quality, diagnostically meaningful ultrasound images. In addition, we develop a robotic lung ultrasound system to validate the proposed methods. Extensive experimental results on two volunteers and a chest phantom confirm the efficacy of our methods, and demonstrate the system's feasibility in automated lung ultrasound examinations. Our work lays a solid foundation for automated robotic complete lung scanning. © 2018 IEEE.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Emotion Recognition Through EEG Signals With Movie Clips Stimuli

Emotion Recognition Through EEG Signals With Movie Clips Sti...

引用

Electrics and computer (INTCEC), Interdisciplinary Conference on

作者： Jonathan Axel Cruz Vazquez Jesús Yaljá Montiel Pérez Rodolfo Romero Herrera Robotics and mechatronics laboratory IPN – CIC CDMX México Department of Computer Science and Engineering IPN – ESCOM CDMX México

ISBN: (数字)9798350349450

ISBN: (纸本)9798350349467

This study proposes a multimodal emotion recognition method acquiring electroencephalogram (EEG) data and using movie clips to express emotional stimuli. The study included 12 participants who aimed to identify three emotions: happy, sad, and neutral. For the experiments, the Emotiv Epoc+ device was used for data collection, including data preprocessing, time and frequency domain feature extraction, and classification. Emotion recognition uses different machine learning algorithms, including support vector machines (SVM), k-nearest neighbors (k-NN), random forests, and neural networks. The algorithm is trained and evaluated using feature vectors extracted from participants' emotional responses to movie videos. This method achieves a competitive accuracy of 79.09% using an SVM(POL) classifier and features including time and frequency domains.

关键词： Support vector machines Emotion recognition Visualization Accuracy Machine learning algorithms Frequency-domain analysis Feature extraction

来源：评论

学校读者我要写书评

暂无评论

An Isomerism Learning Model to Solve Time-Varying Problems Through Intelligent Collaboration

引用

IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng Wang Bob Zhang Leyuan Fang Haisheng Li the Department of Computer and Information Science University of MacaoMacao 999078China the School of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518000 China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

来源：评论

学校读者我要写书评

暂无评论

Automatic speaker identification system based on MLP network and deep learning in the presence of severe interference

引用

Multimedia Tools and Applications 2025年 1-42页

作者： Shafik, Amira Sedik, Ahmed El-Shafai, Walid Khalaf, Ashraf A. M. El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electrical Engineering Faculty of Engineering Minia University Minia61519 Egypt Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafr Elsheikh University Kafr El‑Shaikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Automatic Speaker Identification (ASI) is so crucial for security. Current ASI systems perform well in quiet and clean surroundings. However, in noisy situations, the robustness of an ASI system against additive noise and interference is a crucial factor. An investigation of the impact of interference on ASI system performance is presented in this paper, which introduces algorithms for achieving high ASI system performance. The objective is to resist the interference of various forms. This paper presents two models for the ASI task in the presence of interference. The first one depends on Normalized Pitch Frequency (NPF) and Mel-Frequency Cepstral Coefficients (MFCCs) as extracted features and Multi-Layer Perceptron (MLP) as a classifier. In this model, we investigate the utilization of a Discrete Transform (DT), such as Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST), to increase the robustness of extracted features against different types of degradation through exploiting the sub-band decomposition characteristics of DWT and the energy compaction property of DCT and DST. This is achieved by extracting features directly from contaminated speech signals in addition to features extracted from discrete transformed signals to create hybrid feature vectors. The enhancement techniques, such as Spectral Subtraction (SS), Winer Filter, and adaptive Wiener filter, are used in a preprocessing stage to eliminate the effect of the interference on the ASI system. In the second model, we investigate the utilization of Deep Learning (DL) based on a Convolutional Neural Network (CNN) with speech signal spectrograms and their Radon transforms to increase the robustness of the ASI system against interference effects. One of this paper goals is to introduce a comparison between the two models and build a more robust ASI system against severe interference. The experimental results indicate that the two proposed models lead to satisfa

关键词： Additive noise

来源：评论

学校读者我要写书评

暂无评论

Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells 32

Application of Deep Learning Method to Estimate Bottomhole P...

引用

32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Cheng, Haibo Li, Shichao Zeng, Peng Vyatkin, Valeriy State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Luleå University of Technology Electrical and Space Engineering Department of Computer Science Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350399714

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry. © 2023 IEEE.

关键词： Long short-term memory

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：