检索结果-内蒙古大学图书馆

IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Essia Added Hassène Gritli Safya Belghith Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis University of Tunis El Manar Tunis Tunisia Higher Institute of Information and Communication Technologies University of Carthage Tunis Tunisia RISC Lab (LR16ES07) National Engineering School of Tunis University of Tunis El Manar

The compass-like bipedal walker is described as an impulsive hybrid nonlinear system and is characterized by a passive gait while descending an inclined surface. To study its passive bipedal gait, an identification of the one-periodic walk should be first carried out using the Poincaré map. Moreover, bifurcation diagrams are generally employed to investigate the steady gaits of such passive gait by varying the slope angle or other parameters, and hence to confirm the display of unexpected occurrences like chaos and bifurcations. In this work, to further analyze these complex phenomena, we employ, along with the bifurcation diagrams, the Lyapunov exponents by varying the slope angle and the lower-leg segment length. Thus, we demonstrate and confirm the presence of quasi-periodic gaits and hence the exhibition of the Neimark-Sacker bifurcation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Modelling the Dependence of Chlorophyll Leaf-Clip Measures on Vegetation Indices Derived from Multispectral UAS Images in Vineyards Parcels

Modelling the Dependence of Chlorophyll Leaf-Clip Measures o...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gil Gonçalves Umberto Andriolo Lúcio Paiva Cristiano Premebida António Ferraz Department of Mathematics University of Coimbra Coimbra Portugal Department of Electrical and Computer Engineering INESC Coimbra Coimbra Portugal Research Centre for Natural Resources Environment and Society Polytechnic Institute of Coimbra Coimbra Agrarian Technical School Coimbra Portugal Department of Electrical and Computer Engineering Institute of Systems and Robotics University of Coimbra Coimbra Portugal NASA Jet Propulsion Laboratory Pasadena United States

Multispectral images and leaf-clip measurements were used for evaluating the Chlorophyll (Chl) content on grapevine leaves through the use of vegetation indices. The multispectral leaf images were taken by a sensor onboard an UAS, which was placed over a table at a height of 70 cm. Images were radiometrically and geometrically processed to obtain accurate coregistered five band image stacks. Using a Kmeans segmentation, each leaf imaged in a multispectral image was automatically detected and the mean leaf reflectance values were used to compute three vegetation indices: NDVI, NDRE, and GLI. When compared to leaf-clip measurements, the results indicated that the NDRE index was the best predictor of Chl leaf content (R2=0.81). The obtained NDRE regression model can be used in UAS-based multispectral orthomosaics to generate canopy Chl maps at vine-row scale, which can assist vine growers in monitoring the spatial and temporal variability of grapevine vigor.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimization of Flexible Bronchoscopy Shape Sensing Using Fiber Optic Sensors

Optimization of Flexible Bronchoscopy Shape Sensing Using Fi...

引用

IEEE International Conference on robotics and Automation (ICRA)

作者： Xinran Liu Hao Chen Hongbin Liu School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Professor at Chinese Academy of Sciences Institute of Automation (CASIA) Executive Director for the Centre of AI and Robotics (CAIR) Hong Kong Institute of Science & Innovation Chinese Academy of Sciences An Adjunct Reader and Director of the Haptic Mechatronics and Medical Robotics (HaMMeR) lab at the School of Biomedical Engineering and Imaging Sciences King’s College London (KCL) UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This work presents a novel shape evaluation and optimization approach for shape sensing, specifically targeting the constrained, irregular, and intricate spatial shapes of flexible bronchoscopes (FB) in human bronchial tree. The proposed evaluation criteria and optimization methods combine clinical significance related to bronchial anatomical structures and address issues related to singular points and discontinuities in traditional shape reconstruction models. Three-dimensional experiments were conducted within eight spatial complex configurations printed from a proportional bronchial model. The 3D experiment results demonstrate an average reduction of approximately 34.1% in shape reconstruction errors across all eight airway models compared to the traditional model, validating the effectiveness and feasibility.

关键词： Bronchoscopy Solid modeling Optical fiber sensors Three-dimensional displays Shape Atmospheric modeling Optimization methods

来源：评论

学校读者我要写书评

暂无评论

Development of Bath Auxiliary Robot for the Disabled Elderly

Development of Bath Auxiliary Robot for the Disabled Elderly

引用

IEEE International Conference on Intelligence and Safety for robotics (ISR)

作者： Weibo Wang Ya Chen Xiaofeng Zou Shuoyu Wang João Paulo Ferreira Tao Liu State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China Kochi University of Technology Kochi Japan Coimbra Institute of Engineering Institute of Systems and Robotics of Coimbra Portugal

The rapid aging of the population has put huge pressure on social nursing work. As an important part of elderly care, bathing can remove sweat and oil, relax muscles, promote blood circulation and improve skin's metabolic function and disease resistance, which is related to the physical and mental health of the elderly. In this paper, a set of intelligent bath care system for the elderly is introduced. The system automatically showers, mops, dries the elderly and alarms for abnormal physical conditions. Moreover, bathing parameters such as bath water temperature, scrubbing frequency and speed, drying temperature and wind speed can be set according to the different preferences and physical conditions of the elderly. It realizes the exchange of information among the elderly, equipment and nursing staff, with good cleaning effect and high degree of automation.

关键词： Resistance Wind speed Oils Senior citizens Sociology Medical services Skin

来源：评论

学校读者我要写书评

暂无评论

Control-Oriented Modeling of a Soft Manipulator Using the Learning-Based Koopman Operator

Control-Oriented Modeling of a Soft Manipulator Using the Le...

引用

International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Jie Chen Yu Dang Weiguang Huo Ningbo Yu Jianda Han College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Modeling the dynamics of soft manipulators remains challenging owing to their intrinsic compliance and nonlinear deformation. The Koopman operator theory provides a way to construct control-oriented linear models for soft robots. However, the modeling accuracy of the Koopman operator heavily depends on the choices of the eigenfunctions. In this paper, we propose a data-driven modeling framework for the soft manipulator using the learning-based Koopman operator (LKO). Distinct from the classical Koopman operator, the LKO leverages a neural network to discover the representations of the Koopman operator and the eigenfunctions. In this way, the LKO avoids the manual selection of eigenfunctions, enabling the identification of linear models with higher accuracy than that of the classical Koopman operator. The LKO was examined to predict the tip position and the configuration of a customized soft manipulator. Moreover, the LKO was compared with three conventional data-driven approaches, including the classical Koopman operator, feedforward neural network, and recurrent neural network. The results indicate that the modeling accuracy of the LKO was improved by over 60% compared with that of the other three conventional data-driven approaches. With the linear representation and high accuracy, the LKO has great potential to improve the model-based control performance of soft robots.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Functional Connectivity Analysis Revealed Abnormal Brain Network Pattern in Parkinson's Disease with Freezing of Gait

Functional Connectivity Analysis Revealed Abnormal Brain Net...

引用

Chinese Control Conference (CCC)

作者： Zhilin Shu Jinrui Liu Ting Song Jianda Han Ningbo Yu College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Patients with Parkinson's disease (PD) commonly have deficits in lower-limb movements. Freezing of gait (FOG), a type of gait disturbance of PD, is a complex motor symptom exhibited as inability to generate an effective gait. The mechanism of lower-limb dysfunction of PD, especially FOG, remains to be explored. To investigate the neural mechanisms related to FOG in PD, we evaluated 39 subjects (13 PD patients with FOG, 13 PD patients without FOG, and 13 healthy subjects) based on electroencephalogram (EEG) signals while they performed the pedaling task. We conducted functional connectivity analysis using Magnitude Squared Coherence (MSC) and calculated the metrics to investigate the characteristics of the brain network among the three groups. The results indicated that PD patients were associated with reduced functional integration and segregation of brain network, subserving both motor and cognitive abilities. The reduced functional integration and segregation of cognitive processes were correlated with the severity of FOG. This study revealed the differences in brain networks between PD patients and healthy controls and provided insights into the neural mechanism of FOG.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A New Scheme for Cooperative Hunting Tasks with Multiple Targets in Dynamic Environments

A New Scheme for Cooperative Hunting Tasks with Multiple Tar...

引用

IEEE International Conference on robotics and Biomimetics

作者： Ruikun Hu Ning Tan Fenglei Ni School of Computer Science and Engineering Sun Yatsen University Guangzhou PR China State Key Laboratory of Robotics and Systems (HIT) Harbin PR China

ISBN: (纸本)9781665405362

Multiple robot cooperation has been playing more and more significant role in scientific and engineering applications. The cooperative hunting task with multiple targets is a critical issue in multiple robot problem. To successfully hunt multiple preys, predator robots not only need to settle the problem on how to cooperatively hunt a prey, but also find an efficient task allocation to assign each predator to hunt certain prey. This paper proposes a cooperative hunting scheme based on the multi-target k-winner-take-all (k-WTA) algorithm and the wolf-pack-particle-based model. Based on the competitive mechanism, the multi-target k-WTA algorithm is used for task allocation with an optimized hunting strategy and achieves the allocation within a short period of time in dynamic environments. With simple rules, the wolf-pack-particle-based model can trigger collective behaviors and enable predator robots to encircle the prey. The simulative experiment results show that the proposed approach is capable of efficient task allocation and guiding predator robots to round up multiple moving targets in dynamic environments.

关键词： Costs Heuristic algorithms Conferences Biomimetics Force Dynamic scheduling Resource management

来源：评论

学校读者我要写书评

暂无评论

Provably Convergent Federated Trilevel Learning

arXiv

引用

arXiv 2023年

作者： Jiao, Yang Yang, Kai Wu, Tiancheng Jian, Chengtao Huang, Jianwei Department of Computer Science and Technology Tongji University China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University China Shanghai Research Institute for Intelligent Autonomous Systems China School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society China

Trilevel learning, also called trilevel optimization (TLO), has been recognized as a powerful modelling tool for hierarchical decision process and widely applied in many machine learning applications, such as robust neural architecture search, hyperparameter optimization, and domain adaptation. Tackling TLO problems has presented a great challenge due to their nested decision-making structure. In addition, existing works on TLO face the following key challenges: 1) they all focus on the non-distributed setting, which may lead to privacy breach;2) they do not offer any non-asymptotic convergence analysis which characterizes how fast an algorithm converges. To address the aforementioned challenges, this paper proposes an asynchronous federated trilevel optimization method to solve TLO problems. The proposed method utilizes µ-cuts to construct a hyper-polyhedral approximation for the TLO problem and solve it in an asynchronous manner. We demonstrate that the proposed µ-cuts are applicable to not only convex functions but also a wide range of non-convex functions that meet the µ-weakly convex assumption. Furthermore, we theoretically analyze the non-asymptotic convergence rate for the proposed method by showing its iteration complexity to obtain ϵ-stationary point is upper bounded by (Formula Presented). Extensive experiments on real-world datasets have been conducted to elucidate the superiority of the proposed method, e.g., it has a faster convergence rate with a maximum acceleration of approximately 80%. Copyright © 2023, The Authors. All rights reserved.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Leveraging Machine Learning for Gait Phase Classification with Varied Training Methods

Leveraging Machine Learning for Gait Phase Classification wi...

引用

International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)

作者： Amal Mekni Jyotindra Narayan Hassène Gritli Higher Institute of Information and Communication Technologies University of Carthage RISC Laboratory (LR16ES07) Borj Cedria Tunis Tunisia Department of Computing Imperial College London UK Chair of Digital Health Universität Bayreuth Germany Laboratory of Robotics Informatics and Complex Systems (RISC Lab - LR16ES07) National Engineering School of Tunis University of Tunis El Manar Le Belvédère Tunis Tunisia

ISBN: (数字)9798350351484

ISBN: (纸本)9798350351491

Accurate gait phase recognition is crucial for real-time analysis and intervention in rehabilitation, biomechanics, and prosthetics. However, achieving this is challenging due to the diverse machine learning (ML) training methods. This study employs ML algorithms to classify gait phases, focusing on stance and swing phases, utilizing open-source data from $\mathbf{1 0 0}$ participants ($41.91 \pm 5.3$ yrs). The classification algorithms considered are k-Nearest Neighbor (k-NN), Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Naive Bayesian (NB) algorithms. The study evaluates these algorithm performances using two training methods with five and ten lower body movements: one randomly selects $80 \%$ of stance and swing phase data for training, while the other divides data by participants, allocating $80 \%$ for training and $20 \%$ for testing. When assessing accuracy with five movements, RF achieved $99.8 \%$ for both training methods. With ten movements, RF achieved a high accuracy of $99.9 \%$ using the second method. Notably, the performance of all ML algorithms exhibited improvement when considering data from ten movements versus five. Additionally, it was observed that the second training method proved more effective with five-movement data compared to data involving ten movements. This comprehensive evaluation highlights the potential of machine learning algorithms for accurate gait phase recognition in diverse applications with varied training methods.

关键词： Training Radio frequency Support vector machines Machine learning algorithms Accuracy Real-time systems Classification algorithms

来源：评论

学校读者我要写书评

暂无评论

A Novel Surface Electromyography Signals Denoising Method for Gait Phase Classification

A Novel Surface Electromyography Signals Denoising Method fo...

引用

Chinese Control Conference (CCC)

作者： Yubo Sun Zhenhui Guo Yuxin Feng Ningbo Yu College of Artificial Intelligence Nankai University Tianjin China Engineering Research Center of Trusted Behavior Intelligence Ministry of Education Nankai University Tianjin China Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China Institute of Intelligence Technology and Robotic Systems Shenzhen Research Institute of Nankai University Shenzhen China

Surface electromyography (sEMG) is a non-invasive technique for recording electrical activity and is extensively employed in gait phase classification. However, the measurement process of the sEMG signal inevitably introduces noise. Consequently, denoising is required for gait analysis from the collected sEMG signal. A novel denoising method ICEEMDAN-DFA-WD has been proposed in this paper. The sEMG signals were decomposed into several intrinsic mode functions (IMF) through an improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN). The Hurst exponents were simulated by detrended fluctuation analysis (DFA) to distinguish noisy IMF and desired IMF. During the walking process, the lower limbs' sEMG exhibits strong periodicity, and the desired IMF yields higher Hurst exponents than the noisy IMF. For the noisy IMF, noise removal was performed through further decomposition by wavelet transform, followed by a hard threshold. The processed IMFs were reconstructed to denoise sEMG. In this study, experiments were conducted to compare with the existing denoising methods WD, EMD-IIT, EEMD-IWT, VMD-SIT. The proposed method can obtain better denoising effect and gait phase classification accuracy. The proposed method provides a more effective way for sEMG denoising.

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：