检索结果-内蒙古大学图书馆

2022 International Conference on Electrical, Computer, Communications and Mechatronics engineering, ICECCME 2022

作者： Šelek, Ana Seder, Marija Department of Control and Computer Engineering Faculty of Electrical Engineering and Computing Zagreb Croatia

ISBN: (数字)9781665470957

ISBN: (纸本)9781665470957

In this paper, a real-time smooth motion planning method for a four mecanum wheeled omnidirectional mobile robot in dynamic environments that generates a smooth collision-free trajectory is proposed. The method employs a graph-search-based path planning algorithm and a smoothing technique based on clothoids. It is suitable for real-time operation due to its computational simplicity and allows fast path replanning in case the robot encounters unknown and dynamic obstacles. Such a path is feasible for holonomic mobile robots since it does not contain sharp turns so the energy consumption is reduced. Our method is compared to the reactive model predictive control scheme in simulations. The comparison showed advantages of the proposed method in the reduced task execution time, path length, cumulative replanning time, and smooth velocity profile. © 2022 IEEE.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel Optimization 26

BiERL: A Meta Evolutionary Reinforcement Learning Framework ...

引用

26th European Conference on Artificial Intelligence, ECAI 2023

作者： Wang, Junyi Zhu, Yuanyang Wang, Zhi Zheng, Yan Hao, Jianye Chen, Chunlin Department of Control Science and Intelligent Engineering Nanjing University China College of Intelligence and Computing Tianjin University China

ISBN: (纸本)9781643684369

Evolutionary reinforcement learning (ERL) algorithms recently raise attention in tackling complex reinforcement learning (RL) problems due to high parallelism, while they are prone to insufficient exploration or model collapse without carefully tuning hyperparameters (aka meta-parameters). In the paper, we propose a general meta ERL framework via bilevel optimization (BiERL) to jointly update hyperparameters in parallel to training the ERL model within a single agent, which relieves the need for prior domain knowledge or costly optimization procedure before model deployment. We design an elegant meta-level architecture that embeds the inner-level's evolving experience into an informative population representation and introduce a simple and feasible evaluation of the meta-level fitness function to facilitate learning efficiency. We perform extensive experiments in MuJoCo and Box2D tasks to verify that as a general framework, BiERL outperforms various baselines and consistently improves the learning performance for a diversity of ERL algorithms. © 2023 The Authors.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Magnetic Flux Servoing for Precise Localization Based on Gradient Tensor Contractions 19

Magnetic Flux Servoing for Precise Localization Based on Gra...

引用

19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Martinovic, Dean Orsag, Matko University of Zagreb Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems Zagreb10000 Croatia

ISBN: (纸本)9798350320695

This paper focuses on bridge inspections performed by intelligent unmanned aerial vehicles (UAV). For this, small data loggers are placed by the UAVs at the bridge, which have to be removed later. In our previous work we presented the magnetic localization method SRIOD, which not only detects the center of the data logger but also its orientation. In this work we proof SRIOD in a real application and let a robotic arm locate a magnetic target. The hardware involved is presented including the control strategy for the robot. The motions of the robot and the magnetic target are captured with 12 Optitrack cameras in order to validate the localization quality. © 2023 IEEE.

关键词： Antennas

来源：评论

学校读者我要写书评

暂无评论

Accelerating Heterogeneous Federated Learning with Closed-form Classifiers 41

Accelerating Heterogeneous Federated Learning with Closed-fo...

引用

41st International Conference on Machine Learning, ICML 2024

作者： Fanì, Eros Camoriano, Raffaello Caputo, Barbara Ciccone, Marco Department of Computing and Control Engineering Polytechnic University of Turin Italy Istituto Italiano di Tecnologia Genoa Italy CINI Consortium Rome Italy

Federated Learning (FL) methods often struggle in highly statistically heterogeneous settings. Indeed, non-IID data distributions cause client drift and biased local solutions, particularly pronounced in the final classification layer, negatively impacting convergence speed and accuracy. To address this issue, we introduce Federated Recursive Ridge Regression (FED3R). Our method fits a Ridge Regression classifier computed in closed form leveraging pre-trained features. FED3R is immune to statistical heterogeneity and is invariant to the sampling order of the clients. Therefore, it proves particularly effective in cross-device scenarios. Furthermore, it is fast and efficient in terms of communication and computation costs, requiring up to two orders of magnitude fewer resources than the competitors. Finally, we propose to leverage the FED3R parameters as an initialization for a softmax classifier and subsequently fine-tune the model using any FL algorithm (FED3R with Fine-Tuning, FED3R+FT). Our findings also indicate that maintaining a fixed classifier aids in stabilizing the training and learning more discriminative features in cross-device settings. Official website: https://***/. Copyright 2024 by the author(s)

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Distributed Platooning control of Automated Vehicles Subject to Replay Attacks Based on Proportional Integral Observers

引用

IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1954-1966页

作者： Meiling Xie Derui Ding Xiaohua Ge Qing-Long Han Hongli Dong Yan Song Department of Control Science and Engineering University of Shanghai for Science and TechnologyShanghai 200093China School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318the Heilongjiang Provincial Key Laboratory of Networking and Intelligent ControlNortheast Petroleum UniversityDaqing 163318 Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China

Secure platooning control plays an important role in enhancing the cooperative driving safety of automated vehicles subject to various security *** paper focuses on the distributed secure control issue of automated vehicles affected by replay attacks.A proportional-integral-observer(PIO)with predetermined forgetting parameters is first constructed to acquire the dynamical information of ***,a time-varying parameter and two positive scalars are employed to describe the temporal behavior of replay *** light of such a scheme and the common properties of Laplace matrices,the closed-loop system with PIO-based controllers is transformed into a switched and time-delayed ***,some sufficient conditions are derived to achieve the desired platooning performance by the view of the Lyapunov stability *** controller gains are analytically determined by resorting to the solution of certain matrix inequalities only dependent on maximum and minimum eigenvalues of communication ***,a simulation example is provided to illustrate the effectiveness of the proposed control strategy.

关键词： Automated vehicles platooning control proportional-integral-observers(PIOs) replay attacks time-delays

来源：评论

学校读者我要写书评

暂无评论

A New Benchmark and Algorithm for Clothes-Changing Video Person Re-Identification

引用

IEEE Transactions on Information Forensics and Security 2025年 20卷 1993-2005页

作者： Wang, Likai Zhang, Xiangqun Han, Ruize Wei, Yanjie Wang, Song Feng, Wei Tianjin University College of Intelligence and Computing Tianjin300350 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518107 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

Person re-identification (Re-ID) is a classical computer vision task and has significant applications for public security and information forensics. Recently, long-term Re-ID with clothes-changing has attracted increasing attention. However, existing methods mainly focus on image-based setting, where richer temporal information is overlooked. In this paper, we focus on the relatively new yet practical problem of Clothes-Changing Video-based Re-ID (CCVReID), which is less studied. First, given the dataset shortage, we build two new benchmark datasets for CCVReID problem, including a large-scale synthetic video dataset and a real-world one, both containing human sequences with various clothing changes. Moreover, we systematically study this problem by simultaneously considering the classical appearance feature and temporal feature contained in the video. We develop a dual-branch fusion framework that makes use of the information from both clothes-aware appearance feature and clothes-free gait feature. For better information fusion, a confidence-guided re-ranking strategy is proposed to adaptively balance the weight of these two categories of features. We have released the benchmark and code proposed in this work to the public at https://***/kkw98/CCVReID. © 2025 IEEE.

关键词： Reamers

来源：评论

学校读者我要写书评

暂无评论

Kinect-Based Evaluation of Severity of Facial Paresis: Pilot Study 1

引用

6th Computational Methods in Systems and Software, CoMeSySo 2022

作者： Kovarik, Jan Schätz, Martin Ciler, Jakub Kohout, Jan Mares, Jan Department of Computing and Control Engineering UCT Prague Technicka 5 Dejvice Prague 616628 Czech Republic

ISBN: (数字)9783031214356

ISBN: (纸本)9783031214349

Facial paresis, temporary or permanent loss of facial muscle mobility, seriously affects the patient’s physical and mental health. Patients suffer from difficulties with eating, salivating or speaking. Facial rehabilitation is usually the solution to facial paresis. However, during the rehabilitation facial muscle mobility must be monitored. Unfortunately, the assessment of facial mobility usually depends on the subjective opinion of the doctor. The aim of this pilot study was to design a method of objective identification of a healthy patient and a patient with facial paralysis. Using a depth sensor Kinect a few records of facial movements of health patient were taken for both symmetric and asymmetric movement. Using statistical methods the most suitable of 1347 facial landmarks were chosen for the classification model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Biomedical data Facial paresis Kinect Statistical methods

来源：评论

学校读者我要写书评

暂无评论

Multiobjective Differential Evolution for Higher-Dimensional Multimodal Multiobjective Optimization

引用

IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1458-1475页

作者： Jing Liang Hongyu Lin Caitong Yue Ponnuthurai Nagaratnam Suganthan Yaonan Wang School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001 School of Electrical Engineering and Automation Henan Institute of TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China KINDI Center for Computing Research Qatar UniversityDohaQatarand also with the Nanyang Technology UniversitySingapore College of Electrical and Information Engineering and also with the National Engineering Research Center for Robot Visual Perception and Control TechnologyHunan UniversityChangsha 410082China IEEE

In multimodal multiobjective optimization problems(MMOPs),there are several Pareto optimal solutions corre-sponding to the identical objective *** paper proposes a new differential evolution algorithm to solve MMOPs with higher-dimensional decision *** to the increase in the dimensions of decision variables in real-world MMOPs,it is diffi-cult for current multimodal multiobjective optimization evolu-tionary algorithms(MMOEAs)to find multiple Pareto optimal *** proposed algorithm adopts a dual-population framework and an improved environmental selection *** utilizes a convergence archive to help the first population improve the quality of *** improved environmental selection method enables the other population to search the remaining decision space and reserve more Pareto optimal solutions through the information of the first *** combination of these two strategies helps to effectively balance and enhance conver-gence and diversity *** addition,to study the per-formance of the proposed algorithm,a novel set of multimodal multiobjective optimization test functions with extensible decision variables is *** proposed MMOEA is certified to be effective through comparison with six state-of-the-art MMOEAs on the test functions.

关键词： Benchmark functions diversity measure evolution-ary algorithms multimodal multiobjective optimization.

来源：评论

学校读者我要写书评

暂无评论

Adaptive Trajectory Tracking control for Nonholonomic Wheeled Mobile Robots:A Barrier Function Sliding Mode Approach

引用

IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 1007-1021页

作者： Yunjun Zheng Jinchuan Zheng Ke Shao Han Zhao Hao Xie Hai Wang the School of Mechanical Engineering Hefei University of TechnologyHefei 230009China the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyHawthorn VIC 3122Australia the School of Civil Aviation Northwestern Polytechnical UniversityXi’an 710072China the Shanghai Aerospace Control Technology Institute Shanghai 201109 the School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China the College of Science HealthEngineering and EducationMurdoch UniversityPerth WA6150Australia

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external *** paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for *** with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances *** advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier *** benefit is that the overestimation of control gain can be eliminated,resulting in chattering ***,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the *** stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

关键词： Adaptive sliding mode barrier function nonholonomic wheeled mobile robot(NWMR) trajectory tracking control

来源：评论

学校读者我要写书评

暂无评论

MACLSTM: A Weather Attributes Enabled Recurrent Approach to Appliance-Level Energy Consumption Forecasting

引用

Computers, Materials & Continua 2025年第2期82卷 2969-2984页

作者： Ruoxin Li Shaoxiong Wu Fengping Deng Zhongli Tian Hua Cai Xiang Li Xu Xu Qi Liu NARI-TECH Nanjing Control System Co. Ltd.Nanjing211106China School of Software Nanjing University of Information Science&TechnologyNanjing210044China Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services Nanjing210044China

Studies to enhance the management of electrical energy have gained considerable momentum in recent years. The question of how much energy will be needed in households is a pressing issue as it allows the management plan of the available resources at the power grids and consumer levels. A non-intrusive inference process can be adopted to predict the amount of energy required by appliances. In this study, an inference process of appliance consumption based on temporal and environmental factors used as a soft sensor is proposed. First, a study of the correlation between the electrical and environmental variables is presented. Then, a resampling process is applied to the initial data set to generate three other subsets of data. All the subsets were evaluated to deduce the adequate granularity for the prediction of the energy demand. Then, a cloud-assisted deep neural network model is designed to forecast short-term energy consumption in a residential area while preserving user privacy. The solution is applied to the consumption data of four appliances elected from a set of real household power data. The experiment results show that the proposed framework is effective for estimating consumption with convincing accuracy.

关键词： Electrical load forecasting cloud computing smart grid weather attributes energy consumption time-series analysis

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：