检索结果-内蒙古大学图书馆

IEEE International Conference on Robotics and Automation (ICRA)

作者： Guwen Han Qi Ye Anjun Chen Jiming Chen College of Computer Science and Technology Zhejiang University Hangzhou China College of Control Science and Engineering Zhejiang University Hangzhou China The College of Control Science and Engineeringthe State Key Laboratory of Industrial Control Technology Zhejiang University and the Key Key Lab of CS&AUS of Zhejiang Province

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Interactive hand mesh reconstruction from singleview images poses a significant challenge with the severe occlusion and depth ambiguity inherent in interactive hand gestures. Recent approaches that employ probabilistic models and tokenpruned techniques have shown decent results in multi-view human body reconstruction. Nevertheless, these methods have not fully utilized multi-scale semantic information from multiview images and are not applicable in scenarios involving severe occlusion during dual-hand interactions. Simultaneously, current single-view methods independently reconstruct the left and right hands, which are ineffective in enhancing the interaction between both hands. To address these challenges, we propose CAMInterHand, a cooperative attention-based method for multi-view interactive hand pose and mesh reconstruction. Specifically, CAMInterHand extracts local pyramid features and global vertex features from multi-scale feature maps of multi-view images, enabling the exploration of rich local semantic information and facilitating effective feature alignment. Furthermore, CAMInterHand employs the cooperative attention fusion module to fuse all features from multi-view images, enhancing interactions among vertices of dual hands within global and local contexts. We conduct extensive experiments on the large-scale multi-view dataset InterHand2.6M and CAMInterHand achieves a substantial performance improvement over existing methods for multi-view and single-view interactive hand reconstruction.

关键词： Fuses Semantics Feature extraction Probabilistic logic Data mining Robotics and automation Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Improved Generative Adversarial Network with Hybrid Attention Mechanism for Path Planning 42

Improved Generative Adversarial Network with Hybrid Attentio...

引用

42nd Chinese control Conference, CCC 2023

作者： Zhang, Yi-Fan Sun, Tao Ma, Song Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tsinghua University Department of Automation Beijing100084 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789887581543

Multi-agent path planning is one of the most challenging problems in the field of artificial intelligence. In this paper, an improved generative adversarial network model with hybrid attention mechanism for data-driven path planning is proposed. Firstly, by introducing spatial attention mechanism, positional attention mechanism and channel attention mechanism, a hybrid attention module is designed. This module not only establishes feature relationship between different locations, but also provides adaptive feature weights to highlight key information. Next, by embedding the hybrid attention module into the generative adversarial network, an improved generative adversarial network model is developed. The proposed model can capture effective feature information in the image and ensures that the generated path can evade obstacles accurately. Finally, some simulation results are provided to verify the superiority and accuracy of the model in path planning. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Improved Hybrid Attention Learning System for Remaining Useful Life Prediction 42

Improved Hybrid Attention Learning System for Remaining Usef...

引用

42nd Chinese control Conference, CCC 2023

作者： Li, Zhi Sun, Tao Ma, Song Yang, Bin Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Tsinghua University Department of Automation Beijing100084 China School of Control Science and Engineering Dalian University of Technology Dalian116024 China

ISBN: (纸本)9789887581543

Remaining useful life (RUL) prediction can improve the availability and efficiency of equipment or system by providing timely maintenance suggestions. In this paper, an improved hybrid attention learning system for RUL prediction is developed. By introducing adaptive weighting, a hybrid attention mechanism with self attention and external attention is designed. The mechanism enhances the attention to samples with similar performance degradation patterns, and improves the feature extraction ability of the learning system for sensor data with strong temporal correlation. Finally, we conducted a series of simulation experiments on the commercial modular aviation propulsion system simulation (C-MAPSS) dataset to verify the effectiveness and superiority of the proposed method in RUL prediction. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

BEVTransFusion: LiDAR-Camera Fusion under Bird's-Eye-View for 3D Object Detection with Transformers 4

BEVTransFusion: LiDAR-Camera Fusion under Bird's-Eye-View fo...

引用

4th IEEE International Conference on Pattern Recognition and Machine Learning, PRML 2023

作者： Feng, Kaiqi Zhang, Yu Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou China Zhejiang University State Key Lab. of Indust. Contr. Technol. Key Lab. of Collab. Sensing and Autonomous Unmanned Syst. of Zhejiang Prov. Coll. of Contr. Sci. and Eng. Hangzhou China

ISBN: (纸本)9798350324303

Recently, there is growing research interest in extracting Bird's-Eye-View (BEV) features from images and LiDAR to improve 3D object detection. However, existing methods mainly combine the features mechanically, which limits the utilization of BEV features. To address this limitation, we draw inspiration from TransFusion and design a two-layer transformer decoder to fuse LiDAR and camera BEV features. By doing so, we can omit the steps of reference point backprojection and feature sampling, which results in better correlation between the fused LiDAR and image features and higher robustness to the calibration matrix. Furthermore, we add 3D position encoding to the BEV features to compensate for the lack of height information. We also propose an length-width-height modulated attention mechanism to incorporate scale information. We also perform comprehensive experiments to verify the effectiveness of our methods. © 2023 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

An end-to-end instance segmentation method based on improved ConvNeXt V2

引用

International Journal of Wireless and Mobile Computing 2024年第4期26卷 384-392页

作者： Wang, Wenlu Sun, Ying Xu, Manman Bai, Dongxu Huang, Li Zou, Chunlong Chen, Baojia Tang, Dalai Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Hubei Wuhan China Research Centre for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Hubei Wuhan China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Hubei Wuhan China College of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan China College of Mechanical Engineering Hubei University of Automotive Technology Hubei Shiyan China Hubei Key Laboratory of Hydroelectric Machinery Design and Maintenance China Three Gorges University Hubei Yichang China School of Computer Information Management Inner Mongolia University of Finance and Economics Hohhot China

In order to improve the efficiency of indoor mobile robots in locating and segmenting environmental instances, an instance segmentation method based on RTMDet is proposed. Firstly, the more powerful ConvNeXt V2 is used as the backbone network of the model, which improves the performance of the existing RTMDet model. Subsequently, NAS-FPN is used as a converged network to detect the network at any given time. Finally, AdamW is used as the model optimiser, which effectively solves the problem of excessive memory occupation when updating parameters and improves the performance of the model. The proposed method obtains the highest evaluation index in all cases. After training and testing on the Cityscapes data set, the recognition accuracy reaches 65.0%. © 2024 Inderscience Enterprises Ltd.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

A TCN-Transformer Model of Acceleration Prediction for Preceding Vehicle in CACC Systems

A TCN-Transformer Model of Acceleration Prediction for Prece...

引用

Conference on Vehicle control and Intelligence (CVCI)

作者： Wenzhao Tang Wenbin Tang Xiaohong Jiao Yahui Zhang Dongxue Zhang Hebei Key Laboratory of Industrial Computer Control Engineering Yanshan University Qinhuangdao Hebei Province China School of Mechanical Engineering Yanshan University Qinhuangdao China

ISBN: (数字)9798331504892

ISBN: (纸本)9798331504908

This study establishes an acceleration prediction model of the preceding vehicle tailored for cooperative adaptive cruise control (CACC) systems that address the common challenges posed by V2V communication delays or no communication from the preceding vehicle. The designed model integrates a temporal convolutional network (TCN) with the Transformer architecture block to create a sophisticated mechanism for temporal data analysis. This integration leverages the strengths of TCN in capturing spatial features and the multi-attention mechanism of Transformers to enhance the recognition of long-term dependencies in the time series of data. The synergy between these techniques not only effectively narrows the identification gap between short-term and long-term dependencies but also helps to process spatial information for accurate time-series prediction, significantly improving prediction accuracy. Simulations using the NGSIM dataset confirm the model's prediction performance over the traditional model. Further, the potential of the method to solve the communication delay problem is verified, highlighting the effectiveness of TCN and Transformer multi-attention mechanism in improving the CACC capability.

关键词： Adaptation models Accuracy Uncertainty Adaptive systems Time series analysis Vehicular ad hoc networks Predictive models Transformers Delays Cruise control

来源：评论

学校读者我要写书评

暂无评论

An Improved Fault-Tolerant control and Stabilization for Positive Polynomial Fuzzy Systems

An Improved Fault-Tolerant Control and Stabilization for Pos...

引用

IEEE International Conference on control Science and Systems engineering (CCSSE)

作者： Ziguang Wang Aiwen Meng Mingxuan Wang Zhiquan Li Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei China College of Electronic and Information Engineering Hebei University Hebei China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

This paper presents an improved analysis method to design a fault-tolerant controller for positive polynomial fuzzy systems based on static output feedback as well as actuator faults. Firstly, inspired by the property of fault matrix, a new approach of controller design is presented, and some constraint conditions are introduced to guarantee the stability conditions and posi-tivity conditions to be convex simultaneously. Furthermore, by comparing with the existing methods, this method not only can eliminate the binding to the input matrix B, but also is able to provide a wider range of stability region. Besides, to enhance the relaxation of the stability analysis, we introduce the up-to-date Taylor series membership functions (TSMFs) approximation method such that the information embedded in the membership functions and the state boundary information can be taken into the stability conditions. As a result, on the strength of Lyapunov stability theory, the stability analysis is performed via sum-of-squares (SOS) approach. Finally, a simulation example is given to illustrate the effectiveness and reliability of the proposed method.

关键词： Fault tolerant systems Fault tolerant control Reliability theory Taylor series Systems engineering and theory Stability analysis Polynomials Output feedback Fuzzy systems Lyapunov methods

来源：评论

学校读者我要写书评

暂无评论

Forming Circle Formations of Multi-agent Systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

引用

5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Contragan-Acl:Contrastive Learning for Image-to-Image Translation with Adversarial Comsistency Loss

SSRN

引用

SSRN 2022年

作者： Li, HaiBing ChengXin, Liang Li, YaQian School of Industrial Computer Control Engineering Yanshan University China Key Laboratory of Industrial Computer Control Engineering of Hebei Yanshan University China

Generative adversarial networks (GANs) are a hot research topic recently. So unsupervised image-to-image translation become a central task in computer vision. In this paper, we propose contrastive learning training strategy that obtain more significant features of true and false samples to improve the ability of distinguishing true and false samples. Then we design adversarial consistency loss that the generator and discriminator are added to the reconstruction process to further deal with the details and texture of the generated image to stabilize training strategy. Experiments on CelebA-HQ and a AFHQ,the FID score about reduce by more than 10% and LPIPS score increase by 10%. © 2022, The Authors. All rights reserved.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

VTAO-BiManip: Masked Visual-Tactile-Action Pre-training with Object Understanding for Bimanual Dexterous Manipulation

arXiv

引用

arXiv 2025年

作者： Sun, Zhengnan Shi, Zhaotai Chen, Jiayin Liu, Qingtao Cui, Yu Ye, Qi Chen, Jiming College of Control Science and Engineering Zhejiang University Hangzhou310027 China State Key Laboratory of Industrial Control Technology Zhejiang University China Key Key Lab of CS&AUS of Zhejiang Province China

Bimanual dexterous manipulation remains significant challenges in robotics due to the high DoFs of each hand and their coordination. Existing single-hand manipulation techniques often leverage human demonstrations to guide RL methods but fail to generalize to complex bimanual tasks involving multiple sub-skills. In this paper, we introduce VTAOBiManip, a novel framework that combines visual-tactile-action pretraining with object understanding to facilitate curriculum RL to enable human-like bimanual manipulation. We improve prior learning by incorporating hand motion data, providing more effective guidance for dual-hand coordination than binary tactile feedback. Our pretraining model predicts future actions as well as object pose and size using masked multimodal inputs, facilitating cross-modal regularization. To address the multiskill learning challenge, we introduce a two-stage curriculum RL approach to stabilize training. We evaluate our method on a bottle-cap unscrewing task, demonstrating its effectiveness in both simulated and real-world environments. Our approach achieves a success rate that surpasses existing visual-tactile pretraining methods by over 20%. Copyright © 2025, The Authors. All rights reserved.

关键词： Bottles

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：