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Human-to-Robot Handover control of an Autonomous Mobile Robot Based on Hand-Masked Object Pose Estimation

IEEE Robotics and Automation Letters 2024年第9期9卷 7851-7858页

作者： Huang, Yu-Yun Song, Kai-Tai National Yang Ming Chiao Tung University Institute of Electrical and Control Engineering College of Electrical and Computer Engineering

This letter presents a human-to-robot handover design for an Autonomous Mobile Robot (AMR). The developed control system enables the AMR to navigate to a specific person and grasp the object that the person wants to handover. This letter proposes a motion planning algorithm for grasping an unseen object held in hand. Through hand detection and segmentation, the hand region is masked and removed from the acquired depth image, which is used to estimate the object pose for grasping. For grasp pose determination, we propose to add the Convolutional Block Attention Module (CBAM) to the Generative Grasping Convolutional Neural Network (GGCNN) model to enhance the recognition rate. For the object-grasp task, the AMR localizes the object in person's hand, and uses the Model Predictive control (MPC)-based controller to simultaneously control the mobile base and manipulator to grasp the object. A laboratory-developed mobile manipulator, equipped with a 6-DoF TM5M-900 is used for experimental verification. The experimental results show an average handover success rate of 81% for five different objects. © 2016 IEEE.

关键词： Collaborative robots in manufacturing mobile manipulation pose estimation task and motion planning

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Generating diverse clothed 3D human animations via a generative model

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Computational Visual Media 2024年第2期10卷 261-277页

作者： Min Shi Wenke Feng Lin Gao Dengming Zhu School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China Institute of Computing Technology Chinese Academy of SciencesBeijing 100190China

Data-driven garment animation is a current topic of interest in the computer graphics *** approaches generally establish the mapping between a single human pose or a temporal pose sequence,and garment deformation,but it is difficult to quickly generate diverse clothed human *** address this problem with a method to automatically synthesize dressed human animations with temporal consistency from a specified human motion *** the heart of our method is a twostage ***,we first learn a latent space encoding the sequence-level distribution of human motions utilizing a transformer-based conditional variational autoencoder(Transformer-CVAE).Then a garment simulator synthesizes dynamic garment shapes using a transformer encoder-decoder *** the learned latent space comes from varied human motions,our method can generate a variety of styles of motions given a specific motion *** means of a novel beginning of sequence(BOS)learning strategy and a self-supervised refinement procedure,our garment simulator is capable of efficiently synthesizing garment deformation sequences corresponding to the generated human motions while maintaining temporal and spatial *** verify our ideas *** is the first generative model that directly dresses human animation.

关键词： Transformer garment animation conditional variational autoencoder(CVAE) computer graphics

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An efficient and high-performance WSNs restoration algorithm for fault nodes based on FT in data aggregation scheduling

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International Journal of Cognitive Computing in engineering 2025年 6卷 508-515页

作者： Li, Cheng Zhang, Guoyin College of Computer Science and Technology Harbin Engineering University Heilongjiang Harbin150001 China College of Computer and Control Engineering Qiqihar University Heilongjiang Qiqihar161006 China

In wireless sensor networks(WSNs), data aggregation effectively reduces network traffic, thereby reducing energy consumption and improving network life cycle. Nevertheless, in the process of data aggregation scheduling, if there are fault nodes, the data quality collected by the whole network will decline, and the network performance will decrease, even posing a threat to network security or causing network paralysis. Thus, an efficient and high-performance WSNs restoration algorithm is proposed based on fat tree(FT), which is referred to as the EPRA-FT algorithm. And our goal is to improve the universality, efficiency, and performance retention of the algorithm. Previously, we have conducted a range of the relevant researches on performance improvement of WSNs aggregation scheduling by adopting FT structure, and some successful results have been obtained. On the basis of these results, for the EPRA-FT algorithm, first and foremost, the relationship among nodes is comprehensively recorded in FT construction process. Then, fault nodes are shielded by deleting the known nodes in aggregation tree. Finally, the local reconfiguration of aggregation tree is completed quickly and efficiently. Meanwhile, the aggregation scheduling performance of the original network is maintained to the maximum extent. The feasibility and superiority of our proposed EPRA-FT algorithm are proved by simulation experiments. © 2025

关键词： Wireless sensor networks

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Research on incentive mechanism and evaluation of cross-enterprise distributed research and development resource sharing under networked collaborative design mode

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Soft Computing 2024年第21期28卷 12543-12559页

作者： Hu, Yongqing Su, Weixing Chen, Hanning He, Maowei Liu, Fang College of Control Science and Engineering Tiangong University Tianjin China College of Computer Science and Technology Tiangong University Tianjin China

The promotion and application of model-based systems engineering (MBSE) suffer from the lack of effective sharing of research and design (R&D) resources among enterprises in the networked collaborative design environment. This paper establishes a cross-enterprise R&D resource sharing incentive evolutionary game model, which considers multiple factors about resource sharers, sharing process and shared resource value information. The model analyses how various factors influence the evolution trend of sharing behavior. In addition, in order to realize the dynamic multidimensional evaluation and feedback of shared R&D resources and promote the positive development of resource sharing, this paper establishes a new dynamic double-objective resource evaluation model. The digital information resource in R&D resources is taken as an example to carry out experimental simulation and verification. Compared with the traditional evaluation methods, the new dynamic double-objective evaluation model established in this paper owns better performance on improving the cross-enterprise R&D resources collaborative sharing and further promoting the deep integration between R&D resources and R&D process under the networked collaborative design and MBSE development mode than others. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Evolutionary game model Incentive mechanism Multi-objective evaluation Networked collaborative design Resource sharing

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Flexibility Improvement of CHP Unit for Wind Power Accommodation

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Journal of Modern Power Systems and Clean Energy 2022年第3期10卷 731-742页

作者： Dongming Zhang Yong Hu Yaokui Gao School of Control and Computer Engineering North China Electric Power UniversityBeijingChina

Improving the flexibility of combined heat and power(CHP)units is an important way to solve the problem of wind power accommodation in northern ***,this paper analyzes the principle of an extraction-type CHP unit,calculates its safe operation range,and analyzes its contradiction between heating and ***,the safe operation ranges of the CHP unit with several flexibility modifications are further calculated,which involve two-stage bypass,low-pressure cylinder(LPC)removal,heat storage tank,and electric ***,based on the safe operation ranges,their effects on improving the capabilities of deep peak shaving and wind power accommodation are compared,and their adaptabilities to different wind scenarios are *** results show that:①all flexibility modifications can improve the deep peak shaving capability of the CHP unit,especially for the two-stage bypass and the electric boiler;②LPC removal modification can accommodate wind power to some extent,but most of wind power is still abandoned;③heat storage tank modification is unstable in different wind scenarios,which is determined by the surplus heating capability during the daytime.

关键词： Combined heat and power(CHP) flexibility bypass low-pressure cylinder(LPC)removal heat storage tank electric boiler

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Point Cloud Classification Based on Local Fusion and Dense Connection Structure 4

Point Cloud Classification Based on Local Fusion and Dense C...

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4th International Conference on Neural Networks, Information and Communication engineering, NNICE 2024

作者： Huang, Yansen Zhang, Lujian Bi, Yuanwei Liu, Yaowen Yantai University School of Computer and Control Engineering Shandong Yantai China

ISBN: (纸本)9798350394375

Due to the influence of objective factors such as scene noise and hardware equipment, compared to CAD modeling point clouds, the real point clouds collected by LiDAR often have strong non-uniformity and irregularity, which leads to the low ability of traditional point cloud classification models to extract point cloud features in real scenes and poor classification robustness. To address this issue, we have added a local feature fusion module and a dense connected feature fusion method to PointMLP, thereby encoding broader point cloud information into local features. The simple stacking of multiple MLP and Mixer blocks constitutes our network model-PointMM. The shallow features of the point cloud are used as input and enter the local feature fusion module to perform feature fusion within and between point sets. Finally, by maximizing the pooling layer and selecting points with stronger semantic features as inputs to the second stage feature extraction module. This method has been tested on the ScanObjectNN dataset and shows that it can approach SOTA with a classification accuracy of 0.8%, surpassing other mainstream models. © 2024 IEEE.

关键词： Classification (of information)

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Prototype-Based Interpretable Graph Neural Networks

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第4期5卷 1486-1495页

作者： Ragno, Alessio Rosa, Biagio La Capobianco, Roberto Sapienza University of Rome Department of Computer Control and Management Engineering Rome00185 Italy Sony AI Zurich8952 Switzerland

Graph neural networks have proved to be a key tool for dealing with many problems and domains, such as chemistry, natural language processing, and social networks. While the structure of the layers is simple, it is difficult to identify the patterns learned by the graph neural network. Several works propose post hoc methods to explain graph predictions, but few of them try to generate interpretable models. Conversely, the topic of the interpretable models is highly investigated in image recognition. Given the similarity between image and graph domains, we analyze the adaptability of prototype-based neural networks for graph and node classification. In particular, we investigate the use of two interpretable networks, ProtoPNet and TesNet, in the graph domain. We show that the adapted networks manage to reach better or higher accuracy scores than their respective black-box models and comparable performances with state-of-the-art self-explainable models. Showing how to extract ProtoPNet and TesNet explanations on graph neural networks, we further study how to obtain global and local explanations for the trained models. We then evaluate the explanations of the interpretable models by comparing them with post hoc approaches and self-explainable models. Our findings show that the application of TesNet and ProtoPNet to the graph domain produces qualitative predictions while improving their reliability and transparency. © 2020 IEEE.

关键词： computer architecture

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Comparative Analysis of Wearable and computer Vision-Based Methods for Human Torso Posture Estimation 9

Comparative Analysis of Wearable and Computer Vision-Based M...

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9th International Conference on Mathematics and computers in Sciences and Industry, MCSI 2024

作者： Muntean, Emanuel Leba, Monica University of Petrosani Department of System Control and Computer Engineering Petrosani Romania

ISBN: (纸本)9798350377224

This paper conducts a comparative analysis of human torso posture estimation methodologies, focusing on an inertial measurement unit (IMU) sensor coupled with an Arduino UNO as a wearable approach, and Kinect V2, utilizing OpenCV for posture analysis. The core objective of this study is to ascertain which method yields greater precision in the estimation of human torso posture. The IMU sensor, characterized by its wearability, provides the distinct advantage of unobtrusiveness and the capability to record motion across diverse environments. Conversely, Kinect V2 leverages computer vision techniques to derive posture estimations from visual data in real-time. Through comprehensive experimentation, this research evaluates the accuracy of both methodologies by juxtaposing their posture estimation outcomes. The findings of this investigation aim to significantly contribute to the enhancement of human posture estimation systems, with wide-ranging implications for health, sports, and ergonomics. © 2024 IEEE.

关键词： Ergonomics

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Research of interleaved hysteresis control based on soft-switching power amplifier 7

Research of interleaved hysteresis control based on soft-swi...

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7th IEEE International Electrical and Energy Conference, CIEEC 2024

作者： Qiu, Guangjuan Zhang, Xinyue Wei, Jian Chen, Jingxin Peng, E. College of Computer and Control Engineering Northeast Forestry University Harbin China

ISBN: (纸本)9798350359558

This paper delves into the interleaved hysteresis control method based on soft-switching power amplifiers. Firstly, through modeling and analysis, the basic topology and mode transition of the soft-switching power amplifier are clearly defined, revealing the conditions for implementing soft-switching. Secondly, a strategy for interleaved soft-switching hysteresis control is proposed, detailing its working principle, and the frequency range of the interleaved hysteresis loop is obtained through analysis. In order to optimize the design of the filter, this paper also deeply analyzes the design methods and parameter selection of the filter inductance, providing a theoretical foundation for the implementation of the power amplifier. The research results show that the proposed interleaved soft-switching hysteresis control method can reduce switch losses and electromagnetic interference, thereby improving the efficiency and reliability of the power amplifier. This study provides beneficial theoretical support and practical guidance for the application of high-performance motor drive systems. © 2024 IEEE.

关键词： Power amplifiers

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Optimizing Multimodal Emotion Recognition: Evaluating the Impact of Speech, Text, and Visual Modalities

Optimizing Multimodal Emotion Recognition: Evaluating the Im...

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2024 International Conference on Electronics and Devices, Computational Science, ICEDCS 2024

作者： Wang, Hongsheng Northeastern Forestry University College of Computer and Control Engineering Harbin China

ISBN: (纸本)9798331527624

This research aims to explore and optimize multimodal emotion recognition to enhance its performance. Multimodal emotion recognition involves analyzing information from different modalities - speech, vision, and text - to identify and classify emotional states accurately. This study investigates the roles of speech and text modalities and the auxiliary effect of visual modalities in multimodal emotion recognition. Study employs a two-stage multimodal information fusion neural network based on graph and attention mechanisms. The core idea is to achieve an effective fusion of multimodal information through graph convolutional networks and cross-modal attention mechanisms to improve emotion recognition performance. This study uses two datasets, Interactive Emotional Dyadic Motion Capture (IEMOCAP) and Multimodal Emotion Lines Dataset (MELD), to analyze the impact of speech and text modalities on visual modalities and their potential side effects. Results show that while the visual modality alone is less effective, adding speech or text significantly improves performance. However, introducing the speech modality and the text modality is less beneficial. Experimental outcomes reveal that the speech modality's effect is not as significant as the text modality, and its inclusion does not always lead to positive results, sometimes even degrading overall recognition performance. © 2024 IEEE.

关键词： Convolutional neural networks

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