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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Ruidong Ma Jingyu Chen John Oyekan Department of Automatic Control and System Engineering University of Sheffield Sheffield United Kingdom Department of Computer Science University of York York United Kingdom

Assemble-to-Order (ATO) has become a popular production strategy for the increasing demand for mass-customized manufacturing. In order to facilitate a flexible and automated Human-Robot-Collaboration system for ATO, we propose a Learning from Demonstration (LfD) framework based on 2D videos in this paper. We initially combine temporal hand motions with spatial hand-object interactions to detect assembly actions. Therefore, an assembly graph can be constructed using classified action sequences. Compared to previous studies on task planning for robots, our graph-based semantic planner can directly learn the demonstrated task structure and thus produce more detailed assistive robot actions for more effective collaboration. We validate our approach by applying it to a real-world ATO problem. The results demonstrated that our proposed system can produce actions adaptively in response to varying human action sequences, as well as guide human assembly when the robot is not involved. Our approach also shows generalizability to unseen human action sequences.

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GeoReF: Geometric Alignment Across Shape Variation for Category-level Object Pose Refinement

GeoReF: Geometric Alignment Across Shape Variation for Categ...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Linfang Zheng Tze Ho Elden Tse Chen Wang Yinghan Sun Hua Chen Ales Leonardis Wei Zhang Hyung Jin Chang Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology China School of Computer Science. University of Birmigsham UK Department of Computer Science the University of Hong Kong China

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

Object pose refinement is essential for robust object pose estimation. Previous work has made significant progress to-wards instance-level object pose refinement. Yet, category-level pose refinement is a more challenging problem due to large shape variations within a category and the discrep-ancies between the target object and the shape prior. To address these challenges, we introduce a novel architecture for category-level object pose refinement. Our approach in-tegrates an HS-Iayer and learnable affine transformations, which aims to enhance the extraction and alignment of Geometric information. Additionally, we introduce a cross-cloud transformation mechanism that efficiently merges di-verse data sources. Finally, we push the limits of our model by incorporating the shape prior information for translation and size error prediction. We conducted extensive ex-periments to demonstrate the effectiveness of the proposed framework. Through extensive quantitative experiments, we demonstrate significant improvement over the baseline method by a large margin across all metrics. 1 1 Project page: https://***/***

关键词： Point cloud compression computer vision Shape Soft sensors Pose estimation computer architecture Predictive models

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Cooperative Reinforcement Learning for Military Drones over Large-Scale Battlefields

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年

作者： Kim, Gyu Seon Lee, Sungjoon Woo, Taejin Park, Soohyun Department of Electrical and Computer Engineering Korea University Seoul Korea Republic of LIG Nex1 Ground Control System Team 3 Korea Republic of Division of Computer Science Sookmyung Women’s University Seoul Korea Republic of

The development of autonomous systems in military drone operations signifies a paradigm shift in modern warfare strategies, and modern warfare emphasizes the crucial role of military drones to the extent that it is called drone war. Despite the importance of these military drones, the efficiency of such operations hinges on the swarm military drones’ ability to operate cooperatively in complex battlefield environments where the target changes dynamically. The proposed algorithm for robust and reliable military drones needs to consider a total of three objectives, i.e., (i) cooperative swarm flight maintenance, (ii) target bombing zone maximization, and (iii) energy efficiency optimization. For this objective, multi-agent deep reinforcement learning (MARL) is utilized for the cooperation of military drones to achieve these objectives optimally. Lastly, this paper considers ‘Shahed-136’ which is one of well-known military drones for realistic battlefield evaluation. Additionally, the military drones employing the proposed algorithm are evaluated in a large-scale battlefield environment spanning 4×104 km3. This paper assesses the efficacy of the proposed approach through simulations that evaluate the swarm flight, success rate of bombing, and energy efficiency of drones, particularly under dynamic target conditions. © 2024 IEEE.

关键词： Deep reinforcement learning

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Resilient Cooperative control of Multiple DC Microgrids With Interconnection Networks Against Cyber Attacks

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical systems 2025年 3卷 116-126页

作者： Xiao, Feng Liu, Shiyu Wei, Bo Fang, Fang Qin, Jiahu North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China North China Electric Power University School of Control and Computer Engineering Beijing102206 China North China Electric Power University New Energy Generation National Engineering Research Center Beijing102206 China University of Science and Technology of China Department of Automation Hefei230027 China

The two control objectives of voltage regulation and precise current sharing are conflicting in multi-bus DC microgrids. In this paper, a distributed control strategy is proposed, and it can achieve accurate current sharing and regulate the voltage of a critical node to the rated value. However, such a distributed control system is susceptible to potential cyber attacks that could deteriorate microgrids performances by corrupting communication links or actuators. To overcome these difficulties, we design the interconnected communication networks to establish a resilient cooperative system of multiple microgrids against unknown bounded injection attacks. The proposed resilient control strategy can achieve the control objectives of maintaining voltage regulation and current sharing within each microgrids under different operating conditions, and the interconnected system consisting of multiple microgrids cooperates to mitigate the adverse effect of cyber attacks. The dynamics and stability of the overall close-loop system of the DC microgrids are analyzed, in the present or absent of cyber attacks. Simulation results validate the effectiveness of the proposed approach in two 4-bus DC microgrids. © 2023 IEEE.

关键词： Cyber attacks

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GeoReF: Geometric Alignment Across Shape Variation for Category-level Object Pose Refinement

arXiv

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arXiv 2024年

作者： Zheng, Linfang Tse, Tze Ho Elden Wang, Chen Sun, Yinghan Chen, Hua Leonardis, Aleš Zhang, Wei Chang, Hyung Jin Shenzhen Key Laboratory of Control Theory and Intelligent Systems School of System Design and Intelligent Manufacturing Southern University of Science and Technology China Department of Computer Science The University of Hong Kong Hong Kong School of Computer Science University of Birmingham United Kingdom

Object pose refinement is essential for robust object pose estimation. Previous work has made significant progress towards instance-level object pose refinement. Yet, category-level pose refinement is a more challenging problem due to large shape variations within a category and the discrepancies between the target object and the shape prior. To address these challenges, we introduce a novel architecture for category-level object pose refinement. Our approach integrates an HS-layer and learnable affine transformations, which aims to enhance the extraction and alignment of geometric information. Additionally, we introduce a cross-cloud transformation mechanism that efficiently merges diverse data sources. Finally, we push the limits of our model by incorporating the shape prior information for translation and size error prediction. We conducted extensive experiments to demonstrate the effectiveness of the proposed framework. Through extensive quantitative experiments, we demonstrate significant improvement over the baseline method by a large margin across all metrics. © 2024, CC BY-NC-SA.

关键词： Metadata

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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Liu, Yajun Li, Ru Li, Aimin Fei, Rong Guo, Xie Wu, Fang-Xiang Xi'an University of Technology Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an China Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China University of Saskatchewan Division of Biomedical Engineering Department of Computer Science Department of Mechanical Engineering Saskatoon Canada

ISBN: (纸本)9798350337488

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions. © 2023 IEEE.

关键词： interactive inference network noncoding RNA piRNA-mRNA interactions positive-unlabeled learning

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A survey on user-centric cell-free massive MIMO systems

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Digital Communications and Networks 2022年第5期8卷 695-719页

作者： Shuaifei Chen Jiayi Zhang Jing Zhang Emil Björnson Bo Ai School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing100044China Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong UniversityBeijing100044China Department of Computer Science KTH Royal Institute of TechnologySE-16440KistaSweden Department of Electrical Engineering(ISY) Linköping UniversitySE-58183LinköpingSweden State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing100044China

The mobile data traffic has been exponentially growing during the last several *** was enabled by the densification of the network infrastructure in terms of increased cell density(i.e.,Ultra-Dense Network(UDN))and/or the increased number of active antennas per Access Point(AP)(i.e.,massive Multiple-Input Multiple-Output(mMIMO)).However,neither UDN nor mMIMO will meet the increasing demand for the data rate of the Sixth Generation(6G)wireless communications due to the inter-cell interference and large quality-of-service ***-Free(CF)mMIMO,which combines the best aspects of UDN and mMIMO,is viewed as a key solution to this *** such systems,each User Equipment(UE)is served by a preferred set of surrounding APs *** this paper,we provide a survey of the state-of-the-art literature on CF *** a starting point,the significance and the basic properties of CF mMIMO are *** then present the canonical framework to discuss the essential details(i.e.,transmission procedure and mathematical system model).Next,we provide a deep look at the resource allocation and signal processing problems related to CF mMIMO and survey the up-to-date schemes and *** that,we discuss the practical issues in implementing CF mMIMO and point out the potential future ***,we conclude this paper with a summary of the key lessons learned in this field.

关键词： 6G network User-centric cell-free network Massive multiple-input multiple-output

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Applying system Thinking to Learn from Accident of Modern Automatic control systems

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Chinese Journal of Electronics 2025年第2期23卷 409-414页

作者： Ru Niu Yuan Cao Xiaocheng Ge Tao Tang State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China School of Electronics and Information Engineering National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Beijing China Department of Computer Science University of York York UK

Modern societies increasingly rely on automatic control systems. These systems are hardly pure technical systems; instead they are complex socio-technical systems, which consist of technical elements and social components. It is necessary to have a systematic approach to analyze these systems because it is growing evidence that accidents from these systems usually have complex causal factors which form an interconnected network of events, rather than a simple cause-effect chain. We take railway Train control systems (TCS) as an example to demonstrate the importance of the socio-technical approach to analyze the system. The paper presents an investigation of recent high-speed railway accident by applying STAMP - one of the most notable socio-technical system analysis techniques, outlines improvements to the system which could avoid similar accidents in the future. We also provide our valuable feedback for the use of STAMP.

关键词： Sociotechnical systems Analytical models systematics Railway accidents Transportation Medical services Rail transportation systems thinking Research and development Accidents

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing 26

On the Approximation of the Quotient of Two Gaussian Densiti...

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26th International Conference on Information Fusion, FUSION 2023

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Xue, Yanbo University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Career Science Lab Beijing China

ISBN: (纸本)9798890344854

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target. © 2023 International Society of Information Fusion.

关键词： Cost functions

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Electrical resistivity-temperature characteristics enhancement of insulating cross-linked polyethylene composites by incorporating positive temperature coefficient particles with different Curie temperatures

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High Voltage 2023年第1期8卷 1-11页

作者： Guimin Jiang Yuanxiang Zhou Chenyuan Teng Yunxiao Zhang Xin Huang Lei Xue Luming Zhou The Wind Solar Storage Division of State Key Laboratory of Control and Simulation of Power System and Generation Equipment Xinjiang UniversityUrumqiChina State Key Laboratory of Power System and Generation Equipment Department of Electrical EngineeringTsinghua UniversityBeijingChina College of Information Engineering Zhejiang University of TechnologyHangzhouChina School of Electronics and Computer Science University of SouthamptonSouthamptonUK

Incorporating positive temperature coefficient(PTC)ceramic particles into polymers provides a prospective alternative solution for suppressing severe electric field distortions caused by negative temperature coefficient(NTC)of electrical resistivity within polymer insulation in high voltage direct current *** effect of the Curie temperature of PTC particles on the inhibition of the NTC effect of cross-linked polyethylene(XLPE)is investigated in this *** temperature coefficient particles with varied Curie temperatures are surface-modified and melt blending with *** modified particles are dispersed on averagely in the *** electrical resistivity,space charge behaviour,and direct current(DC)electrical breakdown strength of the samples are investigated at different temperatures,exploring the effect of the Curie temperature of PTC particles on suppressing the NTC effect of *** is demonstrated that the reduction in Curie temperature can further suppress the NTC effect of XLPE,enhance the DC strength at elevated temperatures,and inhibit the internal space charge *** reduction in the Curie temperatures means that the initiation of the PTC effect advances,exhibiting a higher potential barrier and inhibiting the NTC effect more *** work may give a reference for improving the temperature stability of DC properties for XLPE cable insulation.

关键词： coefficient resistivity insulation

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