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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yujie Jiang Xiang Fu Chengxi Zhong Teng Li Haojian Lu Song Liu School of Information Science and Technology ShanghaiTech University Shanghai China College of Control Science and Engineering Zhejiang University Hangzhou China Shanghai Engineering Research Center of Intelligent Vision and Imaging Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Knot tying is an essential task for robotic surgery, which is routinely realized by dual-arm robotic manipulation. Despite the well-established protocol and progress at macro scale so far, there remain challenges to further advance robotic knot tying technique, particularly in terms of decreasing space consumption with better dexterity, higher precision, and well biomechanical compatibility. In this paper, we propose a novel dual-arm nanorobotic system setup for automated knot tying performed on mini-incision under stereo microscope, featured by an additional rotation degree of freedom mounted on each arm. With this setup, an optimized motion trajectory planning under standard knot-tying protocol is also presented in order to support tying knots with shorter and thinner suture. Leveraging the natural advantage of nanorobotics and microscope, the proposed system is capable of tying consecutive throws with micro-suture on mini-incision, like in vascular anastomosis or microsurgery. We successfully evaluated the knot tying system on 2.0 mm wide bionic blood vessel with 30 mm long #8-0 micro-suture. We finally tested the mechanical strength of the knots for potential medical assessment.

关键词： Trajectory planning Microscopy Blood vessels Microsurgery Arms Routing protocols Synchronization

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Resource Allocation for Blockchain-Enabled Fog Computing with Deep Reinforcement Learning 12

Resource Allocation for Blockchain-Enabled Fog Computing wit...

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12th International Conference on Communication and Network Security, ICCNS 2022

作者： Zhang, Yihe Tu, Shanshan Waqas, Muhammad Yang, Yongjie Wu, Aiming Bai, Xuetao Engineering Research Center of Intelligent Perception and Autonomous Control Faculty of Information Technology Beijing University of Technology Beijing China Computer Engineering Department College of Information Technology University of Bahrain 32038 Bahrain School of Engineering Edith Cowan University Perth6027 Australia

ISBN: (纸本)9781450397520

With the developments of the Internet of Things, the demands of low latency, high bandwidth and high-performance computing has increased higher. Therefore, the distributed computing named Fog Computing has proposed to solve the problem above. Fog computing can provide lower transmission latency, faster response time and less network congestion. However, the fog devices are unable to guarantee the security and privacy of data transmission, due to they are vulnerable to attack. Blockchain technology works as a decentralized public ledger to store and share transactions. Blockchain can improve security and protect data privacy of Fog Computing. Moreover, there are still issues in the blockchain-enabled Fog Computing, the two main issues are the energy consumption and computing efficiency. Thus, in this paper, we propose an optimization framework for blockchain-enabled Fog Computing systems to optimize resource allocation. Besides, we adopt the dueling deep reinforcement learning to obtain the optimal resource allocation strategy, with dynamically selecting the fog server, offloading decision, block size. Simulation results show that the proposed framework can reduce the energy consumption and computation overhead of the system, as well as can improve the computing efficiency. © 2022 ACM.

关键词： Blockchain

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A Reinforcement Learning Based Dynamic Multi-Objective Constrained Evolutionary Algorithm for Open-Pit Mine Truck Scheduling

A Reinforcement Learning Based Dynamic Multi-Objective Const...

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2023 China Automation Congress, CAC 2023

作者： Qiu, Junxiang Li, Changhe Yang, Shengxiang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo- Exploration Ministry of Education Wuhan430074 China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

ISBN: (纸本)9798350303759

Aiming at the truck scheduling problem in the open-pit mine scenario, a truck scheduling model based on real-time ore blending is established, and an adaptive evolution algorithm for truck scheduling based on DCNSGA-III is proposed. In the established scheduling model, the real-time grade variance of the crushing plant is minimized as one of the optimization objectives, and the Q-learning algorithm is introduced to adaptively select one of the most effective operators during the search process. Experiments show that the proposed method can effectively control the grade fluctuation of the ore flow and better scheduling schemes are obtained in comparison with algorithms equipped with the traditional search operator selection methods. © 2023 IEEE.

关键词： Evolutionary algorithms

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Distributed Active Disturbance Rejection control of Multiple Mobile Robots for Online Workload Partition

Distributed Active Disturbance Rejection Control of Multiple...

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2023 China Automation Congress, CAC 2023

作者： Li, Xin Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Computer and Data Science Fuzhou University Fuzhou China

ISBN: (纸本)9798350303759

Considering the actual multi-agent coverage process, the motion trajectories are seriously affected by disturbances and noise. In this paper, a cooperative control method based on active disturbance rejection controller (ADRC) for multiple mecanum-wheeled robots (MWMR) is proposed to improve its robustness. In particular, to suppress the total disturbances during the running of each robot and reduce large computation and observation cost of high order ADRC, a reduced-order cascaded ADRC (RC-ADRC) is proposed. Moreover, distributed controller is proposed to track the expected trajectories of multiple mecanum-wheeled robots under disturbances. Compared with the proposed RC-ADRC based cooperative control scheme and PID based cooperative control one, the favorable motion trajectory tracking performance is obtained. Simulation results verify the superiority of the method. © 2023 IEEE.

关键词： controllers

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Light field imaging for computer vision:a survey

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Frontiers of Information technology & Electronic engineering 2022年第7期23卷 1077-1097页

作者： Chen JIA Fan SHI Meng ZHAO Shengyong CHEN Engineering Research Center of Learning-Based Intelligent System(Ministry of Education) Tianjin University of TechnologyTianjin 300384China Key Laboratory of Computer Vision and System(Ministry of Education) Tianjin University of TechnologyTianjin 300384China

Light field(LF)imaging has attracted attention because of its ability to solve computer vision *** this paper we briefly review the research progress in computer vision in recent *** most factors that affect computer vision development,the richness and accuracy of visual information acquisition are *** imaging technology has made great contributions to computer vision because it uses cameras or microlens arrays to record the position and direction information of light rays,acquiring complete three-dimensional(3D)scene *** imaging technology improves the accuracy of depth estimation,image segmentation,blending,fusion,and 3D *** has also been innovatively applied to iris and face recognition,identification of materials and fake pedestrians,acquisition of epipolar plane images,shape recovery,and LF ***,we further summarize the existing problems and the development trends of LF imaging in computer vision,including the establishment and evaluation of the LF dataset,applications under high dynamic range(HDR)conditions,LF image enhancement,virtual reality,3D display,and 3D movies,military optical camouflage technology,image recognition at micro-scale,image processing method based on HDR,and the optimal relationship between spatial resolution and four-dimensional(4D)LF information *** imaging has achieved great success in various *** the past 25 years,more than 180 publications have reported the capability of LF imaging in solving computer vision *** summarize these reports to make it easier for researchers to search the detailed methods for specific solutions.

关键词： Light field imaging Camera array Microlens array Epipolar plane image computer vision

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Deep Learning-Based Dimension Measurement System for Industrial Part Inspection

Deep Learning-Based Dimension Measurement System for Industr...

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2024 China Automation Congress, CAC 2024

作者： Li, Xiao-Di Fan, Xing-Rong Zhang, Xian-Ming Zhang, Han-Zhi Huang, Chun-Jie Xu, Cheng Chongqing Engineering Laboratory for Detection Control and Integrated System School of Artificial Intelligence Chongqing Technology and Business University Chongqing China Engineering Research Centre for Waste Oil Recovery Technology and Equipment Ministry of Education Chongqing Key Laboratory Chongqing Technology and Business University Chongqing China School of Computer Science and Information Engineering Chongqing Technology and Business University Chongqing China Chongqing Intelligent Supply Chain Engineering & Technology Research Center Chongqing Jiaotong University Chongqing China Chongqing Aerospace Bashan Motorcycle Manufacturing Co. Ltd. Chongqing China

ISBN: (纸本)9798350368604

This paper develops a deep learning-based system for the dimension measurement of industrial parts. The system employs a general self-supervised image segmentation network to perform dichotomous image segmentation (DIS) on the parts, effectively extracting binary images of the target components from complex backgrounds without requiring preprocessing steps such as filtering or denoising. Following segmentation, contour detection, and dimension measurement are executed. The system utilizes a CMOS area scan camera and was tested on a computer equipped with a GTX1050 graphics card. The tests, conducted on two typical thrust ball bearing components (i.e., the ball retainer and the shaft ring) ü yielded ten measurements per part. Comparison with a vernier caliper as the reference standard reveals that under normal operating conditions, the maximum standard deviation is 0.007 mm and the maximum absolute error is 0.017 mm. © 2024 IEEE.

关键词： Ball bearings

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Efficient Multi-Query Oriented Continuous Subgraph Matching 40

Efficient Multi-Query Oriented Continuous Subgraph Matching

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40th IEEE International Conference on Data engineering, ICDE 2024

作者： Ma, Ziyi Yang, Jianye Zhou, Xu Xiao, Guoqing Wang, Jianhua Yang, Liang Li, Kenli Lin, Xuemin School of Artificial Intelligence Hebei University of Technology China Wuzhou University Guangxi Key Laboratory of Machine Vision and Intelligent Control China Cyberspace Institute of Advanced Technology Guangzhou University China PengCheng Laboratory Department of New Networks China College of Computer Science and Electronic Engineering Hunan University China Shenzhen Research Institute Hunan University China Antai College of Economics and Management Shanghai Jiao Tong University China

ISBN: (纸本)9798350317152

Continuous subgraph matching (CSM) is a critical task for analyzing dynamic graphs and has a wide range of applications, such as merchant fraud detection, cyber-attack hunting, and rumor detection. Although many efficient CSM algorithms have been recently proposed, they are mainly designed to process a single query. However, in some application scenarios, multi-query oriented continuous subgraph matching (MQCSM) may be of more interest. To our knowledge, the two existing solutions to MQCSM are outdated due to unsatisfactory performance. In this paper, we propose MQ-Match, an efficient approach to MQCSM. First, we design a compact yet effective index structure CCG, which maintains the local matching result of vertices in the data graph using a directed graph. The directed edges in CCG can be utilized as an effective pruning rule for the subsequent incremental matching algorithm when expanding a partial match. Then, we develop a computation sharing incremental matching algorithm. In specific, a set of matching trees is constructed based on the depth-first search trees of the query graphs. By utilizing CCG, we conduct subgraph matching for the matching tree to collect the incremental matches for the query graphs, where the common structures of query graphs are matched only once. Extensive experiments show that MQ-Match can achieve 3.1x-7071.4x speedup over the competitors, and consumes much less memory under the majority of the experiment settings. © 2024 IEEE.

关键词： Directed graphs

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Ontology-Based BERT Model for Automated Information Extraction from Geological Hazard Reports

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Journal of Earth Science 2023年第5期34卷 1390-1405页

作者： Kai Ma Miao Tian Yongjian Tan Qinjun Qiu Zhong Xie Rong Huang Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering China Three Gorges UniversityYichang 443002China College of Computer and Information Technology China Three Gorges UniversityYichang 443002China Hubei Engineering Technology Research Center for Farmland Environment Monitoring China Three Gorges UniversityYichang 443002China School of Computer Science China University of GeosciencesWuhan 430074China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518034China Beijing Key Laboratory of Urban Spatial Information Engineering Beijing 100045China College of Economics and Management China Three Gorges UniversityYichang 443002China

Geological knowledge can provide support for knowledge discovery, knowledge inference and mineralization predictions of geological big data. Entity identification and relationship extraction from geological data description text are the key links for constructing knowledge graphs. Given the lack of publicly annotated datasets in the geology domain, this paper illustrates the construction process of geological entity datasets, defines the types of entities and interconceptual relationships by using the geological entity concept system, and completes the construction of the geological corpus. To address the shortcomings of existing language models(such as Word2vec and Glove) that cannot solve polysemous words and have a poor ability to fuse contexts, we propose a geological named entity recognition and relationship extraction model jointly with Bidirectional Encoder Representation from Transformers(BERT) pretrained language model. To effectively represent the text features, we construct a BERT-bidirectional gated recurrent unit network(BiGRU)-conditional random field(CRF)-based architecture to extract the named entities and the BERT-BiGRU-Attention-based architecture to extract the entity relations. The results show that the F1-score of the BERT-BiGRU-CRF named entity recognition model is 0.91 and the F1-score of the BERT-BiGRU-Attention relationship extraction model is 0.84, which are significant performance improvements when compared to classic language models(e.g., word2vec and Embedding from Language Models(ELMo)).

关键词： ontology BERT model name entity recognition relation extraction knowledge graph

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Two-Stage Robust Optimization Under Decision Dependent Uncertainty

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IEEE/CAA Journal of Automatica Sinica 2022年第7期9卷 1295-1306页

作者： Yunfan Zhang Feng Liu Yifan Su Yue Chen Zhaojian Wang João P.S.Catalão State Key Laboratory of Power System and Generation Equipment the Department of Electrical EngineeringTsinghua UniversityBeijing 100084China Department of Mechanical and Automation Engineering the Chinese University of Hong KongHong Kong SARChina Ministry of Education Key Laboratory of System Control and Information Processing the Department of AutomationShanghai Jiao Tong Universityand also with Shanghai Engineering Research Center of Intelligent Control and ManagementShanghai 200240China Faculty of Engineering of the University of Porto and Institute for Systems and Computer Engineering Technology and Science(INESC TEC)Porto 4200-465Portugal IEEE

In the conventional robust optimization(RO)context,the uncertainty is regarded as residing in a predetermined and fixed uncertainty *** many applications,however,uncertainties are affected by decisions,making the current RO framework *** paper investigates a class of two-stage RO problems that involve decision-dependent *** introduce a class of polyhedral uncertainty sets whose right-hand-side vector has a dependency on the here-and-now decisions and seek to derive the exact optimal wait-and-see decisions for the second-stage problem.A novel iterative algorithm based on the Benders dual decomposition is proposed where advanced optimality cuts and feasibility cuts are designed to incorporate the uncertainty-decision *** computational tractability,robust feasibility and optimality,and convergence performance of the proposed algorithm are guaranteed with theoretical *** motivating application examples that feature the decision-dependent uncertainties are ***,the proposed solution methodology is verified by conducting case studies on the pre-disaster highway investment problem.

关键词： Benders decomposition decision-dependent uncertainty endogenous uncertainty robust optimization(RO)

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case 63

Optimal Linear Deception Attacks on Remote State Estimation ...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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