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第34届中国控制与决策会议

作者： Ziyao Wang Yiye Wang Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

Natural Locomotion interface(NLI) is critical to expanding the users' exploration of scenes in virtual reality and improving user *** on the 2D motion platform,users can achieve a natural locomotion experience in a limited physical *** a small-scale 2D motion platform,an ideal situation is that the velocity of the platform can always be synchronized with the user's actual intended velocity,so that the user's center of mass is kept at the center of the *** puts a brand new requirement on the performance of the platform *** paper designs an acceleration-level state feedback controller for the small-scale 2D motion *** the user's intended acceleration as an external disturbance,it is estimated by introducing a disturbance state observer;for the user' s velocity on the platform,a linear state observer is used to estimate it;then takes the estimated values as feedforward terms to compensate the *** with the HCMK1 2D motion platform,we implemented the controller and verified it to be *** recording the data of the user walking along the circle and the square trajectory,it was verified that the designed controller has good control performance for the user's motion and the state observers a great performance to quickly track the user's intended acceleration and the user's velocity on the platform.

关键词： Virtual Reality Nature Locomotion Interface State Observer 2D-Motion Platform

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Automatic Reading System of Pointer Meters in Gas Gathering Stations

Automatic Reading System of Pointer Meters in Gas Gathering ...

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第34届中国控制与决策会议

作者： Yaqing Chang Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

In gas gathering stations,pointer meters are usually read by workers,which takes high labor costs and has low *** solve these problems and build intelligent gas gathering stations,this paper proposes an automatic reading system for real-time and accurate pointer meter reading.A new dataset is first constructed,which consists of700 pointer meter images with different angles,illumination and *** on the dataset,the deep learning model YOLOv5 is trained for dial and pointer *** the pointer mask output by YOLOv5,image preproces sing is used to separate the pointer from the background and generate the pure *** improved skeleton extraction algorithm and the Hough line detection algorithm are combined to extract the pointer center *** the dial image output by YOLOv5,feature matching and perspective transformation are adopted for position ***,pointer reading is obtained by applying the angle method to the corrected dial and the pointer center *** experiments demonstrate the high accuracy and efficiency of the proposed *** strong robustness to various interference factors in complex environments are also validated.

关键词： Pointer Meter Automatic Reading YOLOv5 Object Detection Skeleton Extraction

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Lightweight Vision Transformer for Small Data Sets 38

Lightweight Vision Transformer for Small Data Sets

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38th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2023

作者： Fang, Wenxing Su, Yanxu Institutes of Physical Science and Information Technology Anhui University Hefei China School of Artificial Intelligence Anhui University Hefei230601 China Southeast University Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9798350303636

With the rapid development of Transformers in the field of computer vision, models based on Transformers have become highly competitive architectures in the area. Although variants of Transformer models have achieved increasing accuracy on image classification tasks, the size of the training set and the number of parameters required by the models have increased dramatically. When dealing with small datasets, such models face problems such as overfitting and undergeneralization, leading to poor accuracy on the test set. We propose a new lightweight vision transformer (LVT) to address these issues. We reconstructed the backbone network, which learns the relationship between pixels through local window self-attention and global self-attention computation. We also use the attention pooling approach to fuse the token sequences generated by the backbone network more meticulously. We trained on the CIFAR-10 and CIFAR-100 datasets from scratch and compared them with a modern convolutional neural network. The experimental results show that LVT outperforms the modern convolutional neural network in terms of accuracy and efficiency. On the test set of CIFAR-10, we have obtained an accuracy of 96.83%, which indicates that our model can effectively solve the problems facing the training of small datasets and has a wide range of application prospects. © 2023 IEEE.

关键词： lightweight pooling self-attention windows

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An Effective Hybrid Genetic Algorithm for the Multi-Robot Task Allocation Problem with Limited Span

SSRN

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SSRN 2024年

作者： Liu, Wenbo Kuang, Zhian Zhang, Yongcong Zhou, Bo He, Pengfei Li, Shihua School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Shanghai Friendess Electronic Technology Shanghai201100 China

Multi-robot task allocation is one of the most interesting multi-robot systems that have gained considerable attention due to various real-world applications. In this paper, we focus on a multi-robot task allocation problem where a set of industrial robots, which are installed on a gantry and have a limited working span, have to jointly perform a set of weld lines in large size. We present a mathematical model that captures the objective of minimizing the cycle time, i.e., the time required to complete a given set of weld lines. Due to the inherent difficulty of the problem, we propose an effective hybrid genetic algorithm to solve it. Because the robots are associated with a limited working span, the algorithm integrates a specific region division algorithm to divide the workpieces into a set of regions where the robots can reach all the weld lines in each region. It also incorporates a dedicated route-based crossover to generate promising offspring solutions and an effective neighborhoodbased local search procedure to improve each offspring solution as much as possible. Extensive experimental results on three benchmark instances show that the algorithm significantly outperforms reference methods. Additional experiments on real-world instances are presented to verify the algorithm’s effectiveness in solving the multi-robot task allocation problem with limited span. © 2024, The Authors. All rights reserved.

关键词： Industrial robots

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Hotspot detection of photovoltaic modules in infrared thermal image based on saliency analysis

Hotspot detection of photovoltaic modules in infrared therma...

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第34届中国控制与决策会议

作者： Yiye Wang Yu Shen Chenxi Li Kanjian Zhang Haikun Wei Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

With the increasing awareness of environmental protection,the solar photovoltaic(PV) industry has been developing dramatically in recent *** module is an important part of PV power generation *** all the defect types of PV modules,hotspots occur more frequently and cause more serious ***,it is necessary to detect *** approach is proposed using saliency analysis method for hotspot detection,combing the cognitive property about visual saliency and the temperature property of *** only does this approach not require manual threshold setting,but also it does not require a large number of learning *** approach can also achieve the defect diagnosis and hotspot location when compared with the electrical characterization *** infrared thermal(IRT)images trained in experiments are obtained using the thermographic camera FLIR Vue Pro with the unmanned aerial vehicle from a PV plant in Jiangsu,*** 135 IRT images are collected and 1020 PV modules are extracted from these *** have proved great accuracy and robustness when using the proposed method to detect hotspots.

关键词： Hotspot PV module IRT image Saliency analysis Graph

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Design of redundant control system for Antarctic unattended energy platform based on RS-485

Design of redundant control system for Antarctic unattended ...

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第34届中国控制与决策会议

作者： Chenwei Sun Kanjian Zhang Haikun Wei Jian Ge Shixiong Fang Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationSchool of AutomationSoutheast University

The successful operation of the Antarctic unattended energy platform with data storage and other functions can provide electric energy for other scientific research ***,its performance needs further improvement due to the lack of experience and the special environmental constraints of *** on the above reasons,this paper proposes an optimized design of unattended energy control platform from the perspective of improving the reliability and safety of the *** to the actual project requirements,the engine control system of the unattended energy platform is designed and *** control system part is designed as a control mode with RS-485 control combined with hardware interface features to realize the direct communication between the upper computer and the generator set and the related hardware control *** redundant control is added to effectively avoid the loss of connection of key equipment of the whole device due to irreparable failure of PLC in the previous system,which improves the reliability of the platform system.

关键词： RS-485 communication Redundant control system Data acquisition and Reliability

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Multi-Modal Based Fuzzy Atmosfield in Human-Robot Interaction 42

Multi-Modal Based Fuzzy Atmosfield in Human-Robot Interactio...

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42nd Chinese control Conference, CCC 2023

作者： Li, Xin-Heng Liu, Zhen-Tao Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581543

Recently, the emotional robot has basic functions of perceiving and expressing emotions, but it still hard to communicate naturally between humans and robots. One major reason is that communication atmosphere is seldom considered in Human-robot Interaction (HRI). We propose Multi-modal (i.e., music background, speech, and semantics) Based Fuzzy Atmosfield (FA), which can not only realize the dynamic adjustment of FA but also dynamically regulate human emotions. In the experiment, a Pepper robot is used and one hundred volunteers are invited for HRI, and soothing piano pieces are used as background music. Questionnaires were filled by the volunteers after the experiments, from which the results show that 90% of the volunteers felt the dynamic changes in the communication atmosphere and 77% of the volunteers felt significant emotional regulation, which demonstrates the effectiveness of our method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Semantics

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AMG: A Depression Detection Model with Autoencoder and Multi-Head Graph Convolutional Network 42

AMG: A Depression Detection Model with Autoencoder and Multi...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Han-Guang Meng, Qing-Hao Jin, Li-Cheng Wang, Jian-Bang Hou, Hui-Rang Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin Key Laboratory of Process Measurement and Control Tianjin300072 China China Southern Power Grid Company Limited Guangzhou510623 China

ISBN: (纸本)9789887581543

Depression is a common chronic mental disorder characterized by high prevalence, recurrence, suicide rate, disability rate and heavy disease burden. Depression assessment based on questionnaires is subjective, therefore, a novel framework to is hereby designed to detect depression automatically and obj ectively. The framework first utilizes a two-way autoencoder to extract the hidden features from the original differential entropy features. The new features are used to generate the channel connectivity graph, using the multi-head attention mechanism. Next, the new features and graphs are input into the graph convolutional network (GCN) to aggregate spatial information. Finally, the output from GCN is passed to a fully connected layer and a soft layer to obtain the predicted label. Experiments are performed on Multimodal Open Dataset for Mental-disorder Analysis dataset. A final accuracy of 88.68% and a cross entropy loss of 2.4532 are obtained, when using ten-fold cross validation, outperforming other traditional machine learning methods including SVM, KNN, decision tree. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Decision trees

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E-Nose-Based Domain-Generalization Recognition of Ignitable Liquids

E-Nose-Based Domain-Generalization Recognition of Ignitable ...

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第43届中国控制会议

作者： Tian-Shu Song Zhen-Peng Chen Hui-Rang Hou Hong-Yue Li Qing-Hao Meng Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Detecting ignitable liquids(ILs) at the scene of a fire is crucial for fire investigation. The electronic nose(e-nose) is crucial for detecting ILs due to its affordability and rapid response time. Process limitations and changes in environmental conditions can cause variations in the reactions of multiple e-noses with the same sensor array to the same input gas. This can significantly reduce the accuracy of identifying ILs when deploying a model trained on one e-nose to other e-noses. In order to tackle the issue of cross-platform identification of ILs using e-noses, we developed a feature mute gated network(FMG-Net).This network is capable of maintaining consistency in the shared components of different e-noses at the low-level feature level while effectively muting the distinct low-level features. FMG-Net is comprised of a main network and multiple branch networks that are specific to different domains. Initially, a subsidiary domain-specific convolutional neural network(SDS-CNN) is trained to learn the network parameters on various e-nose platforms with known labels. Additionally, the backbone network generates low-level features of the e-nose responses. Furthermore, the SDS-CNN incorporates random input of low-level features and generates a mask using the gradient. This mask is then used to explicitly remove the non-overlapping parts of the low-level features. At last, the low-level features are sent back to the backbone network for further training once the non-overlapping parts have been removed. Experiments were conducted to identify four types of ILs(diesel, gasoline, ethanol, and thinner) using five self-made e-nose platforms with identical sensor arrays. The results indicated that the proposed FMG-Net consistently outperforms other domain-generalization algorithms in terms of recognition accuracy and parameter sizes. FMG-Net has the ability to detect volatile gases in ILs using an e-nose, even without the need for a dataset.

关键词： Electronic Nose Fire Investigation Ignitable Liquids Convolutional Neural Network Cross Platform

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Steps Toward Industry 5.0:Building“6S”Parallel Industries With Cyber-Physical-Social Intelligence

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1692-1703页

作者： Xingxia Wang Jing Yang Yutong Wang Qinghai Miao Fei-Yue Wang Aijun Zhao Jian-Ling Deng Lingxi Li Xiaoxiang Na Ljubo Vlacic School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China North Automatic Control Technology Institute Taiyuan 030006China China Huaneng Group Co. Ltd.Beijing 100031China Department of Electrical and Computer Engineering Indiana University-Purdue University Indianapolis(IUPUI)IndianapolisIN 46202 USA Department of Engineering University of CambridgeCambridgeCB21PZUK School of Engineering and Built Environment Griffith UniversityGold CoastQLD 4222Australia

Very recently,intensive discussions and studies on Industry 5.0 have sprung up and caused the attention of researchers,entrepreneurs,and policymakers from various sectors around the ***,there is no consensus on why and what is Industry 5.0 *** this paper,we define Industry 5.0from its philosophical and historical origin and evolution,emphasize its new thinking on virtual-real duality and human-machine interaction,and introduce its new theory and technology based on parallel intelligence(PI),artificial societies,computational experiments,and parallel execution(the ACP method),and cyber-physical-social systems(CPSS).Case studies and applications of Industry 5.0 over the last decade have been briefly summarized and analyzed with suggestions for its future *** believe that Industry 5.0 of virtual-real interactive parallel industries has great potentials and is critical for building smart *** are outlined to ensure a roadmap that would lead to a smooth transition from CPS-based Industry 4.0 to CPSS-based Industry 5.0 for a better world which is Safe in physical spaces,S ecure in cyberspaces,Sustainable in ecology,Sensitive in individual privacy and rights,Service for all,and Smartness of all.

关键词： ACP artificial intelligence CPS CPSS Industry 4.0 Industry 5.0 parallel industries parallel intelligence

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