Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00036
Zhuo-Ya Pan
The new information technology revolution is subverting the traditional business model, and the challenges and opportunities of industrial innovation coexist. In order to enable the stadiums to achieve sustainable development under the new social development situation, Internet technology is gradually infiltrating the management of the stadiums. Large-scale sports events often require a lot of sports venues. For this reason, a large number of sports venues will be modified and built to provide comprehensive solutions for the systematic management of the stadiums and the use of them after the game. Integrate development of stadiums and stadiums through the Internet platform to improve the management level of stadiums and stadiums.
{"title":"Research on the integrated development of stadiums and stadiums under the background of “Internet +”","authors":"Zhuo-Ya Pan","doi":"10.1109/ICCEAI52939.2021.00036","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00036","url":null,"abstract":"The new information technology revolution is subverting the traditional business model, and the challenges and opportunities of industrial innovation coexist. In order to enable the stadiums to achieve sustainable development under the new social development situation, Internet technology is gradually infiltrating the management of the stadiums. Large-scale sports events often require a lot of sports venues. For this reason, a large number of sports venues will be modified and built to provide comprehensive solutions for the systematic management of the stadiums and the use of them after the game. Integrate development of stadiums and stadiums through the Internet platform to improve the management level of stadiums and stadiums.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115001402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00010
S. Sun, Yatong Zhou, Haonuo He, Jingfei He, Yue Chi
With the development of power industry, electricity has become one of the most important energy sources in our country, related to the lifeline of the country's economy. The electricity system is becoming more and more mature, but abnormal electricity consumption behaviors are also emerging endlessly, causing potential safety hazards in the electricity industry and even the electricity supply system. Considering the lack of abnormal annotations in the electricity load data, this paper proposes a semi-supervised electricity load data anomaly detection method based on MixMatch. Firstly, data cleaning of electricity load data is used to remove incorrect data. Secondly, Convolutional Autoencoder (CAE) is used to extract its time-domain and frequency-domain features separately, and the features are combined through feature fusion. Thirdly, the Borderline Synthetic Minority Oversampling Technique (Borderline-SMOTE) is used to solve the problem of data imbalance. The MixMatch semi-supervised algorithm is used to label the abnormal data to realize the anomaly detection of the electricity load data. Finally, this paper uses the k-means clustering and T-Stochastic neighbour Embedding (T -SNE) to classify the abnormal data and visualize the data. The experimental results show that, compared with traditional machine learning methods, the proposed method has a significant improvement on AUC.
{"title":"Anomaly detection of electricity load data based on MixMatch","authors":"S. Sun, Yatong Zhou, Haonuo He, Jingfei He, Yue Chi","doi":"10.1109/ICCEAI52939.2021.00010","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00010","url":null,"abstract":"With the development of power industry, electricity has become one of the most important energy sources in our country, related to the lifeline of the country's economy. The electricity system is becoming more and more mature, but abnormal electricity consumption behaviors are also emerging endlessly, causing potential safety hazards in the electricity industry and even the electricity supply system. Considering the lack of abnormal annotations in the electricity load data, this paper proposes a semi-supervised electricity load data anomaly detection method based on MixMatch. Firstly, data cleaning of electricity load data is used to remove incorrect data. Secondly, Convolutional Autoencoder (CAE) is used to extract its time-domain and frequency-domain features separately, and the features are combined through feature fusion. Thirdly, the Borderline Synthetic Minority Oversampling Technique (Borderline-SMOTE) is used to solve the problem of data imbalance. The MixMatch semi-supervised algorithm is used to label the abnormal data to realize the anomaly detection of the electricity load data. Finally, this paper uses the k-means clustering and T-Stochastic neighbour Embedding (T -SNE) to classify the abnormal data and visualize the data. The experimental results show that, compared with traditional machine learning methods, the proposed method has a significant improvement on AUC.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114672067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00044
Lei Shi, Li Hui, Jing Shi, Bin Zhao, Xiao Cui, Shibo Chu
The paper presented a new wave acquisition stereo system to estimate significant wave height based on stereo (binocular) vision. Using binocular vision, wave transformation in near shore water can be measured in wave altitude. The total measurement numbers are 1024 times. Wave vertical altitudes can be extracted from the datum according to binocular vision. With the help of 3D Fourier transform, the wave surface data can be turned into wave spectrum. By analyzing the wave spectrum, significant wave height can be estimated. Experimental results have shown that the method is effective.
{"title":"Using binocular vision to measure wave characteristic","authors":"Lei Shi, Li Hui, Jing Shi, Bin Zhao, Xiao Cui, Shibo Chu","doi":"10.1109/ICCEAI52939.2021.00044","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00044","url":null,"abstract":"The paper presented a new wave acquisition stereo system to estimate significant wave height based on stereo (binocular) vision. Using binocular vision, wave transformation in near shore water can be measured in wave altitude. The total measurement numbers are 1024 times. Wave vertical altitudes can be extracted from the datum according to binocular vision. With the help of 3D Fourier transform, the wave surface data can be turned into wave spectrum. By analyzing the wave spectrum, significant wave height can be estimated. Experimental results have shown that the method is effective.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"20 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115543115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00022
Zhaoyang Liu, Mingxi Ma, Zhaoming Wu
Hyperspectral images usually have higher spectral resolution but lower spatial resolution, compared with the multispectral images. Low spatial resolution brings difficulties to the practical applications of hyperspectral images. Therefore, to get high spatial resolution hyperspectral image, it is very important to fuse low spatial resolution hyperspectral image with the high spatial resolution multispectral image in the same scene. In this paper, we propose a hybrid regularization model by integrating sparse prior, local low-rank regularization and total variation based on l2 norm to reconstruct high spatial resolution hyperspectral images. In addition, we design an alternating direction method of multipliers (ADMM) to solve it. The experimental results show the superiority and competitiveness of our method over the state-of-the-art methods.
{"title":"Hyperspectral image fusion by hybrid regularizations with local low-rank","authors":"Zhaoyang Liu, Mingxi Ma, Zhaoming Wu","doi":"10.1109/ICCEAI52939.2021.00022","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00022","url":null,"abstract":"Hyperspectral images usually have higher spectral resolution but lower spatial resolution, compared with the multispectral images. Low spatial resolution brings difficulties to the practical applications of hyperspectral images. Therefore, to get high spatial resolution hyperspectral image, it is very important to fuse low spatial resolution hyperspectral image with the high spatial resolution multispectral image in the same scene. In this paper, we propose a hybrid regularization model by integrating sparse prior, local low-rank regularization and total variation based on l2 norm to reconstruct high spatial resolution hyperspectral images. In addition, we design an alternating direction method of multipliers (ADMM) to solve it. The experimental results show the superiority and competitiveness of our method over the state-of-the-art methods.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115682023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00098
Hong Zhang, Xiaojun Wang
Being the most important underlying backbone of a multicore processor, the interconnection network for on-chip memory has a significant impact on the performance of a multicore processor. The evaluation for the type network is almost the first step of designing a new architecture for a multicore processor. For this type of evaluation, however, there are few effective methods available because of the too much uncertainty, especially the need to compare with a great number of different multicore networks on chip. This article presents ETOM (Evaluation on Topology of On-chip Memory), a new method to evaluate the speedup of multicore architectures. ETOM can accurately figure out the contribution of each core to the overall performance of a multicore processor, while all of the cores are controlled by the topology of on-chip memory network, the contributions of cores can certainly illustrate how and how much the topology affects the overall performance, and then a targeted modification to the topology can be made.
片上存储器互连网络作为多核处理器最重要的底层骨干，对多核处理器的性能有着重要的影响。对类型网络的评估几乎是设计多核处理器新体系结构的第一步。然而，对于这种类型的评估，由于存在太多的不确定性，特别是需要与大量不同的片上多核网络进行比较，因此有效的方法很少。本文提出了一种评价多核结构加速的新方法——片上存储器拓扑评价(Evaluation on Topology of on chip Memory)。ETOM可以准确地计算出每个内核对多核处理器整体性能的贡献，而所有内核都是由片上存储网络的拓扑控制的，内核的贡献当然可以说明拓扑对整体性能的影响方式和程度，然后可以对拓扑进行有针对性的修改。
{"title":"Evaluating the Speedup of Multicore Architecture on the Topological Characteristics of On-chip Memory","authors":"Hong Zhang, Xiaojun Wang","doi":"10.1109/ICCEAI52939.2021.00098","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00098","url":null,"abstract":"Being the most important underlying backbone of a multicore processor, the interconnection network for on-chip memory has a significant impact on the performance of a multicore processor. The evaluation for the type network is almost the first step of designing a new architecture for a multicore processor. For this type of evaluation, however, there are few effective methods available because of the too much uncertainty, especially the need to compare with a great number of different multicore networks on chip. This article presents ETOM (Evaluation on Topology of On-chip Memory), a new method to evaluate the speedup of multicore architectures. ETOM can accurately figure out the contribution of each core to the overall performance of a multicore processor, while all of the cores are controlled by the topology of on-chip memory network, the contributions of cores can certainly illustrate how and how much the topology affects the overall performance, and then a targeted modification to the topology can be made.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127496230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00045
Zhu Zeng
One of the most commonly used natural language processing technologies is text classification. Spam detection, news text classification, information retrieval, emotion analysis, and intention judgment, among other applications, are all popular text classification applications [25]. Text classification is the process of assigning pre-defined class labels to text documents in order to shape semantic classes. Engineering, medical science, life science, social sciences and humanities, marketing, and government are only a few of the real-world applications. Machine learning and deep learning algorithms have recently become common and efficient methods for dealing with text classification problems involving labeled data [26]. The primary goal of text classification is to automatically assign texts to pre-defined categories based on their content. In this study, we will conduct a comparative study of the accuracies of different deep learning methods that include Bidirectional Encoder Representations from Transformers (BERT), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), and Region-based convolutional neural networks and compare the effectiveness of these deep-learning approaches in classifying Chinese news title text using the THUCNews dataset.
{"title":"A comparative study of deep learning approaches for Chinese Sentence Classification","authors":"Zhu Zeng","doi":"10.1109/ICCEAI52939.2021.00045","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00045","url":null,"abstract":"One of the most commonly used natural language processing technologies is text classification. Spam detection, news text classification, information retrieval, emotion analysis, and intention judgment, among other applications, are all popular text classification applications [25]. Text classification is the process of assigning pre-defined class labels to text documents in order to shape semantic classes. Engineering, medical science, life science, social sciences and humanities, marketing, and government are only a few of the real-world applications. Machine learning and deep learning algorithms have recently become common and efficient methods for dealing with text classification problems involving labeled data [26]. The primary goal of text classification is to automatically assign texts to pre-defined categories based on their content. In this study, we will conduct a comparative study of the accuracies of different deep learning methods that include Bidirectional Encoder Representations from Transformers (BERT), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), and Region-based convolutional neural networks and compare the effectiveness of these deep-learning approaches in classifying Chinese news title text using the THUCNews dataset.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133320948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00086
Li Wang, Siyu Tang, Jiageng Zhang, Heshan Wang, Jiawei Han, Jianxiang Cao
In the intensive computing scenario with the application of micro-service framework, it is too costly to allocate resources centrally to the micro-service instance on the server side, and it cannot adapt to the changes of the environment in real time. Therefore, allocating resource for micro-service instance distributed on the terminal becomes an effective way to solve the problem mentioned above. A client-based micro-service discovery algorithm with attractor selection model is proposed in this paper, which has the characters of simple and intelligent evolution. At first, this paper models micro-service discovery problem, defines optimization object and constraints; then, it re-defines the parameters of attractor selection and proposes the client-based micro-service discovery algorithm with attractor selection model; and at last, it analyzes the performance of the proposed algorithm with the compared ones in the really productive environment. The experiment results show that the proposed algorithm reduces almost 32 % resource fragments and 70% running time than the compared ones.
{"title":"Terminal Micro-service Discovery Algorithm based on attractor model","authors":"Li Wang, Siyu Tang, Jiageng Zhang, Heshan Wang, Jiawei Han, Jianxiang Cao","doi":"10.1109/ICCEAI52939.2021.00086","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00086","url":null,"abstract":"In the intensive computing scenario with the application of micro-service framework, it is too costly to allocate resources centrally to the micro-service instance on the server side, and it cannot adapt to the changes of the environment in real time. Therefore, allocating resource for micro-service instance distributed on the terminal becomes an effective way to solve the problem mentioned above. A client-based micro-service discovery algorithm with attractor selection model is proposed in this paper, which has the characters of simple and intelligent evolution. At first, this paper models micro-service discovery problem, defines optimization object and constraints; then, it re-defines the parameters of attractor selection and proposes the client-based micro-service discovery algorithm with attractor selection model; and at last, it analyzes the performance of the proposed algorithm with the compared ones in the really productive environment. The experiment results show that the proposed algorithm reduces almost 32 % resource fragments and 70% running time than the compared ones.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114936035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Aiming at the switching control model of hybrid system, the stability of hybrid system is discussed. Combined with the typical switching control model, the sufficient conditions for the hybrid switching system to remain stable when the switching discrete state is changed and the system energy is increased are given. By dividing the switched system into a more reasonable area and adjusting the control law in time, the optimal control of the switched system is achieved. The stability condition of traffic signal switching control is verified by simulation with the traffic signal switching model of key traffic nodes (regions) in unbalanced road network based on hybrid system model. The experimental results show that the hybrid switched control system has more outstanding advantages than the discrete dynamic and continuous dynamic systems in urban traffic signal control.
{"title":"Stability Analysis and Application Research of Hybrid Dynamic System","authors":"Qianqian Wang, Minan Tang, Aimin An, Weili Liu, Kaiyue Zhang, Jiandong Qiu","doi":"10.1109/ICCEAI52939.2021.00082","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00082","url":null,"abstract":"Aiming at the switching control model of hybrid system, the stability of hybrid system is discussed. Combined with the typical switching control model, the sufficient conditions for the hybrid switching system to remain stable when the switching discrete state is changed and the system energy is increased are given. By dividing the switched system into a more reasonable area and adjusting the control law in time, the optimal control of the switched system is achieved. The stability condition of traffic signal switching control is verified by simulation with the traffic signal switching model of key traffic nodes (regions) in unbalanced road network based on hybrid system model. The experimental results show that the hybrid switched control system has more outstanding advantages than the discrete dynamic and continuous dynamic systems in urban traffic signal control.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116983811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00047
Jiahua Wu, H. Lee
There are two stages in bottom-up human pose estimation method, joint detection and joint candidate grouping. Optimizing grouping algorithms can significantly improve the performance of pose estimation. In this paper, we introduce body center, a center point of person instance, and anchor point, a corresponding assistant position point, for the task of grouping. The anchor point is the center of joint and body center, which can help joint grouping to the corresponding person instance like an anchor. The body center and anchor point can be predicted simultaneously with the joint candidate by the same backbone. So, this new grouping method can fully exploit the features extracted by the step of joint detection. On the COCO keypoints dataset, the proposed method performs on par with the existing state-of-the-art bottom-up method in accuracy.
{"title":"A New Bottom-up Human Pose Estimation Method by Body Center and Anchor Points","authors":"Jiahua Wu, H. Lee","doi":"10.1109/ICCEAI52939.2021.00047","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00047","url":null,"abstract":"There are two stages in bottom-up human pose estimation method, joint detection and joint candidate grouping. Optimizing grouping algorithms can significantly improve the performance of pose estimation. In this paper, we introduce body center, a center point of person instance, and anchor point, a corresponding assistant position point, for the task of grouping. The anchor point is the center of joint and body center, which can help joint grouping to the corresponding person instance like an anchor. The body center and anchor point can be predicted simultaneously with the joint candidate by the same backbone. So, this new grouping method can fully exploit the features extracted by the step of joint detection. On the COCO keypoints dataset, the proposed method performs on par with the existing state-of-the-art bottom-up method in accuracy.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130344989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-01DOI: 10.1109/ICCEAI52939.2021.00069
B. Fan, Shiyou Zhang, Ye-hwa Chen, Yi Zhang, Zhangsheng Deng
This study aims to solve the problem of lateral motion control so that the fire robot accurately tracks the desired speed and desired path, so as to realize autonomous driving of the fire robot, reduce the casualties of firefighters in firefighting, and further improve the intelligence of firefighting. According to the use scenario of the fire robot, and comprehensive consideration of lightweight and energy saving, the mechanical structure of its chassis is designed, and the sliding mode variable structure and the radial basis function (RBF) neural network are combined to design the lateral motion controller on this basis. The control expression of the controller is derived. In order to verify the robustness of the controller, this study uses the ADAMS/Simulink co-simulation system, using different driving speeds to simulate and verify the controller under a typical route. The lateral controller studied in this paper plays an important role in the path tracking of fire robot.
{"title":"Lateral control design of intelligent chassis for fire robot","authors":"B. Fan, Shiyou Zhang, Ye-hwa Chen, Yi Zhang, Zhangsheng Deng","doi":"10.1109/ICCEAI52939.2021.00069","DOIUrl":"https://doi.org/10.1109/ICCEAI52939.2021.00069","url":null,"abstract":"This study aims to solve the problem of lateral motion control so that the fire robot accurately tracks the desired speed and desired path, so as to realize autonomous driving of the fire robot, reduce the casualties of firefighters in firefighting, and further improve the intelligence of firefighting. According to the use scenario of the fire robot, and comprehensive consideration of lightweight and energy saving, the mechanical structure of its chassis is designed, and the sliding mode variable structure and the radial basis function (RBF) neural network are combined to design the lateral motion controller on this basis. The control expression of the controller is derived. In order to verify the robustness of the controller, this study uses the ADAMS/Simulink co-simulation system, using different driving speeds to simulate and verify the controller under a typical route. The lateral controller studied in this paper plays an important role in the path tracking of fire robot.","PeriodicalId":331409,"journal":{"name":"2021 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130483442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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