This paper considers the development of a brain driven car, which would be of great help to the physically disabled people. Since these cars will rely only on what the individual is thinking they will hence not require any physical movement on the part of the individual. The car integrates signals from a variety of sensors like video, weather monitor, anti-collision etc. it also has an automatic navigation system in case of emergency. The car works on the asynchronous mechanism of artificial intelligence. It’s a great advance of technology which will make the disabled, abled. In the 40s and 50s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton and the Ratio Club in England. Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them. A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.
本文探讨了大脑驱动汽车的开发问题，它将为身体残疾人士提供极大的帮助。由于这种汽车只依赖于人的思维，因此不需要人的任何身体动作。汽车集成了各种传感器的信号，如视频、天气监视器、防碰撞等。汽车的工作原理是人工智能的异步机制。这是一项伟大的技术进步，它将使残疾人成为健全人。上世纪四五十年代，一些研究人员探索神经学、信息论和控制论之间的联系。他们中的一些人制造出了利用电子网络展现初级智能的机器，如 W. 格雷-沃尔特的海龟和约翰-霍普金斯的 "野兽"。这些研究人员中的许多人都聚集在普林斯顿的遥想学会和英国的比率俱乐部参加会议。大多数研究人员希望，他们的研究成果最终能被整合到具有通用智能（被称为强人工智能）的机器中，该机器将上述所有技能结合在一起，并在大部分或全部技能上超越人类的能力。少数人认为，这样的项目可能需要人工意识或人工大脑等拟人化特征。
{"title":"Brain Controlled Car for Disabled Using Artificial Intelligence","authors":"N. Bindhu, N. Mageswari","doi":"10.46632/daai/3/2/14","DOIUrl":"https://doi.org/10.46632/daai/3/2/14","url":null,"abstract":"This paper considers the development of a brain driven car, which would be of great help to the physically disabled people. Since these cars will rely only on what the individual is thinking they will hence not require any physical movement on the part of the individual. The car integrates signals from a variety of sensors like video, weather monitor, anti-collision etc. it also has an automatic navigation system in case of emergency. The car works on the asynchronous mechanism of artificial intelligence. It’s a great advance of technology which will make the disabled, abled. In the 40s and 50s, a number of researchers explored the connection between neurology, information theory, and cybernetics. Some of them built machines that used electronic networks to exhibit rudimentary intelligence, such as W. Grey Walter's turtles and the Johns Hopkins Beast. Many of these researchers gathered for meetings of the Teleological Society at Princeton and the Ratio Club in England. Most researchers hope that their work will eventually be incorporated into a machine with general intelligence (known as strong AI), combining all the skills above and exceeding human abilities at most or all of them. A few believe that anthropomorphic features like artificial consciousness or an artificial brain may be required for such a project.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129491812","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}
As the primary method of track support, traditional sloping embankments are typically used by railroad lines. Geosynthetically Reinforced Soil (GRS) systems, as an alternative to traditional embankments, have gained appeal, notably for high-speed lines in India. This system's reduced base area compared to traditional embankments means that less ground stabilization, improvement, and land taking is necessary. The research's findings provide intriguing strategies that may be implemented into the way tracks are designed now to accommodate faster freight trains pulling greater loads. This research explains how to anticipate the bearing capacity of weak sand supported by a method of compacted granular fill over natural clay soil using a hybrid Recurrent Neural Network (RNN) and Elephant Herding Optimization (EHO) with Georgic reinforced soil foundation. The exact prediction target for the proposed model was developed by using displacement amplitude as an output index. A number of elements influencing the foundation bed's properties, Georgic reinforcement, and dynamic excitation have been taken into account as input variables. The RNN-anticipated EHO's accuracy was compared to that of three other popular approaches, including ANN, HHO, CFA, and MOA. Strict statistical criteria and a multi-criteria approach were principally used to assess the predictive power of the developed models. The model is also examined using fresh, independent data that wasn't part of the initial dataset. The hybrid RNNEHO model performed better in predicting the displacement amplitude of footing lying on Geogrid-reinforced beds than the other benchmark models. Last but not least, the sensitivity analysis was used to highlight how input parameters might affect the estimate of displacement amplitude.
{"title":"Investigation of Stress Distribution in a Railway Embankment Reinforced By Geogrid Based Weak Soil Formation Using Hybrid Rnn-Eho","authors":"","doi":"10.46632/daai/3/2/39","DOIUrl":"https://doi.org/10.46632/daai/3/2/39","url":null,"abstract":"As the primary method of track support, traditional sloping embankments are typically used by railroad lines. Geosynthetically Reinforced Soil (GRS) systems, as an alternative to traditional embankments, have gained appeal, notably for high-speed lines in India. This system's reduced base area compared to traditional embankments means that\u0000less ground stabilization, improvement, and land taking is necessary. The research's findings provide intriguing strategies that may be implemented into the way tracks are designed now to accommodate faster freight trains pulling greater loads.\u0000This research explains how to anticipate the bearing capacity of weak sand supported by a method of compacted granular fill over natural clay soil using a hybrid Recurrent Neural Network (RNN) and Elephant Herding Optimization (EHO) with Georgic reinforced soil foundation. The exact prediction target for the proposed model was developed by using displacement amplitude as an output index. A number of elements influencing the foundation bed's properties, Georgic reinforcement, and dynamic excitation have been taken into account as input variables. The RNN-anticipated EHO's accuracy was compared to that of three other popular approaches, including ANN, HHO, CFA, and MOA. Strict statistical criteria and a multi-criteria approach were principally used to assess the predictive power of the developed models. The model is also examined using fresh, independent data that wasn't part of the initial dataset. The hybrid RNNEHO model performed better in predicting the displacement amplitude of footing lying on Geogrid-reinforced beds than the other benchmark models. Last but not least, the sensitivity analysis was used to highlight how input parameters might affect the estimate of displacement amplitude.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134344985","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}
Decentralized video sharing structures are much like video sharing structures wherein creators post content material and customers view it. However, the primary distinction lies withinside the community in the back of the decentralized video sharing platform. A peer-to-peer (P2P) community of decentralized video sharing structures helps the steady switch of files. To make sure speedy facts switch, facts is break up into smaller blocks for less complicated switch and download, making sure quicker downloads and browsing. The decentralized video sharing platform transfers facts over a P2P community, however with an extra layer of blockchain era encryption. Less operational value, higher fault tolerance, much less consider necessities among garage carriers and facts owners, and much less vulnerability to attacks. An occasion in blockchain era has delivered a decentralized garage mode to the public. Video transcoding is extensively carried out in video streaming commerce, changing films into a couple of codecs for extraordinary audiences.
{"title":"YouTube Clone by Using Ethereum Block Chain","authors":"","doi":"10.46632/daai/3/1/9","DOIUrl":"https://doi.org/10.46632/daai/3/1/9","url":null,"abstract":"Decentralized video sharing structures are much like video sharing structures wherein creators post content material and customers view it. However, the primary distinction lies withinside the community in the back of the decentralized video sharing platform. A peer-to-peer (P2P) community of decentralized video sharing structures helps the steady switch of files. To make sure speedy facts switch, facts is break up into smaller blocks for less complicated switch and download, making sure quicker downloads and browsing. The decentralized video sharing platform transfers facts over a P2P community, however with an extra layer of blockchain era encryption. Less operational value, higher fault tolerance, much less consider necessities among garage carriers and facts owners, and much less vulnerability to attacks. An occasion in blockchain era has delivered a decentralized garage mode to the public. Video transcoding is extensively carried out in video streaming commerce, changing films into a couple of codecs for extraordinary audiences.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130114655","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}
Thyroid is a gland which is present in front of the neck, wrapped around the windpipe (trachea). Thyroid shape is like Butterfly that’s smaller in the middle and 2 side wings which are around the throat. As Thyroid is a gland it is important in our body when thyroid produces too much thyroid hormones then that condition is called hyperthyroidism and if thyroid gland produces less thyroid hormones then that condition is called hypothyroidism. Machine learning is one of the most important tools to classify the diseases nowadays whether a person has a disease or not like Cancer detection, kidney disease detection or Diabetes etc. Our project is to predict whether a person has Thyroid disease or not. Whether he has hypothyroidism or hyperthyroidism, or he is not suffering from thyroid disease.
{"title":"Thyroid Detection using Machine learning","authors":"Savita Adhav, Vipul Jadhao, Abhishek Markad, Suraj Jadhav","doi":"10.46632/daai/3/2/29","DOIUrl":"https://doi.org/10.46632/daai/3/2/29","url":null,"abstract":"Thyroid is a gland which is present in front of the neck, wrapped around the windpipe (trachea). Thyroid shape is like Butterfly that’s smaller in the middle and 2 side wings which are around the throat. As Thyroid is a gland it is important in our body when thyroid produces too much thyroid hormones then that condition is called hyperthyroidism and if thyroid gland produces less thyroid hormones then that condition is called hypothyroidism. Machine learning is one of the most important tools to classify the diseases nowadays whether a person has a disease or not like Cancer detection, kidney disease detection or Diabetes etc. Our project is to predict whether a person has Thyroid disease or not. Whether he has hypothyroidism or hyperthyroidism, or he is not suffering from thyroid disease.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130547043","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}
COVID-19, also known as 2019-nCoV, is no longer a pandemic but an endemic disease that has killed many people worldwide. COVID-19 has no precise treatment or remedy at this time, but it is unavoidable to live with the disease and its implications. By quickly and efficiently screening for covid, one may determine whether or not one has COVID-19 and thus limit the financial and administrative burdens on healthcare systems. This reality puts a huge demand on these countries' healthcare systems, especially in emerging nations, due to the poor healthcare systems around the world. Although the COVID-19 pandemic cannot be stopped by any licenced vaccine or antiviral medicine, there are other possible solutions that could lighten the burden of the virus on healthcare systems and the economy. The most promising approaches for usage outside of a clinical environment include non-clinical approaches like machine learning, data mining, deep learning, and other artificial intelligence technologies. Artificial intelligence (AI) approaches are increasingly being integrated into wireless infrastructure, real-time data collection, and end-user device processing. A positive and negative COVID-19 case dataset is used to validate artificial intelligence (AI) systems such decision trees, support vector machines, artificial neural networks, and naive Bayesian models. The correlation coefficients between various dependent and independent variables were examined to determine the strength of the relationship between the dependent features. The model was tested 20% of the time while being trained 80% of the time during the preparation phase. The Random Forest had the highest precision (94.99%), according to the evaluation of success.
{"title":"Covid-19 Patient Health Prediction Using Boosted Random Forest Algorithm","authors":"S. Saranya, S. Bobby","doi":"10.46632/daai/3/2/13","DOIUrl":"https://doi.org/10.46632/daai/3/2/13","url":null,"abstract":"COVID-19, also known as 2019-nCoV, is no longer a pandemic but an endemic disease that has killed many people worldwide. COVID-19 has no precise treatment or remedy at this time, but it is unavoidable to live with the disease and its implications. By quickly and efficiently screening for covid, one may determine whether or not one has COVID-19 and thus limit the financial and administrative burdens on healthcare systems. This reality puts a huge demand on these countries' healthcare systems, especially in emerging nations, due to the poor healthcare systems around the world. Although the COVID-19 pandemic cannot be stopped by any licenced vaccine or antiviral medicine, there are other possible solutions that could lighten the burden of the virus on healthcare systems and the economy. The most promising approaches for usage outside of a clinical environment include non-clinical approaches like machine learning, data mining, deep learning, and other artificial intelligence technologies. Artificial intelligence (AI) approaches are increasingly being integrated into wireless infrastructure, real-time data collection, and end-user device processing. A positive and negative COVID-19 case dataset is used to validate artificial intelligence (AI) systems such decision trees, support vector machines, artificial neural networks, and naive Bayesian models. The correlation coefficients between various dependent and independent variables were examined to determine the strength of the relationship between the dependent features. The model was tested 20% of the time while being trained 80% of the time during the preparation phase. The Random Forest had the highest precision (94.99%), according to the evaluation of success.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124434651","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}
Authentication is by password It is alphanumeric in nature. However, the user finds it Difficulty remembering long passwords Remember many times while running. instead of this. They create short, simple and insecure passwords. User data vulnerable to external attacks. Graphically Passwords offer a way out of this dilemma Passwords that are easy for users to remember and use Passwords, more secure. With Graphical password, user clicks on image instead of typing it. A text password containing alphanumeric characters. A New, more secure graphical password system Developed using image segmentation. Picture A segmentation system presents images to the user Here the user selects some grid on that image. If These points, entered in the correct order, user. The result is an alphanumeric password and Both graphical passwords worked around the same time, Graphical passwords were easy to obtain and remember. [1]As such, graphical passwords have been found to be harder to crack They are newly implemented and don't have many algorithms Designed to break them.
{"title":"Strengthen Password Using Image Authentication","authors":"","doi":"10.46632/daai/3/1/8","DOIUrl":"https://doi.org/10.46632/daai/3/1/8","url":null,"abstract":"Authentication is by password It is alphanumeric in nature. However, the user finds it Difficulty remembering long passwords Remember many times while running. instead of this. They create short, simple and insecure passwords. User data vulnerable to external attacks. Graphically Passwords offer a way out of this dilemma Passwords that are easy for users to remember and use Passwords, more secure. With Graphical password, user clicks on image instead of typing it. A text password containing alphanumeric characters. A New, more secure graphical password system Developed using image segmentation. Picture A segmentation system presents images to the user Here the user selects some grid on that image. If These points, entered in the correct order, user. The result is an alphanumeric password and Both graphical passwords worked around the same time, Graphical passwords were easy to obtain and remember. [1]As such, graphical passwords have been found to be harder to crack They are newly implemented and don't have many algorithms Designed to break them.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122451016","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}
Classical cryptographic schemes in use today are based on the difficulty of certain number theoretic problems. Security is guaranteed by the fact that the computational work required to break the core mechanisms of these schemes on a conventional computer is infeasible; however, the difficulty of these problems would not withstand the computational power of a large-scale quantum computer. To this end, the post-quantum cryptography (PQC) standardization process initiated by the National Institute of Standards and Technology (NIST) is well underway. In this paper, the energy consumption of PQC measurements are categorized based on their proposed cryptographic functionality. The results are used in order to identify the most energy-efficient schemes.
{"title":"Energy Consumption Analysis in Post Quantum Cryptography Using Multivariate Signature Algorithms","authors":"","doi":"10.46632/daai/3/2/30","DOIUrl":"https://doi.org/10.46632/daai/3/2/30","url":null,"abstract":"Classical cryptographic schemes in use today are based on the difficulty of certain number theoretic problems. Security is guaranteed by the fact that the computational work required to break the core mechanisms of these schemes on a conventional computer is infeasible; however, the difficulty of these problems would not withstand the computational power of a large-scale quantum computer. To this end, the post-quantum cryptography (PQC) standardization process initiated by the National Institute of Standards and Technology (NIST) is well underway. In this paper, the energy consumption of PQC measurements are categorized based on their proposed cryptographic functionality. The results are used in order to identify the most energy-efficient schemes.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126585218","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}
Visually impaired people find it difficult to identify unknown objects. Some objects may cause harm to them and in this pandemic situation it is not safe to touch each and every object even it is not harmful. The Project that we preferred is to find solution to overcome problems faced by visually-impaired people using object detection. Object detection is an image processing technology that helps us to retrieve data from an image and identify the object. This system can help to detect the objects with its characteristics with the use of image processing techniques. In this system some feature extraction algorithms like SURF are developed to extracting the important features of the object. After feature extraction the extracted values are compared and classified by the classifier algorithm like KNN. The overall concepts are developed and recognized by mat lab software.
{"title":"Assistance and Rehabilitation for Visually Impaired using Image Processing","authors":"","doi":"10.46632/daai/3/1/10","DOIUrl":"https://doi.org/10.46632/daai/3/1/10","url":null,"abstract":"Visually impaired people find it difficult to identify unknown objects. Some objects may cause harm to them and in this pandemic situation it is not safe to touch each and every object even it is not harmful. The Project that we preferred is to find solution to overcome problems faced by visually-impaired people using object detection. Object detection is an image processing technology that helps us to retrieve data from an image and identify the object. This system can help to detect the objects with its characteristics with the use of image processing techniques. In this system some feature extraction algorithms like SURF are developed to extracting the important features of the object. After feature extraction the extracted values are compared and classified by the classifier algorithm like KNN. The overall concepts are developed and recognized by mat lab software.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124522300","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}
R. M. Manjunath, Kumuda valli, Yathindra Sai Ganesh, Marzan G
Bioinformatics is a vast multifarious domain having a share of concepts from Mathematics, Computer Programming to Biological Sciences. It is the leading thrust area in research perspective. It demands knowledge of both Computers and Biology. Latterly has seen an exponential usage of Apps be it for educational purposes or for commercial use. Android app development is playing a key role in creating the demand for newer concepts, which has already dominated the Bio world. Bioinformatics, especially gene analysis has motivated the developers to create many apps related to the bio functionalities. But due to its vast nature and voluminous data, the development cycle is demanding more expertise from the developers. Various Bio-apps are in the market but are not sufficiently covering all the features. This article lists the existing bio-apps with usage analytics based on number of downloads. It strives to explain the conceptual model of Gendroid, a multipurpose bio-app with its prospective development challenges.
{"title":"Gendroid- A Conceptual Bio-Info Android App and Its Challenges","authors":"R. M. Manjunath, Kumuda valli, Yathindra Sai Ganesh, Marzan G","doi":"10.46632/daai/3/2/22","DOIUrl":"https://doi.org/10.46632/daai/3/2/22","url":null,"abstract":"Bioinformatics is a vast multifarious domain having a share of concepts from Mathematics, Computer Programming to Biological Sciences. It is the leading thrust area in research perspective. It demands knowledge of both Computers and Biology. Latterly has seen an exponential usage of Apps be it for educational purposes or for commercial use. Android app development is playing a key role in creating the demand for newer concepts, which has already dominated the Bio world. Bioinformatics, especially gene analysis has motivated the developers to create many apps related to the bio functionalities. But due to its vast nature and voluminous data, the development cycle is demanding more expertise from the developers. Various Bio-apps are in the market but are not sufficiently covering all the features. This article lists the existing bio-apps with usage analytics based on number of downloads. It strives to explain the conceptual model of Gendroid, a multipurpose bio-app with its prospective development challenges.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116448233","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}
The traditional robotic arm control method has strong dependence on the application scenario. To improve the reliability of the mobile robotic arm control when the scene is disturbed, this paper proposes a control method based on an improved proximal policy optimization algorithm. This study researches mobile robotic arms for opening doors. At first, the door handle position is obtained through an image-recognition method based on YOLOv5. Second, the simulation platform CoppeliaSim is used to realize the interaction between the robotic arm and the environment. Third, a control strategy based on a reward function is designed to train the robotic arm and applied to the opening-door task in the real environment. In this paper PPO algorithm is used to solve the result. The experimental results show that the proposed method can accelerate the convergence of the training process. Besides, our method can effectively reduce the jitter of the robotic arm and improve the stability of control.
{"title":"Mobile Robotic Arm for Opening Doors Using Proximal Policy Optimization","authors":"M. Kokila, G. Amalredge","doi":"10.46632/daai/3/2/20","DOIUrl":"https://doi.org/10.46632/daai/3/2/20","url":null,"abstract":"The traditional robotic arm control method has strong dependence on the application scenario. To improve the reliability of the mobile robotic arm control when the scene is disturbed, this paper proposes a control method based on an improved proximal policy optimization algorithm. This study researches mobile robotic arms for opening doors. At first, the door handle position is obtained through an image-recognition method based on YOLOv5. Second, the simulation platform CoppeliaSim is used to realize the interaction between the robotic arm and the environment. Third, a control strategy based on a reward function is designed to train the robotic arm and applied to the opening-door task in the real environment. In this paper PPO algorithm is used to solve the result. The experimental results show that the proposed method can accelerate the convergence of the training process. Besides, our method can effectively reduce the jitter of the robotic arm and improve the stability of control.","PeriodicalId":226827,"journal":{"name":"Data Analytics and Artificial Intelligence","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124779903","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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