2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)最新文献_第4页

Robot Global Relocalization Based on Multi-sensor Data Fusion 基于多传感器数据融合的机器人全局再定位

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10092957

Shuai Dong, R. Lin, Wei-wei Zhao, Yu-hui Cheng

{"title":"Robot Global Relocalization Based on Multi-sensor Data Fusion","authors":"Shuai Dong, R. Lin, Wei-wei Zhao, Yu-hui Cheng","doi":"10.1109/RAAI56146.2022.10092957","DOIUrl":"https://doi.org/10.1109/RAAI56146.2022.10092957","url":null,"abstract":"In order to solve the problems of low localizable accuracy, slipping and “kidnapping”, which may lead to get “ LOST” in robot localization, a multi-sensor data fusion localization method that integrates the wheel encoder, the Inertial Measurement Unit (IMU), the optical flow s ensor a nd t he laser is proposed. Firstly, the Federal Kalman Filter (FKF) is used to fuse multi-sensor data information to obtain more accurate localization; Secondly, when the robot loses its global localization, the optical flow s ensor, t he r angefinder an d IM U ar e fu sed to obtain the localization as a priori for the prediction step in the resampling of Adaptive MonteCarlo Localization (AMCL). Finally, the Conditional Variational Autoencoder (CVAE) is used for training to further optimize the priori localization. The algorithm without correct initial values is converted into an algorithm with fuzzy localization. Experimental results based on real scenarios showed that the multi-sensor data fusion not only helped to obtain more accurate and stable location, but also significantly reduced the “LOST” problem in case of the robot being kidnapped compared to the pre-optimized AMCL algorithm.","PeriodicalId":190255,"journal":{"name":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133009828","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}

引用次数: 0

Application of Gaussian Process Regression Model in Industry 高斯过程回归模型在工业中的应用

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10092999

Zhimin Sun, Licai Zhong, Xueyan Chen, Jianghong Guo

引用次数: 0

Creation of an Afrikaans Speech Corpora for Speech Emotion Recognition 用于语音情感识别的南非荷兰语语料库的创建

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10092988

Michael Norval, Zenghui Wang

{"title":"Creation of an Afrikaans Speech Corpora for Speech Emotion Recognition","authors":"Michael Norval, Zenghui Wang","doi":"10.1109/RAAI56146.2022.10092988","DOIUrl":"https://doi.org/10.1109/RAAI56146.2022.10092988","url":null,"abstract":"The field of Artificial Intelligence (AI) and HumanComputer Interaction (HCI) has grown significantly in the last decade. Speech Recognition (SR) and more specifically Speech Emotion Recognition (SER) is still a growing field with quite a few academic and private companies doing research. Currently, SER is not specifically geared toward African-based languages. The paper is to show how to create an Afrikaans-based speech corpora to train a Neural Network (NN). Method-wise, speech samples are extracted from streamed broadcasts. A local Afrikaans Youtube channel is used. Care is taken that the ‘‘Creative Commons Attribution license (reuse allowed)’’ is always adhered to. In cases where the creative commons license is not available, authorization has been obtained. The speech clips are saved in.wav format. The emotions captured are Anger, Anticipation, Disgust, Joy, Sadness, Suprise, Fear and Trust. All data is anonymized. The recorded clips are verified by a second independent party and if required verified again by another. This makes sure that categorization is correct. The result is an Afrikaans speech corpus with roughly 800 speech clips. Finally, LTSM is applied to the dataset, and the new Afrikaans corpora yielded a detection accuracy of 58% and 74% with transfer learning.","PeriodicalId":190255,"journal":{"name":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134142729","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}

引用次数: 0

A Cartographic Framework for Autonomous Mobile Robot Using OpenStreetMap Data 基于OpenStreetMap数据的自主移动机器人制图框架

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10092973

Seoho Lee, Hongjun Kim

引用次数: 0

Assessment of a Consolidated Algorithm for Constrained Engineering Design Optimization and Unconstrained Function Optimization 约束工程设计优化与无约束函数优化的综合算法评价

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10093006

Stephen Oladipo, Yanxia Sun

{"title":"Assessment of a Consolidated Algorithm for Constrained Engineering Design Optimization and Unconstrained Function Optimization","authors":"Stephen Oladipo, Yanxia Sun","doi":"10.1109/RAAI56146.2022.10093006","DOIUrl":"https://doi.org/10.1109/RAAI56146.2022.10093006","url":null,"abstract":"For real-life optimization problems, methods with adequate capability in exploring the search space are crucial especially when having in mind the perpetual complexity of the problems. Consequently, presenting an effective algorithm to address these problems becomes imperative. The major objective of this work is to assess the application of a consolidated algorithm in addressing constrained and unconstrained function optimization problems. Though the flower pollinated algorithm (FPA) is commonly used, it does have its limitations, including being stuck at local minima, causing premature convergence, and creating imbalances between intensification and diversification. As the FPA operates, the solution to the optimization problem relies on communication with pollen individuals. Consequently, instead of leading pollens randomly, the FPA’s exploratory skills are boosted by employing the pathfinder algorithm’s (PFA) components to route them to much better locations in order to avoid local optima. For that reason, the PFA has been incorporated into the FPA in order to increase its performance. The efficacy of the proposed algorithm is tested using conventional mathematical optimization functions as well as two well-known constrained engineering design optimization problems. Experimental results showed that the suggested algorithm outscored its counterparts for both constrained and unconstrained optimization problems.","PeriodicalId":190255,"journal":{"name":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126750541","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}

引用次数: 0

Proposal of a Swimming Pool Drowning Detection System using Cameras and Raspberry Pi based on Machine Learning 基于机器学习的摄像机和树莓派泳池溺水检测系统的设计

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10092956

Christopher Urruchi, Daniel Cervantes-Chauca, Deyby Huamanchahua

{"title":"Proposal of a Swimming Pool Drowning Detection System using Cameras and Raspberry Pi based on Machine Learning","authors":"Christopher Urruchi, Daniel Cervantes-Chauca, Deyby Huamanchahua","doi":"10.1109/RAAI56146.2022.10092956","DOIUrl":"https://doi.org/10.1109/RAAI56146.2022.10092956","url":null,"abstract":"Drowning deaths represent the third leading cause of accidental deaths worldwide. This is because traditional techniques for the supervision and care of people, especially children, in large pools are inefficient or, in some cases, nonexistent. Nowadays, this problem has become a topic of interest for several researchers who seek to propose different methods of drowning detection. This research work seeks to propose the process to be followed to develop a drowning detection system in swimming pools using cameras and Raspberry Pi based on Machine Learning. To achieve the objective, the use of the Triple Diamond design methodology was proposed. In the development of the first diamond, the information was organized in a Lotus Blossom Diagram, then the problematic situation and the main objective were described. In the development of the second diamond, a bibliometric analysis was performed, searching for information with search equations and then sorting and filtering it, and finally including it in morphological matrices. As a result, an electrical diagram of the system and a flow diagram of the algorithm based on a Support Vector Machine were proposed.","PeriodicalId":190255,"journal":{"name":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128277379","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}

引用次数: 0

LTE Network Planning Using AI and AR 基于AI和AR的LTE网络规划

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10092986

Mohammad Taha, Mohammad Abu Shukur, Mohammad Atallah, Yahya Gosheh

{"title":"LTE Network Planning Using AI and AR","authors":"Mohammad Taha, Mohammad Abu Shukur, Mohammad Atallah, Yahya Gosheh","doi":"10.1109/RAAI56146.2022.10092986","DOIUrl":"https://doi.org/10.1109/RAAI56146.2022.10092986","url":null,"abstract":"In this paper, an optimal base station placement for a LTE cellular network is provided. The designed system relies on a web server that communicates with pre-trained machine learning models trained using measured data and deployed on MATLAB For training, a fingerprinting database has been created for a target RSSI versus the GPS coordinates as features in an outdoor and indoor environment on a multi floor buildings in the university campus. Gaussian Process Regression (GPR) has been used as a benchmark machine learning algorithm due to its outstanding performance. However, its performance was compared with different machine learning techniques in terms of computational complexity and accuracy. Validation of the system has shown that GPR outperformed the other techniques with mean square error of 4.3% at the expense of the time required for training. Moreover, the application has been provided with an augmented reality interface that shows the placed BS on the map along with the predicted RSSI value and the GPS coordinates. The whole system is designed on unity software and made available to mobile devices.","PeriodicalId":190255,"journal":{"name":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","volume":"149 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114519418","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}

引用次数: 0

Performance Comparison of PSO-based Informative Path Planners for Water Monitoring under Dynamic Scenarios 动态场景下基于pso的信息路径规划器的性能比较

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10093003

Micaela Jara Ten Kathen, Isabel Jurado Flores, D. Reina

引用次数: 0

A RNN Based Self-Learning Audio Generating Chatbot For French Language Learners 基于RNN的法语自学习语音生成聊天机器人

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10092995

Rifat Sarker Aoyon, Yamin Ara, Tahsin Anzum Baptee, Mehrin Afroz, Md. Tanzim Reza

{"title":"A RNN Based Self-Learning Audio Generating Chatbot For French Language Learners","authors":"Rifat Sarker Aoyon, Yamin Ara, Tahsin Anzum Baptee, Mehrin Afroz, Md. Tanzim Reza","doi":"10.1109/RAAI56146.2022.10092995","DOIUrl":"https://doi.org/10.1109/RAAI56146.2022.10092995","url":null,"abstract":"A chatbot is an artificial intelligence-based virtual conversational agent that is one of the most potential technologies in the modern era. There are so many sectors where chatbots are providing outstanding performance. This technology has the ability to be an assistant for those who are trying to learn a new language. That is why we have done research to make a chatbot based on an RNN algorithm in order to help people learn French. Although there are many online platforms available to learn French, many of these are not sufficient enough to learn a language as it is mandatory to have a conversational partner to practice a language. Without practicing a language with anyone, it is difficult for a person to keep memorizing a lot of vocabulary. French pronunciation rules are not the same as English. Therefore, we have added a feature for sending text along with audio messages and getting replies in French audio alongside text. Because of having these features, users will not only know the French vocabulary and grammatical rules but can also be introduced to French pronunciation systems and learn to speak French with a native French accent. The self-learning feature assists this chatbot to increase its capability of giving correct responses to the users day by day by having continuous conversations and removes the problem of collecting so much data to make this kind of chatbot. Also the paraphrasing feature will help users to get different replies to a particular question at different times, enriching their vocabulary and familiarizing them with the variety of replies to a particular question.","PeriodicalId":190255,"journal":{"name":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116834761","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}

引用次数: 0

Digital Transformation on Power Transmission Line Inspection using Autonomous Drone and Deep Learning 基于自主无人机和深度学习的输电线路检测数字化转型

2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI) Pub Date : 2022-12-09 DOI: 10.1109/RAAI56146.2022.10092983

N. Surantha, T. Iwao, Zhenwei Ren, H. Morishita

{"title":"Digital Transformation on Power Transmission Line Inspection using Autonomous Drone and Deep Learning","authors":"N. Surantha, T. Iwao, Zhenwei Ren, H. Morishita","doi":"10.1109/RAAI56146.2022.10092983","DOIUrl":"https://doi.org/10.1109/RAAI56146.2022.10092983","url":null,"abstract":"The electrical power generation industry is undergoing significant digital transformation in every aspect. One of the most important assets of this industry is the power transmission line (PTL) system. PTL system distributes electric power for residential and industrial uses. PTL requires regular inspections for early damage detection and maintenance to transmit high-voltage electric power efficiently and reliably. The detection and localization of damage across transmission equipment are crucial, as they help power transmission companies reduce maintenance expenses and prevent unexpected power outages. Traditionally, these inspections have been conducted by line crawling or with the assistance of a helicopter to plan for necessary repair or replacement works before any significant damage that could cause a power outage. These traditional solutions are slow, costly, and dangerous. The emergence of drones, high-resolution cameras, edge computing, and deep learning technology opens the opportunity for PTL inspection using drones. In this paper, the literature review is conducted as a preliminary study for our research. Moreover, the state-of-the-art of PTL technology, the general autonomous drone-based PTL inspection system, is being discussed. Finally, we summarize the research challenge and future direction of research in this field.","PeriodicalId":190255,"journal":{"name":"2022 2nd International Conference on Robotics, Automation and Artificial Intelligence (RAAI)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125909733","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}

引用次数: 0