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The underwater obstacle avoidance method based on ROS 3

The underwater obstacle avoidance method based on ROS

引用

2023 3rd international conference on Artificial intelligence and Industrial technology applications, AIITA 2023

作者： Zhang, Jingguo Lu, Zongqing Yu, Chunliang Shang, Yingda Chen, Yuxiang Tsinghua Shenzhen International Graduate School Shenzhen518071 China Institute of Deep-sea Science and Engineering Chinese Academy of Sciences Sanya572000 China

To achieve real-time obstacle avoidance for underwater robots, the artificial potential field method can be selected as the obstacle avoidance path planning algorithm. However, this method applies a large attractive force to the underwater robot when it is far from the target point, causing it to collide with obstacles. Additionally, when the underwater robot just enters the repulsion influence zone, the repulsion force that it experiences undergoes an abrupt change, resulting in a non-smooth obstacle avoidance path. Furthermore, developing the obstacle avoidance function based on software platforms such as MATLAB has a long algorithm verification cycle, and it is difficult to transfer the algorithm model to practical scenarios. Therefore, this paper proposes an underwater robot obstacle avoidance method based on ROS. Firstly, a dynamic adjustment factor is introduced into the potential field function of the artificial potential field method to redefine the obstacle influence zone, and an improved artificial potential field method is designed as the obstacle avoidance path planning algorithm for underwater robots. The experiment is conducted on the ROS simulation platform, and the results show that the improved algorithm can solve the two problems existing in the artificial potential field method. Secondly, nodes required for underwater robot obstacle avoidance are established based on the ROS operating system, and the improved artificial potential field method is integrated into the obstacle avoidance path planning node. Finally, the obstacle avoidance experiment of the Bluerov2 underwater robot is conducted in a pool, and the experimental results demonstrate that the proposed method can achieve real-time obstacle avoidance for underwater robots. © Published under licence by IOP Publishing Ltd.

关键词： MATLAB

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Comparative Analysis of Power Distribution in Conventional Grids and Deep Learning-Enhanced Smart Grid 3

Comparative Analysis of Power Distribution in Conventional G...

引用

3rd international conference on Electronics and Renewable Systems, ICEARS 2025

作者： Blessy, J. Janish Vinoth Raj, R. Nareshkumar, M. Daniel Kamalam, T. Infanta, J.Binu Allen Velammal Institute of Technology Chennai India Saveetha Engineering College Chennai India Saveetha School of Engineering Chennai India

ISBN: (纸本)9798331509675

This study explores the potential of deep learning methodologies to improve the efficiency and performance of power grids compared to conventional systems. The methodologies employed by machine learning algorithms in processing data sourced from smart meters, weather sensors, and energy markets are examined. The main focus of this study is on applications of energy sectors like demand forecasting, optimisation of generation and distribution, and real-time energy consumption management. The advantages of AI powered grids encompass refined demand forecasting, better integration of renewable energy sources, and optimised management of storage systems. This study illustrates the ability of intelligent grids to effectively manage supply and demand, leading to decreased costs and a minimised environmental footprint. The integration of learning-based smart grids in the context of demand response, emphasising the adaptation of energy supply to align with consumer behaviour is observed. Recurrent Neural Network algorithm is proposed to enhance the framework through the integration of Bagging and Boosting techniques in AI driven distribution systems. The results demonstrate that neural networks possess considerable capability to improve grid stability, decrease operational expenses, and alleviate the effects of climate change through more efficient energy systems. This study explores the comparative potentials of artificial intelligence in optimising smart grid energy systems alongside traditional grid frameworks. The findings indicate that the smart grid, enhanced by deep learning technologies, demonstrates significantly greater efficiency compared to conventional grids. © 2025 IEEE.

关键词： Demand response

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Artificial intelligence in Handwriting Analysis for Personality Trait Identification 3

Artificial Intelligence in Handwriting Analysis for Personal...

引用

3rd international conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Kotharkar, Riya Pradeep Rohini, T. Bnm Institute of Techonology Dept. of Ece Bengaluru India

ISBN: (纸本)9798331515911

Handwriting is a unique characteristic that distinguishes a person's identity and serves as a method for identifying various physical and psychological attributes of the writer. It reflects genuine personality traits, including behavior, emotional responses, self-perception, creativity, honesty, fears, and many other characteristics. In this paper, we propose a multi-layered approach for analyzing personality traits through handwriting analysis, utilizing a Voting Classifier, which integrates predictions from multiple base models to enhance overall performance. Specifically, our Voting Classifier combines Logistic Regression, Support Vector Machine, Random Forest Classifier, and Gradient Boosting Classifier. Each base model is carefully tuned using RandomizedSearchCV to optimize hyperparameters such as regularization strength for Logistic Regression, kernel type for Support Vector Machine, and number of estimators for Random Forest and Gradient Boosting Classifiers. The model's performance evaluation reveals impressive results, with a 93% accuracy in classifying handwriting samples. These findings highlight the model's effectiveness and its ability to handle various handwriting styles with consistency. The strong accuracy underscores the model's potential for real-world applications, offering trustworthy insights into personality traits through handwriting analysis. © 2025 IEEE.

关键词： Decision trees

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Research on Feature-based Image Recognition based on Convolutional Neural Network 3

Research on Feature-based Image Recognition based on Convolu...

引用

3rd international conference on Computer Science, Electronic Information Engineering and Intelligent Control technology, CEI 2023

作者： Ma, Qi Yang, Zeyu Zhang, Qingyao Yang, Yejia Ran, Haibin Bian, Yuhao College of Artificial Intelligence Tianjin University of Science and Technology Tianjin China

ISBN: (纸本)9798350372052

Recently, image identification has achieved promising performance and become the most essential component in real-life image-based applications through training a machine learning model. However, existing methods extract the features and the identification accuracy is almost depended on these features with extractions process, which is the fundamental process for learning models. Existing methods are almost concentrated on the utilization of these feature and ignore the process of extracting procedure. As far as we can concern, the image features contain numerous information and can assist the learning model to enhance the identification accuracy. In this work, we initially utilize a convolutional neural network to obtain the features in the feature space. Subsequently, an attention mechanism and the feature clustering are applying to optimize the extracted features. Finally, we evaluate our proposed model with most used methods in the identical environment setups. From our extensive experimental results, we can observe that our model outperforms compared methods with reasonable computation costs. © 2023 IEEE.

关键词： Convolutional neural networks

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robot navigation based on multi-sensor fusion 3

Robot navigation based on multi-sensor fusion

引用

3rd international conference on Signal Processing and Machine Learning, CONF-SPML 2023

作者： Deng, Mingyao Reading Academy University of Leeds of Electrical and Electronic Engineering No. 11 Jiangcui Road 529000 China

Over the past years, with the rapid development of artificial intelligence technology, mobile robots have appeared in more and more fields. Different types of robots play different roles. Due to the complex indoor environment, there are still many technical problems to be solved for robots. Aiming at the shortcomings of single sensor, low mileage accuracy, and poor security in traditional mobile robot navigation systems, we propose a mobile robot autonomous navigation system based on multi-sensor perception. This system integrates mainstream synchronous positioning and mapping algorithms, path planning algorithms, and positioning algorithms, and uses multiple sensors to compensate each other to achieve the automatic navigation function of the mobile robot. In order to verify the reliability of the method, We have carried out multi angle analysis in the simulation environment, and the experimental results show that the proposed navigation system is reliable in operation, high in mileage accuracy, and good in robustness, which broadens the application scenario of mobile robots. © Published under licence by IOP Publishing Ltd.

关键词： Mobile robots

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The Research on Lightweight Traffic Sign Recognition Algorithm Based on Improved YOLOv5 Model 3

The Research on Lightweight Traffic Sign Recognition Algorit...

引用

3rd IEEE international conference on Computer Communication and Artificial intelligence, CCAI 2023

作者： Liu, Tiande Dongye, Changlei Shandong University of Science and Technology College of Computer Science and Engineering Qingdao China

ISBN: (纸本)9798350335262

Traffic sign detection is an important research direction in object detection, which has been widely used in intelligent transportation system, driving assistance, automatic driving and other fields. In practical applications, traffic sign detection algorithms are required to complete detection and recognition tasks quickly and accurately, which requires the algorithm model to be lightweight to meet the deployment conditions. Aiming at the existing traffic sign detection problems, a lightweight traffic sign detection network based on YOLOv5s model was constructed, which improved the detection performance of the network model on the premise of guaranteeing the computing speed. In order to ensure lightweight, YOLOv5s model was selected. Firstly, Dense CSP Module (DCM) was designed to enhance the effect of feature fusion. At the same time, the feature pyramid is improved, and reduced the number of parameters in the model. Experimental results show that compared with the original algorithm, the detection efficiency of the proposed algorithm is improved by 5.28%, and the experimental results on multiple data sets show obvious improvement effect. This is a lightweight model that works well in the area of traffic sign detection. © 2023 IEEE.

关键词： Object detection

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Script2Graph: Auto-construct Screenplay Text World by Mining Contextual Information 3

Script2Graph: Auto-construct Screenplay Text World by Mining...

引用

3rd IEEE international conference on Software Engineering and Artificial intelligence, SEAI 2023

作者： Wang, Depei Cheng, Lianglun Liu, Hongwei Li, Ruihao Wang, Huilin Liu, Hongrui Guangdong University of Technology School of Automation Guangzhou China Guangdong University of Technology School of Computer Science and Technology Guangzhou China Tianjin Foreign Studies University Tianjin China Guangdong University of Technology School of Physics and Optoelectronic Engineering Guangzhou China Hanshan Normal University Chaozhou China San Jose State University San Jose United States

ISBN: (纸本)9798350337952

With the rapid development of artificial intelligence and the continuous emergence of innovative technologies, its application in movie scenes has gained attention. Meanwhile, the application of natural language processing techniques in movie scripts has gradually attracted the attention of researchers, making text information extraction more intelligent and convenient. However, most of the previous works for unstructured script processing ignore the theoretical guidance of computational language and lack the framework of knowledge schema. Therefore, we propose Script2Graph method based on text world theory to solve unstructured text information extraction and knowledge organization, and realize the automatic construction of script text world. Our experiments demonstrate that the method is effective in extracting text world elements and using high-quality information in downstream applications. © 2023 IEEE.

关键词： Computational linguistics

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AI-Powered Decision Making in Management: A Review and Future Directions 3

AI-Powered Decision Making in Management: A Review and Futur...

引用

3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Ramachandran, K.K. Karthick, K.K. Semwal, Amit Singh, Sardar Parminder Al-Hilali, Aqeel A. Alazzam, Malik Bader DR. G. R. D. College of Science Management/Commerce/International Business India Dr. G. R. Damodaran College of Science Department of Management Science Coimbatore14 India Uttaranchal University Uttaranchal Institute of Technology India Sr University School of Business Telangana Warangal India Al-Farahidi University Medical Technical College Baghdad10021 Iraq Ajloun National University Information Technology College Jordan

ISBN: (纸本)9798350399264

Artificial intelligence (AI) tools have developed to the point where they are now integrated into systems that support decision-making in practical settings and have a significant influence on that decision-making. This paper discusses decision-making theories, artificial intelligence (AI) technologies, and the sensible decision systems that derive fromthe blending of these ideas. This paper reviews the current state of AI-powered decision making in management and discusses future directions for research in this area. The review covers various applications of AI in management, including decision support systems, predictive modeling, and optimization. The benefits and limitations of using AI in decision making are also discussed. The paper concludes with a discussion of future research directions, including the integration of AI with other technologies, the use of explainable AI, and the need for interdisciplinary research. © 2023 IEEE.

关键词： Decision making

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The Role of Internet of Things in Developing Competitive Healthcare Devices: A Case Study in the Digital Healthcare Industry 3

The Role of Internet of Things in Developing Competitive Hea...

引用

3rd international conference on Artificial intelligence and Smart Energy, ICAIS 2023

作者： Yamaganti, Rohita Jyothi, P. N. Siva Manjari, S. Usha Sreenidhi Institute of Science and Technology Dept of It Hyderabad India

ISBN: (纸本)9781665462167

The transformation of the healthcare industry is being aided in part by technological advancements, increases in consumer demand, and other causes. This paradigm of providing medical care has been significantly disrupted by the introduction of digital healthcare apps, which replace the traditional method of one patient speaking directly with another. Apps similar to these enable patients to schedule appointments and connect with their physicians regardless of geographic location or the passage of time. Customers now have improved access to, and more control over, the purchase decisions they make, which enables them to easily switch to a different digital healthcare provider. On the other hand, very little is known about the industry as a whole and how the transition from traditional to digital healthcare is moving the balance of power away from physicians and toward patients. Because of the proliferation of digital technologies, substantial progress has been made in the medical field. The purpose of this research was to investigate recent developments in healthcare-based Internet of Things (IoT) technology, namely topologies, platforms/architectural models and taxonomies, service applications, and industry trends. This study has also analyzed the options that were based on HIoT. This article has also reviewed the most recent developments in HIoT research as well as the numerous problems and roadblocks that need to be overcome in order to successfully combine healthcare technology with IoT modernization. © 2023 IEEE.

关键词： Internet of things

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Three-Phase Inverter Fault Diagnosis Based on MTF-ResNet 3

Three-Phase Inverter Fault Diagnosis Based on MTF-ResNet

引用

3rd international conference on Artificial intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Xie, Zewen Chen, Yucheng Wang, Wu Han, Qunyong School of Electrical Engineering Automation Fuzhou University Fuzhou350108 China School of Information Engineering Zhangzhou Institute of Technology Zhangzhou363000 China School of Smart Manufacturing Zhangzhou Institute of Technology Zhangzhou363000 China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

For the problems of modeling difficulties and signal feature extraction in inverter open-circuit fault diagnosis methods, the methods based on machine learning and deep learning still have limitations in practical applications. In this paper, a three-phase inverter fault diagnosis method based on Markov variational field and residual convolutional network is proposed. The method encodes the phase voltage signal output from the inverter by MTF to generate a two-dimensional image with timing information and state migration information, avoiding the problem of signal information loss when directly converting voltage or circuit signals into one-dimensional or two-dimensional images. At the same time, the method uses ResNet to process MTF images to extract fault features of phase voltage signals and enhance the propagation of feature information so that the feature information can be fully utilized and accurate fault classification and identification can be achieved. The experimental results show that the proposed method can effectively identify 22 open-circuit fault types of three-phase inverters with a diagnostic accuracy of 98.10%. © 2023 SPIE.

关键词： Failure analysis

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