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检索条件"任意字段=International Conference on Advances in Science, Engineering and Robotics Technology"

共 47833 条记录，以下是1141-1150 订阅

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Hot Rolling Finishing Mill Interstand Strip Image Classification Based on Simple Convolutional Neural Network

Hot Rolling Finishing Mill Interstand Strip Image Classifica...

引用

2024 lEEE international conference on Advanced Information, Mechanical engineering, robotics and Automation, AIMERA 2024

作者： He, Wanzhang Sun, Wei Wang, Xiaochen Yang, Quan Yan, Shuzong Zhang, Tao Liu, Bo Ren, Yi University of Science and Technology Beijing National Engineering Technology Research Center of Flat Rolling Equipment Beijing China Angang Steel Company Limited Steel Branch of Angang Steel Company Limited Hot Rolling Department of Bayuquan Liaoning China

ISBN: (纸本)9798350343335

The existing strip deviation and control system for finishing rolling stands has achieved automated detection and correction of strip deviation. However, challenges arise in the harsh industrial site environment, including heavy water vapor mist and rack shaking, resulting in low-quality strip images and the potential for missed or incorrect detections. To address these challenges, this paper develops ResNet10 and GoogleNet models based on convolutional neural networks to achieve rapid strip image feature classification. A dataset of strip images collected at the rolling site is established, incorporating grayscale features. Experimental results demonstrate an impressive image classification accuracy of 98.8% and a swift classification time of only 3 ms. This research provides a theoretical foundation and empirical evidence for subsequent image enhancement and edge detection steps. © 2024 IEEE.

关键词： Convolutional neural networks

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Application of RPA technology in The Digital Transformation of Commercial Vehicles

Application of RPA Technology in The Digital Transformation ...

引用

2023 international conference on Frontiers of robotics and Software engineering, FRSE 2023

作者： Gao, Xue Zhang, Lu Mao, Heling Co. Ltd Prospective Business Department Tianjin China

ISBN: (纸本)9798350301113

The field of commercial vehicles is undergoing digital transformation. With the rapid development of Chinese automobile industry, industry data accumulation has reached the application level of big data, resulting in problems such as large amount of commercial vehicle data, heavy workload of data governance and data maintenance, strong repeatability and tedious. Based on this, this paper takes the concept of RPA(Robotic Process Automation) robot as the entry point, and proposes the application of RPA technology in data governance of commercial vehicles to help the digital transformation of commercial vehicles. This solution can improve the efficiency and accuracy of data governance, free the labor force, and make the data governance task more high-quality and efficient. © 2023 IEEE.

关键词： Commercial vehicles

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An In-Depth Exploration of Deep Reinforcement Learning Techniques for Game Playing

An In-Depth Exploration of Deep Reinforcement Learning Techn...

引用

2024 international conference on Cybernation and Computation, CYBERCOM 2024

作者： Nancy, P. Babu, M. Devipriya, A. Rosaline, R. Anto Arockia Prabhu, M. Ramkumar SRM Institute of Science and Technology Kattankulathur Campus Department of Computing Technologies Chengalpattu India Rajalakshmi Engineering Çollege Department of Information Technology Thandalam Chennai602 105 India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Electronics and Communication Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798331542344

This paper presents a brief survey of the approaches under the DRL umbrella for game playing and a discussion of the problems and the advances that have been witnessed in this promising research line. It is well understandable that the inputs are highly dimensional and the game environment is dynamic and hence the model described above incorporated both CNNs and RNNs. Other components of the methodology were the HRL that started by deconstructing a task into sub-Tasks and then the sub-Tasks were directed by a master policy. The DRL agents were tested on different platform environments: Specific and steady-build games and platforms and then to evaluate its performance, learning effect, and or its ability to generalize. It was found that the proposed methods were reasonably close to the other effective existing methods;in addition, the time required to train the model was less and the percentage of positive results in the games were also good showing an acceptable generality. The study has also has also extended the prior work on transfer learning as well as the efficient rewarding exploration approach to counter negative impacts of limited rewards and computational time. The data generated by this work contributes to the Doctoral study assessment and is relevant to various DRL themes and can be applied for robotics and AS fields based on AI. In conclusion, the authors repeat their imperative for future work on expanding DRL approaches that are effective on a large scale, the limitations of application to multi-Agent systems, and the transferability of learnt behaviour to improve the AI elements of game playing that is not limited to. © 2024 IEEE.

关键词： Deep reinforcement learning

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A Chatbot Assistant for Early Detection and Management of Sugarcane Diseases 2

A Chatbot Assistant for Early Detection and Management of Su...

引用

2nd IEEE international conference on advances in Information technology, ICAIT 2024

作者： Sarala, R. Vishnu Varthini, A. Swetha Raji, T. Department of Computer Science and Engineering Velammal College of Engineering and Technology Madurai India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383867

The Poaceae family's sugarcane, which has a high sucrose content, is an important resource used to make jaggery, white sugar, and byproducts like bagasse and molasses. Meanwhile, these Sugarcanes are getting largely affected and unproductive due to diseases making early detection crucial. This paper has bring forward a deep-learning framework which identifies the vitality of sugarcane plants by examining their physical traits. The market has foreseen a huge demand for Sugarcane plants therefore examining sugarcane diseases is crucial and the main hurdle for this is posed by varying monsoon seasons and other climatic changes. To tackle this hurdle, the authors put forward a solution which includes examining the staging of some pre-trained deep learning models, specifically VGG19 and ResNet50 to detect disorder in Sugarcane plants. Error rates and Performance metrics are checked for measuring overall efficiency. A graphical analysis comparing the models based on their sensitivity is also included. © 2024 IEEE.

关键词： Plant diseases

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Unforgettable Password Generation Using LoRA Fine-Tuned Large Language Model

Unforgettable Password Generation Using LoRA Fine-Tuned Larg...

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2024 international conference on advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Sameer, Mohammed Sudharsan, K. Benazir Begum, A. Hindustan Institute Of Technology And Science Dept.of Computer Science & Engineering Chennai India

ISBN: (纸本)9798350364828

In response to the challenges posed by complex and hard-to-remember passwords in traditional authentication systems, this research introduces an innovative approach leveraging Low Rank Adaption (LoRA) fine-tuned Large Language Models (LLMs) to generate natural language-like strong passwords. Focused on striking a balance between usability and security, proposed system methodology employs smaller-sized pre-trained LLMs, adapted using LoRA fine-tuning, to produce passwords that are both strong and memorable. By addressing the limitations of current password generation practices, proposed system framework aims to encourage user adoption of secure practices, contributing to a positive societal impact through improved cybersecurity hygiene. The proposed solution involves deploying a fine-tuned LLM and serving them through an frontend web UI which emphasizes resource efficiency scalability of deployment of such model, and ease of using the generated passwords in real life authentication purposes fostering good cybersecurity practices among non-technical users. © 2024 IEEE.

关键词： Authentication

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Research on Attitude Control of Launch Vehicle at Ascent Stage Through Reinforcement Learning 3

Research on Attitude Control of Launch Vehicle at Ascent Sta...

引用

3rd international conference on Innovations and Development of Information Technologies and robotics, IDITR 2024

作者： Zhou, Shou Bai, Xibin Zhang, Shifeng Yang, Chengye College of Aerospace Science and Engineering National University of Defense Technology Changsha410073 China

ISBN: (纸本)9798350385694

Focusing on the problem that existing control methods of launch vehicle have insufficient adaptability to the uncertainty in actual flight, an attitude control method of launch vehicle at ascent stage through reinforcement learning (RL) is proposed in this paper. Firstly, a public recorded launch vehicle named Ares-I is taken as the research object, and its dynamic model is built in the specific reference frame. Then, an RL framework based on Soft Actor Critic (SAC) algorithm is constructed for attitude control of Ares-I and a reward function considering the tracking error, trajectory stability and training speed is designed. Finally, through offline training, an RL based attitude controller of Ares-I is proposed. The simulations show that this method improves the control accuracy by an order of magnitude compared with the traditional PID controller. © 2024 IEEE.

关键词： Reinforcement learning

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Fine Tuning Swimming Locomotion Learned from Mosquito Larvae

Fine Tuning Swimming Locomotion Learned from Mosquito Larvae

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2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Rajbhandari, Pranav Dhileep, Karthick Ravi, Sridhar Sofge, Donald Carnegie Mellon University Department of Computer Science PittsburghPA United States School of Engineering and Technology University of New South Wales Canberra Australia Naval Research Laboratory WashingtonDC United States

ISBN: (纸本)9781665481090

In prior research, we analyzed the backwards swimming motion of mosquito larvae, and created a parametrized approximation in a Computational Fluid Dynamics simulation. Since the parameterized swimming motion is replicated from observed larvae, it is not necessarily the most efficient locomotion. In this project, we further optimize this swimming locomotion for the simulated platform, using Reinforcement Learning to guide local parameter updates. Since the majority of the computation cost arises from the Computational Fluid Dynamics model, we additionally train a deep neural network to replicate the forces acting on the swimmer model. We find that this method is effective at performing local search to improve the parameterized swimming locomotion. © 2024 IEEE.

关键词： Computational fluid dynamics

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HTSA: A Hybrid Tree Seed Algorithm based on Differential Evolution with Dynamic Population Diversity Maintenance 4

HTSA: A Hybrid Tree Seed Algorithm based on Differential Evo...

引用

4th international conference on Artificial Intelligence, robotics, and Communication, ICAIRC 2024

作者： Han, Dongliang Chang, Hui Wang, Xuance Chen, Mengyao Ji, Yvzhu Hao, Xinran Zhang, Shengwei Cui, Hao Jilin University of Finance and Economics School of Management Science and Information Engineering Changchun China Zhengzhou University of Light Industry College of Electrical and Information Engineering Zhengzhou China Henan University of Science and Technology Modong Polytechnic Faculty Luoyang China

ISBN: (纸本)9798331531225

Based on the problem of Tree Seed Algorithm (TSA), this paper proposes a Hybrid Tree Seed Algorithm (Hybrid-Tree Seed Algorithm, HTSA) based on Differential Evolution and Dynamic Population Diversity Maintenance. HTSA effectively overcomes the limitations of the original TSA by introducing key enhancement mechanisms. By combining Bernoulli mapping initialization, HTSA ensures that the population distribution is more balanced and efficient compared to the stochastic mapping of TSA. Moreover, the introduction of a positional update formula inspired by the Sparrow Search Algorithm in the seed updating enhances population diversity and convergence, especially in the late optimization stages. Integration with Differential Evolution (DE) further enhances global exploration capabilities. Together, these modifications address issues such as premature convergence and sensitivity to local optimal values in *** experiments showed that HTSA outperformed TSA,EST-TSA and other benchmark algorithms, showing significant advantages in optimization power, convergence rate and population diversity. © 2024 IEEE.

关键词： Anthropogenic

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Ensembled Classifier-Based Evolutionary Algorithm for Dynamic Disassembly Line Balancing

Ensembled Classifier-Based Evolutionary Algorithm for Dynami...

引用

2023 international conference on Frontiers of robotics and Software engineering, FRSE 2023

作者： Cui, Hao Fang, Yilin Wuhan University of Technology School of Information Engineering Wuhan China

ISBN: (纸本)9798350301113

This paper analyzes the dynamic disassembly line balancing problem based on product state uncertainty and regards it as a dynamic multi-objective optimization problem to solve. In dynamic multi-objective optimization problems, it is important to quickly track the Pareto optimal set and respond quickly to the changing environment. Domain generalization has been proved to have good adaptive ability for different environments. Therefore, this paper proposes an ensembled classifier algorithm based on domain generalization to deal with the dynamic disassembly line balancing problem. The algorithm uses the technique of domain generalization to train an ensembled classifier before the arrival of a new environment by using historical environment knowledge. The performance of the algorithm is improved by generating high-quality initial populations. Finally, based on a set of problem examples of different sizes and environmental similarities generated in this paper, and by comparing this algorithm with several latest comparative algorithms, the effectiveness of the algorithm is verified for the dynamic disassembly line balancing problem. © 2023 IEEE.

关键词： Evolutionary algorithms

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A Convenient Calibration Method for Robot Hand Eye System Without External Calibration Objects

A Convenient Calibration Method for Robot Hand Eye System Wi...

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2024 IEEE international conference on robotics and Biomimetics, ROBIO 2024

作者： Zhou, Wei Ji, Yuan Zhang, Juntai Ma, Cui Yang, Fan He, Kai Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Shenzhen Key Laboratory of Precision Engineering Shenzhen518055 China

ISBN: (纸本)9781665481090

For the hand eye system calibration problem of inspection robot equipped with dual robotic arms and RGB-D camera, a simplified joint calibration method based on deep learning is proposed. It eliminates the need for external systems and calibration boards, resolving the calibration of the dual robotic arms and the extrinsic calibration of the RGB-D camera within the hand eye system of the inspection robot. By utilizing nonlinear optimization, it effectively reduces measurement noise and minimizes the propagation and influence of calibration errors in the coordinate transformation. Experimental results demonstrate that the proposed method achieves an average calibration error of 0.5mm for the dual robotic arms, and a minimum calibration error of 1.2mm for the camera's extrinsic parameters. Consequently, it significantly enhances the hand eye localization accuracy of the inspection robot during task execution. The innovative approach holds promising potential for improving the practical application of inspection robots. © 2024 IEEE.

关键词： Robotic arms

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