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检索条件"任意字段=2023 International Conference on Robotics, Control and Vision Engineering, RCVE 2023"

共 1305 条记录，以下是71-80 订阅

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Electromechanical Conversion Reliability Testing Device of Electronic Remote Water Meter Based on Machine vision 2

Electromechanical Conversion Reliability Testing Device of E...

引用

2nd international Symposium on control engineering and robotics, ISCER 2023

作者： Wu, Xiaojie Fang, Yan Zhang, Ningning Chen, Guofu Shou, Xia Ying, Hanyan Institute of Flow Measurement Zhejiang Institute of Metrology Zhejiang Provincial Key Laboratory of Energy and Environmental Protection Measurement and Testing Hangzhou China

ISBN: (纸本)9798350336405

The reliability of electromechanical conversion is the key index that affects the quality of the direct-reading electronic remote transmission water meter. Aiming at the problems of low automation level and low detection efficiency of current detection methods, a set of electromechanical conversion reliability detection device for electronic remote water meter based on machine vision technology is designed. The device adopts the non-real flow automatic detection method, simulates the test flow through the servo motor control system, and automatically obtains the mechanical reading of the water meter through the machine vision technology, thus realizing the automatic detection of the electromechanical conversion performance. The experimental results show that the designed device has high degree of automation, high detection efficiency, and accurate and reliable results. © 2023 IEEE.

关键词： Reliability

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Towards Automated Regulation of Jacobaea Vulgaris in Grassland using Deep Neural Networks

Towards Automated Regulation of Jacobaea Vulgaris in Grassla...

引用

IEEE/CVF international conference on Computer vision (ICCV)

作者： Schauer, Moritz Hohl, Renke Vaupel, Dennis Bienhaus, Diethelm Ghobadi, Seyed Eghbal Univ Appl Sci Mittelhessen Giessen Germany

ISBN: (纸本)9798350307443

The highly poisonous ragwort (Jacobaea Vulgaris) is increasingly spreading, posing significant risks to agriculture, livestock, and nature conservation due to the production of toxic pyrrolizidine alkaloids (PAs). The current manual control methods, such as plucking weed, are labor-intensive and time-consuming. This paper introduces a workflow towards automated regulation of J. Vulgaris, which consists of the two independent tasks of deep learning-based monitoring and controlling. We aim to detect and control J. Vulgaris in an early growth stage before the plant can reseed, which challenges the data collection and the training of deep neural networks. Primarily we need to detect the green leaf rosettes on a green meadow. The main focus lies on the monitoring part with synthetic training data generation and a deep neural network-based labeling assistant.

关键词： Agriculture Annotations Computer vision Deep Learning Jacobaea Vulgaris Ragwort robotics Weed Detection

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Research of Neural Network Methods of Visual Defectoscopy of Metal Structures

Research of Neural Network Methods of Visual Defectoscopy of...

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2023 international conference on Industrial engineering, Applications and Manufacturing, ICIEAM 2023

作者： Chernikov, Alexander Smirnova, Elena Zhavoronkov, Oleg Peter the Great St. Petersburg Polytechnic University Higher School of Automation and Robotics St. Petersburg Russia Saint Petersburg State University Department of System Programming St. Petersburg Russia Computer Vision Systems Llc St. Petersburg Russia

ISBN: (纸本)9781665475952

The production of metal pipes is an important component of metallurgy and the entire industry as a whole. Traditional surface quality control is carried out by human inspectors, which is unsatisfactory due to low productivity, reliability and economy. Therefore, the introduction of an automatic visual inspection system into this production allows you to quickly find defects in products and reduce economic losses. To solve this problem, an algorithm based on the neural networks of the YOLOv5 and Unet architectures has been created, which allows finding the bounding frames of defects and their segmentation mask from the image. The created algorithm was applied to two control sites: mandrel defectoscopy and pipe defectoscopy. For mandrel defectoscopy, the accuracy for mAP 0.5 detection is 0.785, for iou_score segmentation - 0.562. For pipe defectoscopy, the accuracy for mAP 0.5 detection is 0.693, for iou_score segmentation - 0.526. © 2023 IEEE.

关键词： Computer vision

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A Noval Event-IMU Odometry Based on Quadtree-Accelerated Asynchronous Event Corner and Graph Optimization 5

A Noval Event-IMU Odometry Based on Quadtree-Accelerated Asy...

引用

5th international conference on robotics, Intelligent control and Artificial Intelligence, RICAI 2023

作者： Lv, Xianwei Ma, Xiaoguang School of Information Science and Engineering Northeast University Shenyang China Foshan Graduate School Northeast University Foshan China

ISBN: (纸本)9798350357950

Event cameras, a type of neuromorphic vision sensor, capture pixel-level intensity changes to generate asynchronous event streams with precise timestamps. They offered several advantages, including a high dynamic range, high temporal resolution (low latency), and freedom from motion blur. Leveraging event information and corresponding visual algorithms holded significant promise for the development of robotic autonomous systems. In this paper, we proposed an event-inertial odometry method based on asynchronous event corner detection and tracking. We introduced a novel approach for fast event corner detection using a quadtree-based method, ensuring a spatiotemporally uniform distribution of corners. Additionally, we presented a high-precision state estimation framework that combines IMU measurements and event corner observations through graph optimization. To assess the performance of our method, we conducted experiments using a publicly available dataset and compared our results with state-of-the-art (SOTA) methods. Our findings demonstrated that our approach excels in terms of both accuracy and speed. © 2023 IEEE.

关键词： Computer vision Event Cameras Odometry

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vision Robotic Manipulator Combined with Neural Radiance Field for Autonomous Real-time 3D Reconstruction 2

Vision Robotic Manipulator Combined with Neural Radiance Fie...

引用

2nd international Symposium on control engineering and robotics, ISCER 2023

作者： Wang, Xuwei Fang, Shuhua Wang, Jiyao Southeast University-College of Software Engineering Southeast University Suzhou China

ISBN: (纸本)9798350336405

We present a new method to achieve accurate and real-time 3D scene reconstruction based on monocular cameras on a vision robotic manipulator platform. To realize this, we use the initialization part of SLAM and the latest advances in N eRF (Neural Radiance Field), Instant-NGP, and, most importantly, the information from the robotic manipulator to acquire real-time camera pose. This work uses keyframe images with camera real-time pose obtained from the visual robotic manipulator. Thus, the problem that instant-NGP needs images with pose are solved on the platform of the robotic manipulator, reducing the time of secondary processing of pure images and, consequently, realizing real-time 3D reconstruction. © 2023 IEEE.

关键词： Cameras

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A Comparative Study of Pre-trained CNNs and GRU-Based Attention for Image Caption Generation 5

A Comparative Study of Pre-trained CNNs and GRU-Based Attent...

引用

5th international conference on robotics and Computer vision, ICRCV 2023

作者： Khan, Rashid Huang, Bingding Hassan, Haseeb Zaman, Asim Ye, Zhongfu University of Science and Technology of China Hefei College of Big Data and Internet SZTU Shenzhen China College of Big Data and Internet SZTU Shenzhen China College of Health Sciences and Environmental Engineering SZTU Shenzhen China Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei China

ISBN: (纸本)9798350326369

Image captioning is a challenging task involving generating a textual description for an image using good computer vision and natural language processing techniques. This paper proposes a deep neural framework for image caption generation using a GRU-based attention mechanism. Our approach employs multiple pre-trained convolutional neural networks as the encoder to extract features from the image and a GRU-based language model as the decoder to generate descriptive sentences. To improve performance, we integrate the Bahdanau attention model with the GRU decoder to enable learning to focus on specific image parts. We evaluate our approach using the MSCOCO and Flickr30k datasets and show that it achieves competitive scores compared to state-of-the-art methods. Our proposed framework can bridge the gap between computer vision and natural language and can be extended to specific domains. © 2023 IEEE.

关键词： Computer vision

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Spatial Mapping of light aircraft with stereo-vision camera for use on Unmanned Aircraft System for defect localisation

Spatial Mapping of light aircraft with stereo-vision camera ...

引用

international conference on Unmanned Aircraft Systems (ICUAS)

作者： Connolly, Luke O'Gorman, Diarmuid Garland, James Tobin, Edmond F. South East Technol Univ Dept Aerosp & Mech Engn Fac Engn Carlow Campus Carlow Ireland South East Technol Univ Dept Elect Engn & Commun Fac Engn Carlow Campus Carlow Ireland

ISBN: (纸本)9798350310375

Spatial mapping creates a 3D reconstruction of a visualised area to reproduce a perception of the environment. This can be applied in robotics for manoeuvring in environments where Global Navigation Satellite Systems (GNSSs) are inaccessible. Such devices capable of spatial mapping are stereo-vision cameras. These cameras possess two or more image sensors, simulating human binocular vision and giving it the ability to perceive depth. Using this hardware on an Unmanned Aircraft System (UAS) introduces new capabilities for autonomous navigation and unmanned control. This, in turn, introduces new possibilities for application. Such a use case would be for a General Visual Inspection (GVI) of aircraft in a hangar environment where access to GNSS is limited. Providing a flight plan to a UAS with a stereo-vision camera to assist with collision avoidance and to keep a consistent distance from the aircraft would provide a robust system for defect detection and localisation during a GVI.

关键词： Cameras

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Simulation of vision-based Tactile Sensors with Efficiency-tunable Rendering

Simulation of Vision-based Tactile Sensors with Efficiency-t...

引用

2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Sun, Yuhao Zhang, Shixin Shan, Jianhua Zhao, Lei Wang, Xiangbo Sun, Fuchun Yang, Yiyong Fang, Bin Anhui University of Technology School of Mechanical Engineering China Tsinghua University Institute for Artificial Intelligence Department of Computer Science and Technology Beijing National Research Center for Information Science and Technology Beijing100084 China School of Engineering and Technology Beijing100083 China Hebei University School of Quality and Technology Supervising Baoding China

ISBN: (纸本)9798350325706

vision-based tactile sensors (VBTS) leverages visual modality to present high-resolution tactile information. The vision-based sensing mechanism has good adaptability to robot manipulation because of available information capture and data processing. However, the simulation of VBTS is a challenging problem because it deals with computer graphics and elasto-plastic deformation. In this paper, we propose a simulation approach for VBTS using a rendering approach based on path tracing. The rendering method can be integrated with existing VBTS and robotic simulators for the simulation of robotic systems. In addition, this method can control the rendering efficiency and quality by controlling the number of voxels in the fitting deformation area to meet the requirements of efficient robot training. The experimental results verify that our method can provide high-quality images at low rendering efficiency or reduce image quality to improve rendering efficiency. Our work has the potential to advance the sim-to-real research on VBTS. © 2023 IEEE.

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Research on intelligent insect species identification based on computer vision 7

Research on intelligent insect species identification based ...

引用

7th international conference on Mechatronics and Intelligent robotics, ICMIR 2023

作者： Huang, Bin Nanchang Institute of Technology Jiangxi Nanchang330044 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

Image-based insect species identification is a comprehensive application of computer vision technology, image processing technology and pattern recognition technology to realize insect species identification. It is of great significance to find and identify crop insects in time and quickly, so as to take corresponding measures to prevent and control pests in time and reduce the losses caused by pests. In this paper, intelligent insect species identification based on computer vision is studied. For insect images, using feature fusion technology will obtain more comprehensive insect image features, which will greatly improve the recognition accuracy and improve the recognition efficiency of the system. In the learning process, firstly, a certain number of insect images are selected as training samples, and the feature vectors of insects are extracted as the input vectors of SVM(support vector machine) training, and the input vectors are learned to get the best classification model. The experimental results show that the average recognition rate of insects by feature fusion is 94.747%. The experimental results show that the research results of this paper provide theoretical and practical basis for intelligent insect species recognition technology based on computer vision. © 2023 SPIE. All rights reserved.

关键词： Support vector machines

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Robot automatic path-finding algorithm based on computer vision and neural network model 7

Robot automatic path-finding algorithm based on computer vis...

引用

7th international conference on Mechatronics and Intelligent robotics, ICMIR 2023

作者： Yang, Libo Guangdong University of Science and Technology Dongguan523083 China

ISBN: (数字)9781510668089

ISBN: (纸本)9781510668072

Motion control of mobile robot is the premise of completing all tasks, and trajectory tracking control, as an extremely important part of motion control, is the basis for robot to complete all tasks. For different fields, the problem background and application scenarios faced by robots are different, but in any application scenario, it is necessary to ensure that the mobile robot can track a given trajectory or target quickly and stably in the process of motion control, so as to realize real-Time trajectory tracking control. The path-finding method introduced in this paper is to optimize the traditional back propagation neural network (BPNN) from the perspective of structure and weight setting under the environment model established by grid method, and then, according to the characteristics of high-speed parallel operation of neural network, an automatic path-finding algorithm based on logical judgment and memory is proposed, which can achieve ideal results by combining it with the improved BPNN. The simulation results show that the algorithm can effectively overcome the influence of uncertain factors such as model error and external disturbance, and its trajectory tracking effect is better than the traditional trajectory tracking control algorithm. © 2023 SPIE. All rights reserved.

关键词： Neural networks

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