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Research on Recognition of Grasping Arbitrary Objects by Autonomous Mobile robot Based on YoloX-Tiny 4

Research on Recognition of Grasping Arbitrary Objects by Aut...

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4th Asia-Pacific conference on Communications Technology and computer Science, ACCTCS 2024

作者： Sun, Yunxiang Wang, Xiuping Zhu, Weiwei Zhejiang Gongshang University Department of Electronic and Information Engineering Zhejiang Hangzhou310000 China Fuzhou University Fuzhou350000 China

ISBN: (纸本)9798350359985

As intelligent manufacturing enters a new era, autonomous mobile robots have entered a stage of high-quality development. To propose 3D positioning that better meets the needs of arbitrary position capture in the manufacturing industry, we need to focus on innovative ideas based on deep learning. Based on the dynamic evolution of RGB-D camera development, the theoretical analysis framework of 3D positioning development is built according to the internal logic of data-driven. Researchers explain the 3D positioning development mechanism jointly generated by depth model and pose estimation related to RGB-D camera and YoloX-Tiny. In addition, we will continue to explore the possibility of switching to high-image-quality development from the perspective of changing image quality and experimentally deriving 3D positioning. the purpose of developing this technology is to provide the desired results for the manufacturing industry, and researchers are committed to continuously improving the success rate and efficiency of grasping. therefore, we take a series of measures, including object identification and positioning control based on deep information quality inner loop, constructing the interaction and coordination mechanism between the vision system and robot, and establishing the evaluation system of grasping performance and user satisfaction to realize the high-quality development of technology. It will boost intelligent manufacturing and meet the needs of the manufacturing industry. © 2024 IEEE.

关键词： Smart manufacturing

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Research on improvement strategy of detr real time object detection algorithm for small devices 4

Research on improvement strategy of detr real time object de...

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4th International conference on computer vision, Application, and Algorithm, CVAA 2024

作者： Gao, Chao Gao, Jing Cao, Lili Zhao, Long Gao, Shaojie School of Information Engineering East University of Heilongjiang Harbin China School of Computer and Information Engineering Heilongjiang University of Science and Technology Harbin China Gannan County Second Middle School Qiqihar China Wuxi Vocational Institute of Commerce Wuxi China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

With the rapid development of deep learning technology, object detection, as an important task in the field of computer vision, has also been widely applied in the ROS[1](robot Operating System) robot field. ROS, as an open-source robot operating platform[1], provides a favorable operating environment for object detection algorithms. this article studies the improvement strategy of real-time object detection algorithm (RT-DETR) [2] for small devices, which provides a better solution for the field of robotics. through the application analysis of the RT-DETR[2] algorithm, we found that there are certain issues with detection accuracy and efficiency, as well as the ability to detect small objects, when the performance of small devices is limited. Especially when the camera is not in focus or the image is ghosted, the issues of detection accuracy and efficiency are particularly prominent. For this purpose, we propose a dynamic and irregular deformable convolution kernel strategy to address the performance issues of small edge devices in terms of detection accuracy. In response to efficiency concerns, we propose an enhanced non-linear network structure to achieve greater non-linear capability with fewer parameters applied during the operation process. Finally, we combine the two methods to form a DenNet network (Deformable and Enhanced Nonlinear Convolutional Kernel Networks). through experimental verification, our improvement strategy can greatly improve the detection accuracy and efficiency of small devices, solve the efficiency problem of insufficient performance of small devices, and has important practical application value. © 2025 SPIE.

关键词： robot Operating System

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Visual Defect Detection and Analysis of Digital robot Based on Virtual Artificial Intelligence Algorithm 4

Visual Defect Detection and Analysis of Digital Robot Based ...

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4th International conference on Machine Learning and Big Data Analytics for IoT Security and Privacy, SPIoT 2023

作者： Qiao, Lisha Zhang, Xiao He, Shun Guilin University of Electronic Technology Guangxi Beihai536000 China Northwest University Shaanxi Xi'an710127 China Kashgar Armed Police Detachment Xinjiang Uygur Autonomous Region Kashgar844000 China

the current research background of digital robot visual defect detection focuses on the application of virtual artificial intelligence algorithms. Convolutional neural networks (CNNS) perform well in the field of image processing and can learn and extract image features, which provides a more refined analysis ability for the visual defect detection of digital robots. therefore, this paper focuses on the application of convolutional neural networks in digital robot vision defect detection, and explores the main processes of data collection and preprocessing, feature extraction, model training and defect detection in detail. Finally, the results of simulation experiments are as follows: Compared with traditional methods that rely on edge detection or threshold segmentation, the optimized defect detection accuracy rate is increased by 11.4%, and the image detection speed is increased by about 33.9%. the research results have important practical significance for improving the quality control of industrial manufacturing, which can not only improve the quality of products, but also adapt to the constant changes of the production line. © 2024 the Authors.

关键词： robot vision

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Research of Adaptive three kinds Education robot Based on Large Model Framework 4

Research of Adaptive Three kinds Education Robot Based on La...

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4th International conference on computer vision and Pattern Analysis, ICCPA 2024

作者： Lyu, Wenbo Min, Chenxi Wang, Zhennan Yin, Jiajun Liu, Baoshuai Saxo Fintech Business School University of Sanya Sanya572000 China

ISBN: (纸本)9781510682528

this article aims to design a three kinds real-time binocular vision detection system based on the ppdet target detection large model of the Paddlepaddle framework to improve the recognition capabilities and efficiency of smart classroom education robots. Firstly, an in-depth study was conducted on the theories related to binocular stereo vision, including camera models, binocular ranging principles, binocular camera calibration stereo correction, etc. then it introduces the selection of hardware platform, binocular vision system image preprocessing, FPGA acceleration of stereo matching algorithm, and real-time comparison of stereo vision implementation. Next, the expert experience was used to label the face status of teachers and students in the smart classroom into three categories, and the processed data was trained based on the ppdet target detection large model, and the model was tested. Finally, experimental verification was conducted through a real-life application scenario of a binocular patrol robot. Experimental results show that the binocular vision system module of the smart classroom inspection robot can effectively reshape visual data to improve target recognition accuracy. © 2024 SPIE.

关键词： Educational robots

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Generative Data Augmentation with Liveness Information Preserving for Face Anti-Spoofing 24

Generative Data Augmentation with Liveness Information Prese...

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4th Annual International conference on Multimedia Retrieval (ICMR)

作者： Chen, Changgu Li, Yang Zhang, Jian Liu, Jiali Wang, Changbo East China Normal Univ Sch Comp Sci & Technol Shanghai Peoples R China Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9798400706028

Face anti-spoofing is a critical aspect of ensuring security in the context of human-robot interaction and collaboration. Recently, disentangled-based data augmentation methods have achieved great success in face anti-spoofing tasks. the underlying assumption of those methods is that the liveness information could be completely disentangled and the labeling of the augmented data could totally depend on the liveness-related feature branch. However, we observe that it is almost impossible to extract the liveness-related information completely, which makes the current labeling strategy inaccurate. In this paper, we rethink the disentangling process and propose a novel generative-based data augmentation framework without forcing liveness information encoded into any specific feature space. Specifically, the original images are decomposed into statistic feature space and spatial feature space with liveness information preserving. With these two feature spaces, synthesized liveness-preserving images are generated with the Cartesian product to further approach the distribution of real face anti-spoofing data. Along with the original samplings, the augmented data are fed to a ResNet-based classifier with our proposed pseudo-label strategy for liveness information augmentation. Both qualitative and quantitative experiments demonstrate promising results to show the effectiveness of our proposed method.

关键词： Facial Security Human-computer Interaction computer vision

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Research on the method of accurate recognition of target object pose by intelligent robot using CDPN in visual guidance 4

Research on the method of accurate recognition of target obj...

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4th International conference on computer vision and Data Mining, ICCVDM 2023

作者： Qiao, Haiye Zhang, Zhen Xu, Xiansheng Foshan City Foshan Polytechnic Foshan China

ISBN: (纸本)9781510674448

the current vision-guided relevant target object pose recognition methods applied in intelligent robots have the problems of poor accuracy and simple application scenarios, so the study optimized its network on the basis of the de-entangled pose network of coordinates and experimentally verified it. the experimental results show that in the analysis of the network test results, the average value of the improved pose recognition estimation network is 92.05%, which is significantly higher than the 89.86% of the original de-entangled pose network of coordinates, and is significantly higher than the other comparison methods. In the analysis of the network output visualization results, the study uses the data with 5px as the threshold to visualize and display, at which time the accuracy of all objects exceeds 90%. And its overall success rate reaches 92% when it is practically applied in intelligent robots. Comprehensively, the improved target object attitude estimation network proposed by the study has the effectiveness and practicability, which can effectively improve the degree of grasping intelligence of intelligent robots. © 2024 SPIE.

关键词： Intelligent robots

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Affordance Perception by a Knowledge-Guided vision-Language Model with Efficient Error Correction 4th

Affordance Perception by a Knowledge-Guided Vision-Languag...

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4th International conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2024

作者： Burghouts, Gertjan J. Schaaphok, Marianne van Bekkum, Michael Meijer, Wouter Hillerstrüm, Fieke van Mil, Jell TNO The Hague2597 AK Netherlands

ISBN: (纸本)9789819787043

Mobile robot platforms will increasingly be tasked with activities that involve grasping and manipulating objects in open world environments. Affordance understanding provides a robot with means to realise its goals and execute its tasks, e.g. to achieve autonomous navigation in unknown buildings where it has to find doors and ways to open these. In order to get actionable suggestions, robots need to be able to distinguish subtle differences between objects, as they may result in different action sequences: doorknobs require grasp and twist, while handlebars require grasp and push. In this paper, we improve affordance perception for a robot in an open-world setting. Our contribution is threefold: (1) We provide an affordance representation with precise, actionable affordances;(2) We connect this knowledge base to a foundational vision-language models (VLM) and prompt the VLM for a wider variety of new and unseen objects;(3) We apply a human-in-the-loop for corrections on the output of the VLM. the mix of affordance representation, image detection and a human-in-the-loop is effective for a robot to search for objects to achieve its goals. We have demonstrated this in a scenario of finding various doors and the many different ways to open them. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Visual languages

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Digital Transformation in Mechatronics: ICT Applications in Automation and robotics 4

Digital Transformation in Mechatronics: ICT Applications in ...

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4th IEEE International conference on ICT in Business Industry and Government, ICTBIG 2024

作者： Vajpayee, Deepshikha Gupta, Nagesh Joshi, Vaishali Symbiosis University of Applied Sciences School of Computer Science and Information Technology Indore India

ISBN: (纸本)9798331518981

Mechatronics, a multidisciplinary field and transformed the conventional methods to dynamic and autonomous systems. the emergence of robotics and technology in various sectors marks a significant revolution in the industry specially in manufacturing, construction, food, and pharmaceutical industries. this ensured quality, efficiency and precision in the concerned industries. Based on this background, it is from this perspective that the paper addresses transformatory work in collaborative robots, automation technologies, and robotic manipulators through object recognition, human-robot interaction, and machine learning applications. Reviewing the key technologies- machine vision, thermography etc. that transformed the quality control across the industries, enhancing the reliability and precision and efficiency of the *** robots and manipulators in conjunction with the da Vinci Surgical System represent huge promise for surgical purposes and therapeutic interventions within medicine. Discuss some of the challenges in the path planning for system adaptability and insist on the need for robust data in medical robotics, besides the key success factors for adopting robotics in every other sector. this research marks how the growing role of robotics, which includes changing industries that are driving the Fourth Industrial Revolution, offset labor shortages, and growing global demands, is being found. © 2024 IEEE.

关键词： Motion planning

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4th International conference on Agriculture Digitalization and Organic Production, ADOP 2024

4th International Conference on Agriculture Digitalization a...

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4th International conference on Agriculture Digitalization and Organic Production, ADOP 2024

ISBN: (纸本)9789819744091

the proceedings contain 40 papers. the special focus in this conference is on Agriculture Digitalization and Organic Production. the topics include: Approach for Long-Term Forecasting of Frosts and Droughts in Smart Agriculture;deep Learning for Pink Bollworm Detection and Management in Organic Cotton Farming Practices;the Use of Satellite Monitoring and Aerial Photography Data to Assess the Heterogeneity of Agricultural Crops in the Khabarovsk Territory;application of Unmanned Aerial Vehicles for Precision Spraying of Chemicals in Agronomic Operations: A Case Study of Potato Desiccation;local Positioning of an Agricultural Mobile robot Based on a vision System;voice-Controlled Autonomous Agri-robot for Organic Farming Pest and Disease Monitoring;evaluation Model for Digital Technology Efficiency: the Example of Intelligent Digital Video Monitoring of Early Disease Diagnosis and Physiological Cows Condition;research of Reindeer Migration Routes Based on Tracking Technologies;improving the Quality of X-ray Images of Seeds in Smart Farming Using Deep Learning;digital Maize Crop Guardian: Automated Identification of Fall Armyworm Infestation Using computer vision;enzymatic Detoxification of Zearalenone-Contaminated Wheat and Corn Grain Using a Recombinant Zearalenone Hydrolase from Clonostachys rosea;organic and Inorganic Weed Management Practices in Soybean Under Different Land Configurations;fishery in Armenia and Aqua-probiotics;automatic Determination of Sturgeon Size Using Deep Learning Technologies;methods and Technical Means of Nonintrusive Assessment of Fish Biomass and robotic Maintenance of Cage Aquaculture;seasonal Dynamics and Vertical Distribution of Phosphorus in Sediments Under Trout Сage Farms in Lake Ladoga;Forecasting the SAM Index Value Using Fourier Series and Neural Networks.

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Research on precise positioning technology on the tower of high-voltage transmission line with live working robot 4

Research on precise positioning technology on the tower of h...

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4th International conference on computer Engineering and Application, ICCEA 2023

作者： Huang, Li Xu, Boyu Pan, Wenbo Wu, Qingqi Zou, Yang Guangdong Power Grid Co. Ltd. Meizhou Power Supply Bureau Guangdong China

ISBN: (纸本)9798350347548

the identification and positioning of obstacles on the operating lines of the live working robot is one of the key technologies to complete the operation task. In order to perform localization and ranging of obstacles on power lines, a binocular vision approach was used. In this paper, a binocular camera was used and camera calibration was performed first. the aberration correction and stereo correction of the binocular camera views were performed by the acquired camera internal reference matrix and the left and right camera positional matrices. then, the parallax map of the binocular image is obtained using the semi-global matching algorithm SGM (Semi-Global Matching), and the parallax map is smoothed using the weighted least squares filtering algorithm. Finally, the depth information of the obstacle is obtained by reprojecting the parallax map. the effectiveness and accuracy of the proposed localization and ranging method is verified by experiments on the obstacles of power lines. © 2023 IEEE.

关键词： robots

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