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

共 1298 条记录，以下是41-50 订阅

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Self Automated Kinematic Smart Haptic Arm 7

Self Automated Kinematic Smart Haptic Arm

引用

7th international conference on Design Innovation for 3 Cs Compute Communicate control, ICDI3C 2023

作者： Ajith, A.S. Manoj, S.C. Monisha, N. Prajwal, R. Praveen, A. Mvj College of Engineering Ece Dept. Bengaluru India Mvjce Mvj College of Engineering Ece Dept Bengaluru India

ISBN: (数字)9798350395556

ISBN: (纸本)9798350395556

robotics is an engineering discipline that focuses on the design and development of robots and their associated technologies. The main goal of robotics is to create new technologies that are versatile, user-friendly, and capable of processing and analysing vast amounts of data. Researchers in this field are interested in automating various tasks by using sensors to convey information about the environment to the robotic arm. They are also focused on implementing analytical concepts in robotics to improve their functionality. Nowadays, many industries rely heavily on robotic machinery, which is used in a wide range of manufacturing factories. For instance, these devices can be used in the medical field or manufacturing companies. They act as controllers for industrial robotic arms and offer more precision and ease-of-use than their predecessors. With these devices, programming a robotic arm to complete multiple tasks at once is much simpler. Ultimately, the aim of developing these devices is to bridge the gap between robots and humans. © 2023 IEEE.

关键词： Computer vision

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Machine vision-based algorithm for tooth workpiece pose subpixel detection 3

Machine vision-based algorithm for tooth workpiece pose subp...

引用

3rd international conference on control and Intelligent robotics, ICCIR 2023

作者： Tao, Liujie Liu, Zhigang Hefei China

ISBN: (纸本)9781510671867

Aiming to address the issue of pose detection of workpieces in automatic assembly processes, this paper presents an algorithm for detecting the pose of metal gear workpieces. The method utilizes an improved homomorphic filtering algorithm to eliminate spot noise from metal workpieces. The complete gear profile is then obtained through the use of the K-means threshold segmentation method and neighborhood tracking method. The center of the gear is determined with the gravity center method, and a virtual circle is scanned with the center as its point of origin. The subpixel feature points of the tooth profile are determined by the least square method, enabling the exact position and pose of the gear workpiece to be obtained. The results of experimentation demonstrate that this method improves detection accuracy by 41.7%, reduces detection error, and has stronger robustness than pixel-level detection algorithms. The proposed method enables the high-precision positioning of the position and pose of the gear workpiece and has practical application value. © 2023 SPIE.

关键词： Computer vision

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A Force-driven and vision-driven Hybrid control Method of Autonomous Laparoscope-Holding Robot

A Force-driven and Vision-driven Hybrid Control Method of Au...

引用

IEEE international conference on robotics and Automation (ICRA)

作者： Fang, Jin Li, Ling Li, Xiaojian Mo, Hangjie Guo, Pengxin Xiao, Xilin Qu, Yanwei Hefei Univ Technol Sch Management Hefei Peoples R China Hefei Univ Technol Key Lab Proc Optimizat & Intelligent Decis Making Minist Educ Hefei Peoples R China

ISBN: (纸本)9798350384581;9798350384574

Laparoscope-holding robots significantly enhance the stability and precision of visualization in minimally invasive surgeries. Most existing robots of this kind depend on visual servo systems and struggle with efficient, rapid adjustments in the field-of-view (FOV), especially when identifying organs and needles outside the FOV. This paper presents a laparoscope-holding robot system capable of employing both vision-driven and force-driven mechanisms for continuous and large-scale FOV adjustments, respectively. The system features an integrated tactile handle, enabling the reception of human-robot interaction forces during surgical navigation. We propose a hybrid control method that leverages both force and vision inputs for laparoscopic FOV adjustments. This approach integrates a virtual wrench, generated from visual information, and an interaction wrench, obtained from the tactile handle, into the robot's dynamic model, which complies with remote center of motion constraints. The interaction wrench's gain is adjusted with the gripping force on the integrated tactile handle, ensuring that unintended movements caused by accidental contacts are prevented, thus safeguarding operational safety. The proposed method eliminates the need to switch control modes, enabling simultaneous visual tracking and tactile interaction guidance. Experimental results demonstrate that the proposed method not only allows for FOV adjustments with surgical instrument guiding but also adapts well to large-scale FOV adjustment tasks.

关键词： Laparoscopy

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Design of vision-guided Gripping System for 6DOF Robots Combined with Dexterous Hands 7

Design of Vision-guided Gripping System for 6DOF Robots Comb...

引用

7th international conference on robotics, control and Automation engineering, RCAE 2024

作者： Wang, Chengwen Wan, Guoyang Li, Hanqi Li, Xuna Zheng, Da Teng, Mingyao Anhui University of Engineering Dept. School of Electrical Engineering Wuhu China

ISBN: (纸本)9798350355642

In the robot application system incorporating dexterous hand, a vision-based robot grasping system is proposed to address the lack of robustness of dexterous hand in grasping fixed attitude objects. First, a 6DOF robot grasping system based on machine vision is constructed using dexterous hand, depth camera and 6DOF collaborative robot, which realizes accurate grasping under vision guidance;second, to solve the problem of vision system's poor localization accuracy due to the loss of image information and features caused by image noise, occlusion and complex background in the process of image processing, a pooling layer and attention mechanism to enhance the feature extraction ability;moreover, an optimized dexterous hand grasping strategy is proposed through exhaustive grasping action design and analysis, which effectively improves the robustness of the system. The experimental results show that the accuracy of the target detection model reaches 87% through the localization measurement of the experimental objects, which is 2.1% higher than the original method, and the grasping success rate of the robotic system equipped with dexterous hand and depth camera is improved by 3.5%. These results validate the feasibility of the robotic grasping system incorporating dexterous hands in practical applications and significantly enhance the robustness of the system. © 2024 IEEE.

关键词： Collaborative robots

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A vision-Integrated Navigation Method in AUV Terminal Mobile Docking Based on Factor Graph Optimization 8

A Vision-Integrated Navigation Method in AUV Terminal Mobile...

引用

8th international conference on Automation, control and robotics engineering, CACRE 2023

作者： Ma, Tianheng Chen, Shumin Ruan, Liang Xu, Yuanxin Zhejiang University College of Information Science and Electronic Engineering Hangzhou China Zhejiang Sci-Tech University Faculty of Informatics and Electronics Hangzhou China

ISBN: (纸本)9798350302776

The widespread use of Autonomous Underwater Vehicles (AUVs) highlights the need for autonomous docking, during which accurate pose estimation and navigation play a vital role. This paper proposes a multi-sensor fusion navigation framework based on the factor graph optimization method, integrating tightly-coupled visual information from the light array to provide high-accuracy and high-frequency relative pose estimations between AUV and its mobile dock at the terminal docking stage. Simulation results demonstrate that the proposed algorithm outperforms PnP and achieves smaller RMSE in relative attitude and translation estimations. Furthermore, the experiments show that the proposed algorithm provides smoother estimation results and that it has the potential to be deployed in embedded applications. © 2023 IEEE.

关键词： Computer vision

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vision robotics for the Automatic Assessment of the Diabetic Foot 32nd

Vision Robotics for the Automatic Assessment of the Diabetic...

引用

32nd international conference on Flexible Automation and Intelligent Manufacturing

作者： Mesquita, Rui Costa, Tatiana Coelho, Luis Silva, Manuel F. Polytech Porto Sch Engn Porto Portugal INESC TEC Porto Portugal

ISBN: (纸本)9783031382406;9783031382413

Diabetes, a chronic condition affecting millions of people, requires ongoing medical care and treatment, which can place a significant financial burden on society, directly and indirectly. In this paper we propose a vision-robotics system for the automatic assessment of the diabetic foot, one the exams used for the disease management. We present and discuss various computer vision techniques that can support the core operation of the system. U-Net and Segnet, two popular convolutional network architectures for image segmentation are applied in the current case. Hardcoded and machine learning pipelines are explained and compared using different metrics and scenarios. The obtained results show the advantages of the machine learning approach but also point to the importance of hard coded rules, especially when well know areas, such as the human foot, are the systems' target. Overall, the system achieved very good results, paving the way to a fully automated clinical system.

关键词： vision robotics Image segmentation Diabetes

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Semi-Automated Video Archiving Using Object Detection, Tracking and Ontological Annotation 4

Semi-Automated Video Archiving Using Object Detection, Track...

引用

4th international conference on Artificial Intelligence, robotics and control, AIRC 2023

作者： Ayman, Shehab Eldeen Hussein, Walid Karam, Omar H. The British University in Egypt Faculty of Informatics and Computer Science Department of Software Engineering Cairo Egypt The British University in Egypt Faculty of Informatics and Computer Science Department of Computer Science Cairo Egypt

ISBN: (纸本)9798350348248

In light of this unmistakable exponential data expansion, visual media archiving must be rethought. Human generated meta-data might not be sufficient for efficient data retrieval. Object detection and object recognition enable the generation of computer-generated meta data that improve the storage and retrieval of data. We present a semi-automated approach for preserving video footage that combines object identification and ontologies. This significantly cuts down on search time, data scrubbing by providing only the relevant information making for more efficient queries. © 2023 IEEE.

关键词： Computer vision

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robotics Solution for Agriculture: Automated and IoT-enabled Tomato Picking and Packing

Robotics Solution for Agriculture: Automated and IoT-enabled...

引用

2023 IEEE international conference on Agrosystem engineering, Technology and Applications, AGRETA 2023

作者： Stepanova, Anastasiia Pham, Ha Zourmand, Alireza HAMK Tech Research Unit Häme Universitv of Applied Sciences Hämeenlinna Finland

ISBN: (纸本)9798350347333

This paper presents a novel robotics solution for the food industry, focusing on automated and IoT-enabled tomato picking and packing. The work includes a pilot execution of a low-cost implementation of Internet of Things (IoT) and Machine to Machine (M2M) communication for the postharvest stage, specifically targeting tomato picking and primary packing using a computer vision-based robotic arm. The vision system employs You Only Look Once (YOLO) model weights to accurately detect and localize tomatoes. The proposed IoT development enables users to send commands specifying the desired number of tomatoes to be packed, while also providing easy control and monitoring capabilities for workers. The command transmission occurs via a local network that incorporates a collaborative robot UR5, a Zivid Two 3D industrial camera connected to a laptop, and a Raspberry Pi microcomputer. This work addresses the crucial aspects of food safety and labor shortage in small and medium-sized enterprises (SMEs), while also paving the way for automated tomato processing to ensure the high quality of fresh, perishable tomatoes. © 2023 IEEE.

关键词： Computer vision

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FOOD QUALITY INSPECTION AND SORTING USING MACHINE vision, MACHINE LEARNING AND robotics

FOOD QUALITY INSPECTION AND SORTING USING MACHINE VISION, MA...

引用

ASME international Mechanical engineering Congress and Exposition (IMECE)

作者： Drogalis, Conor Zampino, Christopher Chauhan, Vedang Western New England Univ Springfield MA 01119 USA

ISBN: (纸本)9780791887608

The integration of Industry 4.0 technologies, such as machine vision, machine learning, and robotics, has transformed the food industry by enabling more efficient, accurate, and productive food quality inspection. This scope of this work is to implement these technologies in the inspection of chocolate chip cookies in a lab based setting. The PC-based system includes a conveyor belt, webcam, low-cost robotic arm, grayscale sensors, and MATLAB and Arduino microcontroller for communication between the vision system and the robot. Machine vision captures images of cookies and processes these images for feature extraction, while machine learning algorithms classify cookies based on their visual features and identify defects. The use of Artificial Neural Networks for training and testing results in an overall accuracy of 95% and 90%, respectively. The sorting of cookies based on the machine learning classification is carried out using a robotic arm. The robotic arm receives signals from the ML algorithm to remove defective cookies from the conveyor into a rejected cookies bin. The closed-loop system effectively (98%) inspects food quality, reducing defective food from reaching consumers. Machine vision and machine learning techniques offer a promising approach to improving quality control in the food industry.

关键词： Industry 4.0 machine vision machine learning robotics food quality inspection

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Design and Feasibility Test of an Automatic Scraping Robot 9

Design and Feasibility Test of an Automatic Scraping Robot

引用

9th international conference on Automation, robotics and Applications (ICARA)

作者： Cui, Zhenmeng Han, Liang Dong, Guancheng Lin, Yingze Gao, Yangzhen Fan, Shuaishuai Southeast Univ Sch Mech Engn Nanjing Peoples R China

ISBN: (纸本)9781665489218

Scraping is a key technology in high-precision machine tool machining. Scraping can eliminate the accumulated tolerances and improve the assembly accuracy of the machine tool. Scraping is a time-consuming and tedious manual labor, which is usually conducted by experienced technician. To overcome these shortcomings, a novel automatic scraping robot was designed and tested in this study. The robot includes a 3-axis moving mechanism, a vision recognition system, a 3-D measurement system, and a control system. In this study, milling is used to simulate the shape of tool marks in the traditional scraping process. After a series of tests, the designed robot has been verified to be able to perform automatic scraping work. The workpiece scraped with this robot meets the standard of a high precision machine.

关键词： automatic scraping vision recognition robot measurement system

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