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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81-90 订阅

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Enhancing Manufacturing Efficiency with Computer vision and Doosan robotics: An Overview of Real-Time Object Detection and Automated Decision-Making 4

Enhancing Manufacturing Efficiency with Computer Vision and ...

引用

4th international Informatics and Software engineering conference, IISEC 2023

作者： Chaabani, Ameni Cherif, Raef Yaddaden, Yacine Université du Québec À Rimouski Département de Mathématiques Informatique et Génie Rimouski Canada

ISBN: (纸本)9798350318036

This article presents a solution developed with Doosan robotics and OnRobot for identifying missing or broken pull tabs in manufacturing processes using computer vision and robotics integration. The solution involves a collaborative robot equipped with a 2.5D camera and an end-effector capable of grasping and manipulating objects. The 2.5D camera captures images of the objects, and computer vision algorithms are applied to detect and identify the presence of pull tabs and assess their condition. The system utilizes advanced image processing techniques to analyze the captured images, identifying any instances of missing or broken pull tabs. Upon detection, the robot employs its end-effector to interact with the identified pull tabs, facilitating their removal or replacement as necessary. The integration also incorporates automated decision-making algorithms to optimize production efficiency, reduce errors, and improve product quality. Integrating these technologies enhances precision, accuracy, and speed in identifying and manipulating objects, leading to increased productivity, cost reduction, and improved product quality. © 2023 IEEE.

关键词： Object detection

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Design and Fabrication of a vision-based Tactile Sensor 11

Design and Fabrication of a Vision-based Tactile Sensor

引用

11th RSI international conference on robotics and Mechatronics, ICRoM 2023

作者： Mirzaee, Mohammad Amin Sadighi, Ali University of Tehran School of Mechanical Engineering Tehran Iran

ISBN: (纸本)9798350308105

The sense of touch is an essential element for robotic arms in manipulating objects and their optimal interaction with the environment. Tactile sensors provide extensive quantitative and qualitative information about the contact between the sensor and the target object. With the advancements in machine vision and image processing, vision-based tactile sensors have been introduced as a more versatile sensing technology. This paper covers the steps of design, fabrication, and calibration of a vision-based tactile sensor. A brief introduction to optical simulation is presented and the convolutional neural networks model is used as the force estimation model for the simulation and experimental data. The fabricated sensor is capable of detecting normal-Axis forces up to 5 newtons and tangential forces in two directions up to slip (approx. 1.4 times the applied normal force). The mean square error obtained for the built sensor is equal to 0.038 newtons in the vertical axis and 0.0033 and 0.0039 newtons in the two tangential axes on all the experimental data. © 2023 IEEE.

关键词： Fabrication

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Autonomous Landing of an Unmanned Aerial Vehicle on a Mobile Platform 7

Autonomous Landing of an Unmanned Aerial Vehicle on a Mobile...

引用

7th international conference on Automation, control and Robots, ICACR 2023

作者： Dalang, Felix Sihitshuwam Kulathunga, Geesara Khusainov, Ramil Innopolis University Robotics and Computer Vision Innopolis Russia Innopolis University Center of Autonomous Technologies Innopolis Russia Robotics Innopolis University Innopolis Russia

ISBN: (纸本)9798350302882

Landing an Unmanned Aerial Vehicle (UAV) on a mobile vehicle, has been an active research area due to its much needed applicability in numerous directions such as landing an aerial vehicle on the international space station or a ship at sea. Such research is conducted mainly in two directions: control-based and vision-based. vision-based approaches require sensing from cameras that detect features, such as visual markers, on the mobile vehicle to estimate and track the mobile vehicle pose till the landing pose. The visual markers are usually utilized for feature detection, which most mobile vehicles might not have. This paper proposes a new approach for achieving autonomous landing of a UAV by generating constrained uniform B-spline trajectories assuming known pose of both the UAV and the UGV. Then applying PID controller to regulate velocity set point to land the UAV on the mobile vehicle. The overall effectiveness of the proposed approach is demonstrated using ROS/Gazebo simulations, with a UAV (Px4 enabled IRIS) and a mobile vehicle (Jackal from ClearPath robotics). Landing tasks for static and dynamic cases are carried out and the findings and limitations are stated thereafter. © 2023 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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6D Pose Estimation for vision-guided Robot Grasping Based on Monocular Camera 6

6D Pose Estimation for Vision-guided Robot Grasping Based on...

引用

6th international conference on robotics, control and Automation engineering, RCAE 2023

作者： Wang, Shiman Liu, Jianxin Lu, Qiang Liu, Zhen Zeng, Yongjie Zhang, Dechang Chen, B.O. Xihua University Chengdu China Nagasaki Institute of Applied Science Nagasaki Japan

ISBN: (纸本)9798350315301

Enhancing the intelligence of grasping operations through visual empowerment is currently a hot research topic in the field of robotics, where pose estimation is an important component. However, existing methods that solely rely on RGB images mostly employ direct methods or indirect methods using two-stage/multistage network predictions. Estimating the translation and rotation components of pose solely through a single network model does not yield optimal solutions. In this paper, different networks were used to predict the translation and rotation components, and convolutional block attention module (CBAM) and Pyramid Pooling Module (PPM) were introduced to address the issues that features decay in the backbone residual network after multiple layers of convolution and the insufficient utilization of feature information. Furthermore, in the rotation prediction branch, the problem of inaccurate recognition caused by weakened details after multiple layers of convolution was addressed by incorporating pyramid pooling into the network to capture richer detail and contextual information. Experimental tests were conducted on the publicly available Linemod dataset and in real environments. The results demonstrate that the proposed network exhibits a significant improvement of 2.76% in the most common ADD metric compared to a coordinate-based disentangled pose network (CDPN). It also achieves a 1 % improvement in the 5°, 5cm metrics and comparable performance in the Proj.2D metric with a 0.2% increase. © 2023 IEEE.

关键词： Convolution

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Investigation on MLP, CNNs and vision Transformer models performance for Extracting a Human Emotions via Facial Expressions 3

Investigation on MLP, CNNs and Vision Transformer models per...

引用

3rd international Symposium on Instrumentation, control, Artificial Intelligence, and robotics, ICA-SYMP 2023

作者： Panlima, Aomsup Sukvichai, Kanjanapan Kasetsart University Dept. of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9781665473538

One of the difficult challenges in AI development is to make machine understand the human feeling through expression because human can express feeling in various ways, for example, through voices, facial actions or behaviors. Facial Emotion Recognition (FER) has been used in interrogating suspects and being a tool to help detect emotions in people with nerve damage or even in the COVID-19 pandemic when patients hide their timelines. It can be applied to detect lies through micro expression. In this work will mainly focus on FER. The results of Deep Neural Network (DNN), Convolutional Neural Network (CNN), and vision Transformer were compared. Human emotion expressions were classified by using facial expression datasets from AffectNet, Tsinghua, Extended Cohn Kanade (CK+), Karolinska Directed Emotional Faces (KDEF) and Real-world Affective Faces (RAF). Finally, all models were evaluated on the testing dataset to confirm their performance. The result shows that vision Transformer model outperforms other models. © 2023 IEEE.

关键词： Emotion Recognition

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Research on Simulating Application of Artificial Intelligence in Aerospace Field 2

Research on Simulating Application of Artificial Intelligenc...

引用

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

作者： Yuan, Fei Shen, Xiaozhong Wu, Jiawei Yang, Weilin School of Intelligent Equipment and Automotive Engineering WuXi Vocational Institute of Commerce Wuxi China Shenzhen Yuejiang Technology Co. Ltd Shenzhen China School of Internet of Things Engineering Jiangnan University Wuxi China

ISBN: (纸本)9798350336405

The project relies on the intelligent mechanical arm and omnidirectional intelligent mobile car developed by Yuejiang Technology Co., LTD to simulate the space missions such as spaceship departure, astronaut exit, material handling, base station construction, astronaut return and spaceship return, and integrates multiple technologies such as autonomous control of mechanical arm, path planning of unmanned vehicle, AI identification and sensor technology. The research of the project has a certain role in promoting the promotion of AI in higher vocational education, and also has a certain reference significance for the application of AI in aerospace, logistics and other fields. © 2023 IEEE.

关键词： Computer vision

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Harnessing vision Transformers for LiDAR Point Cloud Segmentation

Harnessing Vision Transformers for LiDAR Point Cloud Segment...

引用

2023 IEEE international conference on robotics and Biomimetics, ROBIO 2023

作者： Inan, Burak Alp Rondao, Duarte Aouf, Nabil School of Science and Technology Department of Electrical and Electronic Engineering

ISBN: (纸本)9798350325706

Point cloud data, representing 3D objects, has become an indispensable format in numerous applications. However, directly processing this data form, particularly for tasks like segmentation, remains a challenging endeavor. In this manuscript, we present an innovative methodology tailored for point cloud segmentation. Our approach exclusively harnesses the capabilities of two vision Transformers (ViTs). To facilitate this, we first transform the point cloud into a 2D image representation through spherical projection. Subsequently, the initial ViT is utilized for the extraction of salient features from the projected image. These extracted features are then channeled into the second ViT. Our methodology synergizes the compactness and efficiency of spherical projection with the robustness and adaptability of vision transformer networks. The latter has been celebrated for its state-of-the-art performance across a myriad of computer vision challenges. For empirical validation, we train our network architecture using the renowned SemanticKITTI dataset, aiming to benchmark its efficacy against existing frameworks. © 2023 IEEE.

关键词： deep learning Point cloud segmentation spherical projection vision transformer networks

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Research on fire localization based on binocular vision 2

Research on fire localization based on binocular vision

引用

2nd international conference on Artificial Intelligence, Human-Computer Interaction and robotics, AIHCIR 2023

作者： Chu, Shengli Yuan, Yi Yang, Guangyu Wang, Dandan Zheng, Wenpei Gan, Yifan Sun, Bingcai Cnpc Research Institute of Safety and Environment Technology Beijing China College of Safety and Ocean Engineering China University of Petroleum-Beijing Beijing China

ISBN: (纸本)9798350360363

Aiming at the problem of less fire source localization and low localization accuracy in current fire monitoring methods, a fire localization perception method based on binocular vision is proposed. Through the visible binocular camera, the first calibration camera internal and external parameters to select the error minimum baseline, after the acquisition of image flame information, through the visible binocular camera on the fire source ranging, combined with the camera position to the fire source localization. The experimental results show that the average relative error of flame localization model recognition is at 4.54%, and the lowest reaches 1.50%. The fire localization method based on binocular vision can accurately locate the fire source, detect and alarm the typical image features appearing when the fire is burning, and achieve the purpose of precise positioning of the fire source. Realize the fire 'early detection, early warning, early disposal' purpose. © 2023 IEEE.

关键词： Binocular vision

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Based on machine vision robot zero and the integration of hand-eye calibration method 3

Based on machine vision robot zero and the integration of ha...

引用

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

作者： Wang, Enguo Feng, Xin Su, Chengzhi Ma, Chengshuai School of Mechanical and Electrical Engineering Changchun University of Technology Jilin Changchun130022 China Changchun University of Technology Artificial Intelligence Institute Jilin Changchun130022 China

ISBN: (纸本)9781510671867

In order to improve the absolute positioning accuracy of the robot, a robot -based robot zero and hand -eye integration calibration method is proposed. By collecting several robotic joint corners, end position data data, and cooperative target position data under the camera coordinate system, use the string function to adjust the input, and then based on the gradient drop method, obtain the results of the robot's eye and eye calibration. Errors and correction of their parameters, thereby improving the absolute positioning accuracy of the robot. The experimental results showed that the maximum error of the absolute positioning accuracy of the robot was reduced from 6.298mm to 3.149mm, and the average error dropped from 3.745mm to 1.899mm. It indicates that this method can improve the absolute positioning accuracy of the robot under low cost conditions. © 2023 SPIE.

关键词： Errors

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Design of Servo control System for Mobile Robot Based on UAV Global vision 24

Design of Servo Control System for Mobile Robot Based on UAV...

引用

4th international conference on robotics and control engineering, RobCE 2024

作者： Ji, Peng Dou, Yonglin Pang, Yanxu Wang, Ziqi Ma, Fengying School of Information and Automation Engineering Qilu University of Technology Shandong Academy of Sciences Shandong Province Jinan City China

ISBN: (纸本)9798400716782

When ground reconnaissance mobile robots perform tasks alone, they can only obtain ground view perception, which leads to the inability to globally optimize, resulting in local rather than global optimal solutions. Inspired by this, a servo control system for mobile robots based on UAV global vision is designed in this paper. Firstly, acquire global visual images and process them, selecting target points via mouse under global vision. Secondly, plan an obstacle avoidance path to reach the target point using artificial potential field method, and smooth the path using B-spline curves. Then, establish the kinematic model of the mobile robot and use the LQR algorithm to enable the robot to track the path. Finally, experimental tests were conducted via the Webots simulation platform to verify the feasibility of the system. Experimental results show that the system can ensure high accuracy and smooth path tracking, and has strong cooperative control, effectively addressing the single visual problem of ground mobile robots. Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Mobile robots

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