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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101-110 订阅

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vision-based mobile robotic grinding path generation for large castings 3

Vision-based mobile robotic grinding path generation for lar...

引用

3rd international conference on robotics, Automation and Intelligent control, ICRAIC 2023

作者： Chen, Lufeng Chen, Aobo Kuang, Yiqun Fan, Shuai Qiu, Jing Uestc School of Automation Engineering Chengdu China Chengdu University of Technology School of Mechanical and Electrical Engineering Chengdu China Uestc School of Mechanical and Electrical Engineering Chengdu China

ISBN: (纸本)9798350360813

Given the numerous drawbacks of manual grinding for castings, the use of robots for intelligent grinding is quickly becoming an unavoidable trend. This paper introduces the design of a grinding robot system for the intelligent grinding of medium and large non-standard castings. The proposed system uses labels to identify and scan the surface that needs grinding, subsequently registering and segmenting the obtained point cloud. From here, it converts the select grinding area into a triangular mesh surface, and maps it onto a parametric domain using the re-parameterization method. The system then plots a path on the plane and maps it back onto the original workpiece, acquiring the final grinding path after necessary tool axis adjustments. The grinding head is then manipulated to perform constant force grinding, employing the PID control. Tests have shown that the system can effectively grind the surface of medium and large nonstandard castings in real-world industrial settings. © 2023 IEEE.

关键词： Grinding (machining)

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Design and Implementation of an Automated Material Handling Robot 5

Design and Implementation of an Automated Material Handling ...

引用

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

作者： Zhu, Feitian Feng, Zhichao Zheng, Chuang Yan, Shijin Ling, Rongyao School of Mechanical and Electrical Engineering Shaoxing University Shaoxing China

ISBN: (纸本)9798350357950

This study addresses the design and implementation of an automated material handling robot, primarily focusing on line following, localization, obstacle avoidance, material recognition and handling. To achieve these function alities, hardware modules for the robot were designed including a main control module, grayscale line tracking module, robotic arm control module, and power module, among others. With the adoption of an STM32F407 microcontroller, an efficient, stable, and user-friendly controller solution was developed. Data acquired from various sensor modules were analyzed and processed based on different priorities at different stages, enabling effective obstacle detection and path planning. In terms of motion control, a PID control algorithm was employed, optimizing the stability and speed of the automated material handling robot's movement and significantly improving its search speed. Experimental verification demonstrated that the designed controller solution for the automated material handling robot successfully accomplished multiple tasks, yielding the intended control performance. © 2023 IEEE.

关键词： automated material handling line following obstacle avoidance vision-based recognition wheeled mobile robot

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Computer vision-Based Hydroponic Lettuce Contour and Area Recognition System

Computer Vision-Based Hydroponic Lettuce Contour and Area Re...

引用

2023 international conference on Electrical engineering and Informatics, ICEEI 2023

作者： Pranowo, Samuel Raymond Sukra, Zener Lie Asy'ari, Muhammad Zacky Paryasto, Marisa Binus Aso School of Engineering Bina Nusantara University Automotive and Robotics Program Computer Engineering Department Jakarta Indonesia Telkom University Computer Engineering Program Electrical Engineering Department Bandung Indonesia

ISBN: (纸本)9798350381290

Agriculture is a vital industry for the people of Indonesia, but there are several obstacles, including limited space in urban areas and inefficient conventional sorting and harvesting methods. Using computer vision to choose hydroponic lettuce that is ready to be harvested and a robotic arm to bring the selected lettuce yields, the produced system aims to solve this problem. The system's computer vision algorithms include color space conversion, intensity transformation, and an algorithm for following borders. This project's research methodology combines a quantitative approach with an experimental approach, which consists of conducting several trials on the built system. Several trials demonstrated that the computer vision software was able to accomplish the specified objectives. The average success rate of the developed computer vision system is 93%, while the average success rate of the robot arm is 85%. © 2023 IEEE.

关键词： Lettuce

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Omnibot: A Scalable vision-Based Robot Swarm Platform 18

Omnibot: A Scalable Vision-Based Robot Swarm Platform

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IEEE 18th international conference on control and Automation (ICCA)

作者： Ma, Zhao Liang, Jiachen Wang, Hongyi Guo, Shiliang Huo, Peidong Zhang, Yin Zhao, Shiyu Westlake Univ Sch Engn Intelligent Unmanned Syst Lab Hangzhou Peoples R China

ISBN: (纸本)9798350354416;9798350354409

Introducing vision sensing into swarms presents three challenges for developing robot platforms. First, the vision system requires a wide field of view to perceive surrounding robots. Second, vision algorithms demand high computational power, which poses a challenge for real-time vision-in-the-loop simulation. Third, as the swarm scale increases, managing the system becomes increasingly demanding. The main contribution of this paper is the development of a novel mobile robot swarm platform to overcome these challenges. 1) Each robot features a 360-degree omnidirectional vision system comprising four cameras, allowing each robot to detect and interact with the surrounding robots. 2) It has a novel ROS-based distributed swarm simulation system, which can effectively utilize the onboard computational resources of multiple robots to achieve parallel vision-in-the-loop simulation. 3) It features a novel swarm management system that allows real-time monitoring and debugging of multiple robots. These innovative designs provide a novel swarm platform that can facilitate the study of versatile vision-based swarm tasks.

关键词： Swarm intelligence

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Design of Autonomous Fire Hose Docking System for Intelligent Fire-Fighting Robots 5

Design of Autonomous Fire Hose Docking System for Intelligen...

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

作者： Yang, Zhiwei Zhang, Fei Shang, Weiwei Chaoxia, Chenyu University of Science and Technology of China Department of Automation Hefei China

ISBN: (纸本)9798350357950

Although existing fire-fighting robots have been able to extinguish fires, the docking task of fire hoses has always been the key obstacle to achieving autonomous fire extinguishing functions for fire-fighting robots. Therefore, it is crucial to enable robots to autonomously dock fire hoses to fire hydrants. To solve this problem, we design a new multi-DOF docking mechanism and develop a vision-guided autonomous fire hose docking system based on a robot operating system. When the robot detects the fire, the camera mounted on it can guide the docking system to complete the docking of the fire hose, laying the foundation for the robot to achieve autonomous fire extinguishing. © 2023 IEEE.

关键词： Camera vision Fire Hose Docking Intelligent Fire-fighting Robot

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A 3D Positioning Method for Electric Robots Based on Binocular vision 3

A 3D Positioning Method for Electric Robots Based on Binocul...

引用

3rd international conference on Computer, control and robotics, ICCCR 2023

作者： Zhang, Wancai Yang, Wenqing Sun, Zhen Zhang, Nan Information System Integration Branch of NARI Technology Co. Ltd Nanjing China

ISBN: (纸本)9781665492126

When employing monocular camera model detection to determine the 3D position of the operation target, which is common in the field of electric power robotics, the robot arm cannot be accurately guided to work. The approach initially aligns, corrects, and denoises the binocular image data in accordance with the calibration parameters of the binocular camera system. This work offers a 3D positioning method based on binocular vision. Following the separation of the apparent features of the operation target from the binocular image data, the 3D coordinates of the operation target are computed utilizing the geometric constraints of the binocular pair. Finally, the 3D coordinates of the operation target are matched with the pre-constructed 3D model by ICP to obtain the accurate 3D pose of the operation target. It has been demonstrated through studies that the method presented in this work greatly improves the 3D positional identification accuracy when compared to other existing charging port detection methods. It may also be applied to other sectors of electric robots. © 2023 IEEE.

关键词： Binocular vision

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vision-Based Reactive Planning and control of Quadruped Robots in Unstructured Dynamic Environments 8

Vision-Based Reactive Planning and Control of Quadruped Robo...

引用

8th IEEE international conference on Advanced robotics and Mechatronics, ICARM 2023

作者： Qian, Tangyu Zhou, Zhangli Wang, Shaocheng Li, Zhijun Su, Chun-Yi Kan, Zhen University of Science and Technology of China Department of Automation Hefei China School of Automation Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of Technology Guangzhou China

ISBN: (纸本)9798350300178

Quadruped robots have received increasing attention for the past few years. However, existing works primarily focus on static environments or assume the robot has full observations of the environment. This limits their practical applications since real-world environments are often dynamic and partially observable. To tackle these issues, vision-based reactive planning and control (V-RPC) is developed in this work. The V-RPC comprises two modules: offline pre-planning and online reactive planning. The pre-planning phase generates a reference trajectory over continuous workspace via sampling-based methods using prior environmental knowledge, given an LTL specification. The online reactive module dynamically adjusts the reference trajectory and control based on the robot's real-time visual perception to adapt to environmental changes. © 2023 IEEE.

关键词： Robot programming

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Calculation Method of Road Distress Area Based on Monocular vision 3

Calculation Method of Road Distress Area Based on Monocular ...

引用

3rd international conference on Computer vision and Pattern Analysis, ICCPA 2023

作者： Wang, Lei Hu, Yuxin Zhang, Zhaowei Jiang, Lin School of Mechanical and Automation Engineering Wuhan University of Science and Technology Wuhan430081 China Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology Wuhan430081 China

ISBN: (纸本)9781510667563

Proposed a method for calculating the area of road diseases using a monocular camera. The camera and the road plane are calibrated to obtain the mapping relationship between pixel points and spatial points;the Mask R-CNN is used to detect and segment the road disease;the inverse perspective transformation is used to convert the target image into a bird’s-eye view to obtain the relationship between the pixel scale and the real scale;binarize the bird’s-eye view according to the segmentation effect, and the area of the road disease could be obtained through calculating the number of target pixels. It has been verified that the calculation error of the algorithm is about 2.1675% in the near vicinity. © 2023 SPIE.

关键词： Birds

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Research on Vibration Displacement Measurement of Sleeper Based on Machine vision 1

引用

UNIfied conference of international Workshop on Defence Applications of Multi-Agent Systems, DAMAS 2023, international conference on Maintenance engineering, IncoME-V 2023, international conference on the Efficiency and Performance engineering Network, TEPEN 2023

作者： Chi, Yuliang Gao, Yunpeng Liu, Guiyi Zhang, Chao School of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014000 China Key Laboratory of Intelligent Diagnosis and Control of Electromechanical Systems in Inner Mongolia Autonomous Region Baotou014000 China Baotou Railway Vocational and Technical College Baotou014000 China

ISBN: (数字)9783031494215

ISBN: (纸本)9783031494208

Machine vision technology has the characteristics of high precision, fast speed, non-contact and high degree of automation in displacement detection. It is feasible to apply machine vision technology to the detection of vibration displacement of railway sleeper. In this paper, the vibration displacement measurement technology of railway sleeper is studied, and a machine vision method based on monocular vision measurement is proposed. According to the geometric relationship between the feature points of the target and the corresponding feature points of the space target in the shot image, the pose information of the space target relative to the camera coordinate system is calculated. By monitoring the change of the attitude of the target rigidly connected to the sleeper, the vibration displacement results of the sleeper when the train passes are obtained. The experimental results show that the proposed method meets the requirements of sleeper vibration measurement in terms of measurement accuracy, sampling comment and stability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Displacement measurement

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3D vision Based Lamination Gap Detection of Carbon Fiber Composite

3D Vision Based Lamination Gap Detection of Carbon Fiber Com...

引用

2023 IEEE international conference on Real-Time Computing and robotics, RCAR 2023

作者： Xu, Yuanye Yuan, Libiao Liang, Wei Yang, Yutuo Liu, Shuai Zeng, Ziming Zhang, Yinlong Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Shenyang University of Chemical Technology College of Information Engineering Shenyang110142 China Shenzhen Polytechnic School of Automotive and Transportation Engineering Shenzhen518055 China

ISBN: (纸本)9798350327182

The paper presents a machine learning approach to detect laminate gaps and to classify them as open or closed. Compared with the traditional detection methods, which suffer from low precision of point cloud segmentation and poor effect of gap extraction in traditional gap detection, this paper proposes a gap detection algorithm based on 3D vision. First, an improved undirected graph point cloud segmentation algorithm is used to overcome the under-segmentation of the target region. Second, an adaptive vector for angle discriminant model is proposed to solve the problem of poor extraction effect of the gap edge points. Finally, the B-spline curve-fitting model is used to describe the 3D points on the lamination edges. The proposed algorithm has been evaluated in a visual quality detection platform for carbon fiber composite laminates. The results show that the proposed approach is able to accurately detect and classify laminate gaps in carbon fiber composite structures, providing a reliable tool for quality control in industrial manufacturing processes. © 2023 IEEE.

关键词： Extraction

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