检索结果-内蒙古大学图书馆

robotIC INTELLIGENCE AND AUTOMATION 2025年第2期45卷 248-261页

作者： Shang, Deyong Huang, Yunshan Pan, Zhan Huang, Zhuomeng Zhang, Tianyou China Univ Min & Technol Beijing Sch Mech & Elect Engn & Intelligent Min &Robot Res Beijing Peoples R China Minist Emergency Management Key Lab Intelligent Min & Robot Beijing Peoples R China China Univ Min & Technol Beijing Sch Mech & Elect Engn Beijing Peoples R China

PurposeIn the context of coal mine intelligent construction, intelligent sorting of coal gangue based on robot technology has become one of the main development directions for gangue sorting. The sorting sequence and path of gangue depend on the dynamic sorting planning algorithm, which plays a crucial role in determining the efficiency and energy consumption of coal gangue sorting robots. The purpose of this paper is to solve the inefficiency of existing algorithms and propose a dynamic sorting planning algorithm based on greedy strategy for continuous coal gangue sorting by Delta ***/methodology/approachFirst, the visual recognition system processes images of gangue flow and extracts the position and quality information of each gangue. Considering the variation in coal gangue quality and sorting distance, a robot energy consumption index is introduced. To optimize the greedy algorithm and reduce active omissions in gangue sorting, a correction function is introduced. Divide the gangue flow on the conveyor belt into continuous time window areas in time T, and calculate the sorting order and sorting path of all gangue within the current time window through an optimized greedy algorithm. Finally, MATLAB simulation and robot experiment are carried out to compare the two gangue sorting planning *** on the optimized greedy algorithm under the energy consumption index, a better sorting sequence and sorting path are planned in gangue sorting;Under two different gangue flow densities, compared with the sequential planning algorithm, the optimized greedy algorithm can successfully sort more gangue in a shorter time and with lower energy consumption, which verifies that this algorithm can effectively improve the sorting efficiency of ***/valueIn response to the low efficiency, high energy consumption and significant sorting omissions inherent in traditional sequential planning algorithms, a refined greedy strategy planning algorit

关键词： sorting robot Coal gangue sorting Greedy strategy sorting planning

来源：评论

学校读者我要写书评

暂无评论

Occlusive target recognition method of sorting robot based on anchor-free detection network

引用

JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE 2024年

作者： Wang, Fuzhi Song, Changlin Xihua Univ Sch Mech Engn Chengdu 610039 Peoples R China

The rapid development of industry intelligence has promoted the importance of sorting robots, but the shortcomings of sorting tasks are also gradually obvious. The target detection of the sorting robot in the process of sorting and grasping is affected by the anchor frame setting, and its grasping efficiency and recognition effect are low. Therefore, a detection network based on an anchor frame-free regression algorithm is proposed in this study, and a positioning and grasping method of the sorting robot based on the Deep Belief Network (DBN) algorithm is proposed. The algorithm experiment shows that the prediction accuracy of the proposed anchor-free detection network in the PASCAL VOC dataset reaches 92.91, significantly higher than that of other detection networks. In addition, the sorting robot was researched and designed with high accuracy in occlusion target recognition. When the occlusion area reaches 70%, the accuracy rate is as high as 81.26%, which is far higher than other detection schemes. The above results show that in improving the sorting robot's target recognition ability, the anchor-free detection network can significantly improve its recognition accuracy. At the same time, introducing the DBN network can improve the robot's recognition ability for occluded targets, which is of great significance to the development of the sorting robot and the intelligent industry.

关键词： sorting robot no anchor frame target detection regression algorithm DBN

来源：评论

学校读者我要写书评

暂无评论

Design and operation of a deep-learning-based fresh tea-leaf sorting robot

引用

COMPUTERS AND ELECTRONICS IN AGRICULTURE 2023年第1期206卷

作者： Zhang, Xuechen Wu, Zhengmin Cao, Chengmao Luo, Kun Qin, Kuan Huang, Yangyang Cao, Jie Anhui Agr Univ Coll Engn Hefei 230036 Peoples R China Anhui Agr Univ Sch Tea & Food Sand Technol Hefei 230036 Peoples R China Minist Agr & Rural Affairs Minist Educ State Key Lab Tea Plant Biol & Utilizat Key Lab Tea Biol & Tea ProcInt Joint Res Lab Tea Hefei 230036 Anhui Peoples R China

Tea is one of the most popular beverages worldwide. It is rich in substances, such as tea polyphenols and polysaccharides, that are closely related to human health. However, fresh tea leaves picked by machines are neither neat nor uniform. In this study, we apply a deep learning algorithm and the DELTA parallel robotic arm for high-precision and fast sorting of machine-picked fresh tea leaves. First, a convolutional neural network algorithm and a regional segmentation method are used to achieve fast identification and localization of machine-picked fresh tea leaves. Second, the actual running time model of the stepper motor at different pulse frequencies was established by the interpolation fitting method. The running times of the parallel mechanical arm associated with S-curve type acceleration and deceleration motions were calculated accurately using this model, and the sorting point of tea fresh leaves was then determined. A multi-objective, continuous sorting model of machine-picked fresh tea leaves is constructed to verify and optimize the model effects. The results of the robot's arm running-time test show that the running time from the end of the robotic arm's application to the fresh tea leaf sorting plane is in the range 500-1800 ms. The experimental results of fresh tea leaf recognition and classification show that after 150 iterations, the recognition accuracy of the validation set can reach 99.82%. Finally, the average sorting accuracy of the four experiments reach 89%, with the highest sorting accuracy reaching up to 92%. These results demonstrate that the proposed method leads to an excellent sorting effect pertaining to machine-picked fresh tea leaves. This approach could be easily applied to any agricultural product sorting application.

关键词： DELTA parallel robotic arm Convolutional neural network sorting robot Fresh tea leaf

来源：评论

学校读者我要写书评

暂无评论

Fully Automated Paper Document sorting robot Design

引用

Journal of Electronic Research and Application 2023年第6期7卷 1-9页

作者： Guo-Long Yang Biao-Hua Zhang Zhanjiang Preschool Education College Zhanjiang 524000Guangdong ProvinceChina

A fully automated paper document sorting robot was developed in this *** robot classifies documents efficiently and *** objective of this project was to improve the efficiency of classifying or sorting paper documents,reduce costs,and save *** robot can classify documents according to user-defined rules,such as keywords,dates,serial numbers,bar codes,and the meaning of *** it can classify or sort documents intelligently,it can complete large-scale document classification *** robot is constructed using an aluminum profile to create a box-type truss gantry structure *** was built on the LubanCat 4 motherboard and controlled through Python language *** by a stepper motor to move the *** camera module is combined with an artificial intelligence algorithm to recognize paper in real time,and the text is recognized after taking pictures of the *** sorting function is performed by several *** addition,a web-based human-computer interaction platform was developed using the Flask web framework in *** could access this platform in a variety of ways,allowing them to easily and swiftly configure parameters and send operational instructions to perform various functions.

关键词： Paper documents sorting robot Python Human-computer interaction

来源：评论

学校读者我要写书评

暂无评论

A Goods sorting robot System for E-Commerce Logistics Warehouse Based on robotic Arm Technology

A Goods Sorting Robot System for E-Commerce Logistics Wareho...

引用

IEEE International Conference on Real-time Computing and robotics (IEEE-RCAR)

作者： Wang, Yinghan Liang, Yi Chen, Diansheng Liu, Yongzhan Wang, Min Beihang Univ Sch Mech Engn & Automat Beijing Peoples R China

ISBN: (纸本)9781728172934

This paper proposed a goods sorting robot system, which is used in e-commerce logistics warehouse to lessen the workloads in logistics warehouses. The system comprises of three main modules, including a six-axis arm and its controller, motion planning software and the flexible end effector. This paper firstly introduced the whole structure of the sorting robot system, then introduced each function module in detail, and finally introduced the experiments to verify that the robot system meets its requirements.

关键词： six-axis robotic arm logistics warehouse sorting robot robot system integration

来源：评论

学校读者我要写书评

暂无评论

Design of a Flexible End-Effector for Logistics sorting robot

Design of a Flexible End-Effector for Logistics Sorting Robo...

引用

IEEE International Conference on Real-time Computing and robotics (IEEE-RCAR)

作者： Liang, Yi Li, Aojie Chen, Diansheng Xu, Ying Wang, Min Beihang Univ Sch Mech Engn & Automat Beijing Peoples R China

ISBN: (纸本)9781728172934

In this paper we propose an end-effector for goods sorting robot in the e-commerce logistics warehouse, which is used to enable the sorting robot to flexibly grasp a variety of logistics goods. Taking advantages of the multi-finger gripper and the suction tool, this paper provides a scheme combining a vacuum suction tool and a three-linger gripper. In order to measure the utility of the flexible end-effector, a picking experiment is performed. The result proves that the end-effector meets its requirements.

关键词： end-effector vacuum suction tool three-finger gripper logistics warehouse sorting robot

来源：评论

学校读者我要写书评

暂无评论

Optimization of Grasping Efficiency of a robot Used for sorting Construction and Demolition Waste

引用

International Journal of Automation and computing 2020年第5期17卷 691-700页

作者： Yue-Dong Ku Jian-Hong Yang Huai-Ying Fang Wen Xiao Jiang-Teng Zhuang College of Mechanical Engineering and Automation Huaqiao UniversityXiamen 361000China

The recycling of construction and demolition waste(CDW)remains an urgent problem to be *** the industry,raw CDW needs to be manually *** achieve high efficiency and avoid the risks of manual sorting,a sorting robot can be designed to grasp and sort CDW on a conveyor *** dynamic grasping on the conveyor belt is a *** collected location information with a three-dimensional camera and then evaluated the method of dynamic robotic *** paper discusses the grasping strategy of rough processed CDW on the conveyor belt,and implements the function of grasping and sorting on the recycling ***,two new mathematical models for a robotic locating system are established,the accuracy of the model is tested with Matlab,and the selected model is applied to actual working conditions to verify the sorting ***,the robot kinematics parameters are optimized to improve the sorting efficiency through experiments in a real system,and it was concluded that when the conveyor speed was kept at around 0.25 m/s,better sorting results could be *** the speed and shortening the acceleration/deceleration time would reach the maximum efficiency when the load would allow ***,the sorting efficiency reached approximately 2000 pieces per hour,showing a high accuracy.

关键词： Construction and demolition waste sorting robot grasping strategy mathematical models robot kinematics parameters

来源：评论

学校读者我要写书评

暂无评论

Designing and Manufacturing of sorting robot Based on Ability Storm robot

Designing and Manufacturing of Sorting Robot Based on Abilit...

引用

2015 International Conference on Automation,Mechanical and Electrical Engineering(AMEE 2015)

作者： Z.Yang N.L.Sun College of Information Science and Engineering Ocean University of China College of Information and Electrical Engineering Shandong University of Science and Technology

A simple sorting robot is designed and manufactured in order to simulate the sorting system for different objects sorting in a production line. The Grandar Ability Storm robot(AS-UII) was used as the controller of the sorting robot, and the innovation kits AS-EI were utilized to make the robot arm, and the VJC language was used to write the software program. After elaborative debugging, measuring, and running, a stable work of the robot can be achieved. The experiment results show that the detection and capturing ratios reach 94% and 91%, respectively, achieving the desired requirements.

关键词： sorting robot ability storm robot robot arm luminance detection innovation modules

来源：评论

学校读者我要写书评

暂无评论

A robot system equipped with deep convolutional neural network for autonomous grading and sorting of root-trimmed garlics

引用

COMPUTERS AND ELECTRONICS IN AGRICULTURE 2020年 178卷 105727-105727页

作者： Thuyet, Dang Quoc Kobayashi, Yuichi Matsuo, Morinobu Natl Agr & Food Res Org Inst Agr Machinery Kita Ku 1-40-2 Nisshin Saitama Saitama 3318537 Japan Natl Agr & Food Res Org Cent Reg Agr Res Ctr 768 Senbonmatsu Nasushiobara Tochigi 3292793 Japan

The demand for smart automation systems in postharvest technology, particularly in the postharvest process of garlic production, is high. In this study, we introduce an artificial intelligence (AI)-integrated robot system for grading and sorting of garlics after root trimming. We developed a robot system that automatically grades and sorts root-trimmed garlics based on image analysis using a deep learning model, which is equipped with a deep convolutional neural network (CNN). The robot system consists of three main modules: image acquisition module (IAM), image processing module (IPM), and garlic sorting module (GSM). The IAM captures a live video of garlic roots using an independent light-emitting diode (LED) and a web camera connected to a computer. The IPM consists of garlic image processing software (GIPS) installed on a Windows 10 computer. GIPS imports videos, detects the shape of garlic bulbs, and predicts the garlic class using the deep learning model. When a garlic bulb shape is detected, the image is preprocessed, and the deep learning model is automatically activated to predict the garlic class. The GSM physically separates garlics into three containers for good, bad, and scratched classes based on a previous predicted result. A total of 800 root-trimmed garlics were tested and evaluated in nine experiments. The processing time to predict classes from a garlic image on a regular laptop computer (Intel (R) core (TM) i7-8650U 1.9 GHz CPU, with 16 Gb RAM) was 0.19-0.58 s. The median time to trim and sort one garlic was 11 s (in a setting with three prediction replications), and the overall grading accuracy for the three classes was 89%. The individual predicted precision for the good, bad, and scratched classes was 95%, 68%, and 100%, respectively. Given that the robot system was robust and inexpensive, it has the potential to be integrated into a garlic root trimming machine to develop a fully automatic garlic root trimming and sorting robot.

关键词： Garlic root trimming Convolutional neural network Computer vision Autonomous grading sorting robot

来源：评论

学校读者我要写书评

暂无评论

robotics for control strategy optimization and simulation in automatic cigarette sorter

引用

COMPUTERS & ELECTRICAL ENGINEERING 2022年 99卷 107801-107801页

作者： Xu, Zhi Wang, Chuan Wang, Xin Zhang, JiaHai Sanjiang Univ Sch Mech & Elect Engn Nanjing 210012 Jiangsu Peoples R China China Tobacco Jiangsu Ind CO LTD Nanjing Cigarett Nanjing 210019 Jiangsu Peoples R China

In the world of advancement and rapid growth, new retail marketization and distribution require a substantial degree of versatility and resilience in the manufacturing plant to accommodate demand transitions. A Digital Matching Structure (DMS) is built such that real-time data from the framework for processing the physical goods can be aggregated and then translated into the digital context. A collaborative design approach is implemented in the DMS to automate stacked cigarette labelling and sorting. The periodic optimal decisions can be achieved from the joint optimization model by obtaining online details from the specific unit for the management network and then feeding them to the quasi-physical simulation platform in the DMS for validation of results. A sorting robot built-in DMS can be configured to catch and sort cigarettes on a conveyor belt to ensure high performance and eliminate the possibility of manual sorting. Digital Matching Structure - sorting robot (DMS-SR) is the solution recommended for the proposed integration. This article explores how finely packaged cigarettes are handled on the conveyor belt and how the packaging line works to understand and filter the product. The proposed integration method is assessed using appropriate mathematical models for validating its consistency and verifying the accuracy of sorting. Eventually, the proposed autonomous system parameters have been enhanced by tests on a real machine to boost the sorting performance. It was found that better sorting could be obtained when the conveyor speed of around 0.36 m/s. When there is sufficient load, growing the momentum and shortening the declaration/accelerationtime will produce the optimum efficacy. The DMS-SR currently has a sorting output of about 1900 cigarettes per hour, highly precise.

关键词： Digital matching structure sorting robot Joint optimization model

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：