• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

由复杂自主系统服务的机电一体化生产线的建模与控制。

Modelling and Control of Mechatronics Lines Served by Complex Autonomous Systems.

机构信息

Department of Automation, Computer Science and Electrical Engineering, Valahia University of Târgoviște, 130024 Târgoviște, Romania.

Department of Automation and Electrical Engineering, Dunărea de Jos University of Galați, 800008 Galați, Romania.

出版信息

Sensors (Basel). 2019 Jul 24;19(15):3266. doi: 10.3390/s19153266.

DOI:10.3390/s19153266
PMID:31344960
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6695814/
Abstract

The aim of this paper is to reverse an assembly line, to be able to perform disassembly, using two complex autonomous systems (CASs). The disassembly is functioning only in case of quality default identified in the final product. The CASs are wheeled mobile robots (WMRs) equipped with robotic manipulators (RMs), working in parallel or collaboratively. The reversible assembly/disassembly mechatronics line (A/DML) assisted by CASs has a specific typology and is modelled by specialized hybrid instruments belonging to the Petri nets class, precisely synchronized hybrid Petri nets (SHPN). The need of this type of models is justified by the necessity of collaboration between the A/DML and CASs, both having characteristics and physical constraints that should be considered and to make all systems compatible. Firstly, the paper proposes the planning and scheduling of tasks necessary in modelling stage as well as in real time control. Secondly, two different approaches are proposed, related to CASs collaboration: a parallel approach with two CASs have simultaneous actions: one is equipped with robotic manipulator, used for manipulation, and the other is used for transporting. This approach is correlated with industrial A/D manufacturing lines where have to transport and handle weights in a wide range of variation. The other is a collaborative approach, A/DML is served by two CASs used for manipulation and transporting, both having simultaneous movements, following their own trajectories. One will assist the disassembly in even, while the other in odd workstations. The added value of this second approach consists in the optimization of a complete disassembly cycle. Thirdly, it is proposed in the paper the real time control of mechatronics line served by CASs working in parallel, based on the SHPN model. The novelty of the control procedure consists in the use of the synchronization signals, in absence of the visual servoing systems, for a precise positioning of the CASs serving the reversible mechatronics line.

摘要

本文旨在通过两个复杂的自主系统 (CAS) 实现流水线的反向操作，以便执行拆卸。只有在最终产品中发现质量缺陷的情况下，拆卸才会进行。CAS 是配备有机器人操作器 (RM) 的轮式移动机器人 (WMR)，它们可以并行或协作工作。由 CAS 辅助的可反向装配/拆卸机电一体化线 (A/DML) 具有特定的类型，通过属于 Petri 网类的专用混合仪器进行建模，即精确同步混合 Petri 网 (SHPN)。需要这种类型的模型是因为 A/DML 和 CAS 之间需要协作，两者都具有需要考虑的特性和物理约束，以使所有系统兼容。首先，本文提出了在建模阶段和实时控制中进行任务规划和调度的必要性。其次，提出了两种与 CAS 协作相关的不同方法：一种是并行方法，两个 CAS 同时行动：一个配备有机器人操作器，用于操作，另一个用于运输。这种方法与工业 A/D 制造线相关联，其中必须在广泛的变化范围内运输和处理重量。另一种是协作方法，由两个用于操作和运输的 CAS 为 A/DML 提供服务，两者同时移动，遵循各自的轨迹。一个将协助偶数工作站的拆卸，另一个将协助奇数工作站的拆卸。第二种方法的附加值在于完整拆卸周期的优化。第三，本文提出了基于 SHPN 模型的由并行工作的 CAS 控制机电一体化线的实时控制。控制过程的新颖之处在于使用同步信号，而不是视觉伺服系统，以精确定位为可逆机电一体化线服务的 CAS。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/36a2c1622bde/sensors-19-03266-g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/0d3f6a533b14/sensors-19-03266-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/63e8b8066524/sensors-19-03266-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/c2899832a62a/sensors-19-03266-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/d11cfb2ce6a2/sensors-19-03266-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/922380024568/sensors-19-03266-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/a35c0c7cc0e4/sensors-19-03266-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/24337ebbe3e9/sensors-19-03266-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/702d55e7132f/sensors-19-03266-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/5da98b9a9ca0/sensors-19-03266-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/01e737e86c52/sensors-19-03266-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/bcf0807a64b8/sensors-19-03266-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/06078aea213a/sensors-19-03266-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/9d9918ae1df0/sensors-19-03266-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/2150280ea4bf/sensors-19-03266-g014a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/42a792d367b1/sensors-19-03266-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/9e12b7bb6b5c/sensors-19-03266-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/71306639b83a/sensors-19-03266-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/5be14da4eb8d/sensors-19-03266-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/501d097aaf95/sensors-19-03266-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/8bd10d3768ae/sensors-19-03266-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/33c7e6b02891/sensors-19-03266-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/27f1798217c6/sensors-19-03266-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/36a2c1622bde/sensors-19-03266-g023.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/0d3f6a533b14/sensors-19-03266-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/63e8b8066524/sensors-19-03266-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/c2899832a62a/sensors-19-03266-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/d11cfb2ce6a2/sensors-19-03266-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/922380024568/sensors-19-03266-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/a35c0c7cc0e4/sensors-19-03266-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/24337ebbe3e9/sensors-19-03266-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/702d55e7132f/sensors-19-03266-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/5da98b9a9ca0/sensors-19-03266-g009a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/01e737e86c52/sensors-19-03266-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/bcf0807a64b8/sensors-19-03266-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/06078aea213a/sensors-19-03266-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/9d9918ae1df0/sensors-19-03266-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/2150280ea4bf/sensors-19-03266-g014a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/42a792d367b1/sensors-19-03266-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/9e12b7bb6b5c/sensors-19-03266-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/71306639b83a/sensors-19-03266-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/5be14da4eb8d/sensors-19-03266-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/501d097aaf95/sensors-19-03266-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/8bd10d3768ae/sensors-19-03266-g020.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/33c7e6b02891/sensors-19-03266-g021.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/27f1798217c6/sensors-19-03266-g022.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0a3e/6695814/36a2c1622bde/sensors-19-03266-g023.jpg

相似文献

1
Modelling and Control of Mechatronics Lines Served by Complex Autonomous Systems.由复杂自主系统服务的机电一体化生产线的建模与控制。
Sensors (Basel). 2019 Jul 24;19(15):3266. doi: 10.3390/s19153266.
2
Digital Twin for a Multifunctional Technology of Flexible Assembly on a Mechatronics Line with Integrated Robotic Systems and Mobile Visual Sensor-Challenges towards Industry 5.0.数字孪生在机电一体化线上的多功能柔性装配技术中的应用——集成机器人系统和移动视觉传感器，面向工业 5.0 的挑战。
Sensors (Basel). 2022 Oct 25;22(21):8153. doi: 10.3390/s22218153.
3
Magnetic resonance-compatible robotic and mechatronics systems for image-guided interventions and rehabilitation: a review study.用于图像引导介入和康复的磁共振兼容机器人与机电一体化系统：一项综述研究。
Annu Rev Biomed Eng. 2007;9:351-87. doi: 10.1146/annurev.bioeng.9.121806.160642.
4
Robust dead reckoning system for mobile robots based on particle filter and raw range scan.基于粒子滤波器和原始距离扫描的移动机器人鲁棒航位推算系统。
Sensors (Basel). 2014 Sep 4;14(9):16532-62. doi: 10.3390/s140916532.
5
Performance evaluation of 3D vision-based semi-autonomous control method for assistive robotic manipulator.基于3D视觉的辅助机器人操纵器半自动控制方法的性能评估
Disabil Rehabil Assist Technol. 2018 Feb;13(2):140-145. doi: 10.1080/17483107.2017.1299804. Epub 2017 Mar 22.
6
OMNIVIL-An Autonomous Mobile Manipulator for Flexible Production.OMNIVIL—用于灵活生产的自主移动机器人
Sensors (Basel). 2020 Dec 17;20(24):7249. doi: 10.3390/s20247249.
7
Cable-based parallel manipulator for rehabilitation of shoulder and elbow movements.用于肩部和肘部运动康复的基于缆绳的并联机器人
IEEE Int Conf Rehabil Robot. 2011;2011:5975503. doi: 10.1109/ICORR.2011.5975503.
8
A Single RF Emitter-Based Indoor Navigation Method for Autonomous Service Robots.基于单个射频发射器的自主服务机器人室内导航方法。
Sensors (Basel). 2018 Feb 14;18(2):585. doi: 10.3390/s18020585.
9
Development of an autonomous biological cell manipulator with single-cell electroporation and visual servoing capabilities.一种具有单细胞电穿孔和视觉伺服功能的自主生物细胞操纵器的开发。
IEEE Trans Biomed Eng. 2009 Aug;56(8):2064-74. doi: 10.1109/TBME.2009.2021577.
10
Cost-effectiveness analysis for computer-aided surgical simulation in complex cranio-maxillofacial surgery.复杂颅颌面外科手术中计算机辅助手术模拟的成本效益分析
J Oral Maxillofac Surg. 2006 Dec;64(12):1780-4. doi: 10.1016/j.joms.2005.12.072.

引用本文的文献

1
IoT-Cloud, VPN, and Digital Twin-Based Remote Monitoring and Control of a Multifunctional Robotic Cell in the Context of AI, Industry, and Education 4.0 and 5.0.在人工智能、工业4.0和5.0以及教育4.0和5.0背景下，基于物联网云、VPN和数字孪生的多功能机器人单元远程监控与控制
Sensors (Basel). 2024 Nov 22;24(23):7451. doi: 10.3390/s24237451.
2
Digital Twin for a Multifunctional Technology of Flexible Assembly on a Mechatronics Line with Integrated Robotic Systems and Mobile Visual Sensor-Challenges towards Industry 5.0.数字孪生在机电一体化线上的多功能柔性装配技术中的应用——集成机器人系统和移动视觉传感器，面向工业 5.0 的挑战。
Sensors (Basel). 2022 Oct 25;22(21):8153. doi: 10.3390/s22218153.

本文引用的文献

1
An Approach to Robust INS/UWB Integrated Positioning for Autonomous Indoor Mobile Robots.一种用于自主室内移动机器人的稳健 INS/UWB 集成定位方法。
Sensors (Basel). 2019 Feb 23;19(4):950. doi: 10.3390/s19040950.
2
Smart Sensors Applications for a New Paradigm of a Production Line.智能传感器在生产线新纪元中的应用。
Sensors (Basel). 2019 Feb 5;19(3):650. doi: 10.3390/s19030650.
3
An Approach for Managing Manufacturing Assets through Radio Frequency Energy Harvesting.通过射频能量收集管理制造资产的方法。
Sensors (Basel). 2019 Jan 22;19(3):438. doi: 10.3390/s19030438.
4
Path Smoothing Techniques in Robot Navigation: State-of-the-Art, Current and Future Challenges.机器人导航中的路径平滑技术：现状、当前挑战与未来挑战。
Sensors (Basel). 2018 Sep 19;18(9):3170. doi: 10.3390/s18093170.
5
Self-Diagnosis of Localization Status for Autonomous Mobile Robots.自主移动机器人的定位状态自诊断。
Sensors (Basel). 2018 Sep 19;18(9):3168. doi: 10.3390/s18093168.