2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)最新文献_第2页

Virtual commissioning of a robotic cell: an educational case study 机器人细胞的虚拟调试:一个教育案例研究

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8869373

Igor Azkarate Fernández, Mikel Ayani Eguía, Luka Eciolaza Echeverría

引用次数: 8

OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources OPC UA节点集本体作为表示制造资源语义数字孪生的支柱

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8868954

A. Perzylo, Stefan Profanter, Markus Rickert, A. Knoll

{"title":"OPC UA NodeSet Ontologies as a Pillar of Representing Semantic Digital Twins of Manufacturing Resources","authors":"A. Perzylo, Stefan Profanter, Markus Rickert, A. Knoll","doi":"10.1109/ETFA.2019.8868954","DOIUrl":"https://doi.org/10.1109/ETFA.2019.8868954","url":null,"abstract":"The effectiveness of cognitive manufacturing systems in agile production environments heavily depend on the automatic assessment of various levels of interoperability between manufacturing resources. For taking informed decisions, a semantically rich representation of all resources in a workcell or production line is required. OPC UA provides means for communication and information exchange in such distributed settings.This paper proposes a semantic representation of a resource’s properties, in which we use OWL ontologies to encode the information models that can be found in OPC UA NodeSet specifications. We further combine these models with an OWL-based description of the resource’s geometry and – if applicable – its kinematic model. This leads to a comprehensive semantic representation of hardware and software features of a manufacturing resource, which we call semantic digital twin. Among other things, it reduces costs through virtual prototyping and enables the automatic deployment of manufacturing tasks in production lines. As a result, small-batch assemblies become financially viable.In order to minimize the effort of creating OWL-based UA NodeSet descriptions, we provide a software tool for the automatic transformation of XML-based NodeSet specifications that adhere to the OPC Foundation’s NodeSet2 XML schema.","PeriodicalId":6682,"journal":{"name":"2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"34 1","pages":"1085-1092"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75588480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 22

Cognitive Assistance Systems For Dynamic Environments 动态环境的认知辅助系统

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8868986

Rainer Müller, L. Hörauf, Attique Bashir

引用次数: 4

Self-adaptive Cobots in Cyber-Physical Production Systems 网络物理生产系统中的自适应协作机器人

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8869165

Roberto Nogueira, João C. P. Reis, R. Pinto, G. Gonçalves

{"title":"Self-adaptive Cobots in Cyber-Physical Production Systems","authors":"Roberto Nogueira, João C. P. Reis, R. Pinto, G. Gonçalves","doi":"10.1109/ETFA.2019.8869165","DOIUrl":"https://doi.org/10.1109/ETFA.2019.8869165","url":null,"abstract":"Absolute automation in certain industries, such as the automotive industry, has proven to be disadvantageous. Robots are fairly capable when performing tasks that are repetitive and demand precision. However, a hybrid solution comprised of the adaptability and resourcefulness of humans cooperating, in the same task, with the precision and efficiency of machines is the next step for automation. Manipulators, however, lack self-adaptability and true collaborative behaviour. And so, through the integration of vision systems, manipulators can perceive their environment and also understand complex interactions. In this paper, a vision-based collaborative proof-of-concept framework is proposed using the Kinect v2, a UR5 robotic manipulator and MATLAB. This framework implements 3 behavioural modes, 1) a Self-Adaptive mode for obstacle detection and avoidance, 2) a Collaborative mode for physical human-robot interaction and 3) a standby Safe mode. These modes are activated with recourse to gestures, by virtue of the body tracking and gesture recognition algorithm of the Kinect v2. Additionally, to allow self-recognition of the robot, the Region Growing segmentation is combined with the UR5’s Forward Kinematics for precise, near real-time segmentation. Furthermore, self-adaptive reactive behaviour is implemented by using artificial repulsive action for the manipulator’s end-effector. Reaction times were tested for all three modes, being that Collaborative and Safe mode would take up to 5 seconds to accomplish the movement, while Self-Adaptive mode could take up to 10 seconds between reactions.","PeriodicalId":6682,"journal":{"name":"2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"44 1","pages":"521-528"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80138731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Tying Together Solutions for Digital Manufacturing: Assessment of Connectivity Technologies & Approaches 将数字制造解决方案捆绑在一起:连接技术和方法的评估

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8869411

Greg Hawkridge, M. P. Hernández, Lavindra de Silva, G. Terrazas, Yedige Tlegenov, D. McFarlane, Alan Thorne

引用次数: 10

An MPC Framework for Online Motion Planning in Human-Robot Collaborative Tasks 人机协作任务在线运动规划的MPC框架

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8869047

M. Faroni, M. Beschi, N. Pedrocchi

引用次数: 23

A new architecture for the design of virtual/remote labs: The coupled drives system as a case of study 虚拟/远程实验室设计的一种新架构:以耦合驱动系统为例

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8869192

Jacobo Sáenz, L. D. L. Torre, J. Chacón, S. Dormido

引用次数: 6

Cybersecurity in Industrial Control Systems [breaker page] 工业控制系统中的网络安全

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/etfa.2019.8869177

引用次数: 0

Placement of Passive UHF RFID Tags and Readers Using Graph Models 无源超高频RFID标签和阅读器使用图形模型的位置

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8869196

O. Gan

引用次数: 1

An efficient genetic method for multi-objective continuous production scheduling in Industrial Internet of Things 工业物联网中多目标连续生产调度的高效遗传算法

2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) Pub Date : 2019-09-01 DOI: 10.1109/ETFA.2019.8869049

Ke Shen, Joachim David, Toon De Pessemier, L. Martens, W. Joseph

引用次数: 4