Industrial Collaborative Robot Digital Twin integration and Control Using Robot Operating System
 
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1
Mechanical and Industrial engineering, Tallinn University of Technology, Estonia
 
2
Department of Electronics and Computer Engineering, Technological University of the Shannon: Midlands Midwest, Ireland
 
 
Submission date: 2022-01-29
 
 
Final revision date: 2022-03-11
 
 
Acceptance date: 2022-04-06
 
 
Online publication date: 2022-04-18
 
 
Publication date: 2022-06-28
 
 
Corresponding author
Simone Luca Pizzagalli   

Mechanical and Industrial engineering, Tallinn University of Technology, Ehitajate tee 5, 12616, Tallinn, Estonia
 
 
Journal of Machine Engineering 2022;22(2):57-67
 
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ABSTRACT
Universal solutions for industrial robot integration are urgent requirements for companies looking for machine interconnectivity, and tailor-made manufacturing systems design. These solutions must be supported by modular and open-source components and Extended Reality (XR) interfaces. Robot Operating System (ROS) has proven to be a reliable, interoperable and modular standard for industrial robot integration. Digital Twins (DT) of industrial equipment and processes offer a solid base to develop innovative digital tools relying on synchronization between physical and digital entities and the setup of XR interfaces for teleoperation and programming. This work presents the integration of the OMRON TM5-9000 collaborative industrial robot into the IVAR laboratory DT system at Tallinn University of Technology. By using Unity3D game engine and developing a ROS package for the specific machine, the digital model of the collaborative robot is integrated into the existing twin, synchronized with the real counterpart, and controlled by a remote user interface.
REFERENCES (23)
1.
BASTIDAS-CRUZ A., HEIMANN O., HANINGER K., KRÜGER J., 2020, Information Requirements and Interfaces for the Programming of Robots in Flexible Manufacturing, Annals of Scientific Society for Assembly, Handling and Industrial Robotics, 183–192.
 
2.
SHERWANI F., ASAD M.M., IBRAHIM B.S.K.K., 2020, Collaborative Robots and Industrial Revolution 4.0 (IR 4.0), 2020 International Conference on Emerging Trends in Smart Technologies, ICETST 2020.
 
3.
ROMERO D., BERNUS P., NORAN O., STAHRE J., FAST-BERGLUND A., 2016, The Operator 4.0: Human Cyber-Physical Systems & Adaptive Automation Towards Human-Automation Symbiosis Work Systems, IFIP Advances in Information and Communication Technology, 677–686.
 
4.
QUIGLEY M., CONLEY K., GERKEY B., FAUST J., FOOTE T., LEIBS J., WHEELER R., NG A.Y., 2009, ROS: an Open-Source Robot Operating System, ICRA Workshop on Open Source Software, 3, 5.
 
6.
GUTIERREZ C.S.V., JUAN L.U.S., UGARTE I.Z., GOENAGA I.M., KIRSCHGENS L.A., VILCHES V.M., 2018, Time Synchronization in Modular Collaborative Robots, rXiv:1809.07295.
 
7.
MOKARAM S., AITKEN J.M., MARTINEZ-HERNANDEZ U., EIMONTAITE I., CAMERON D., ROLPH J., GWILT I., MCAREE O., LAW J., 2017, A ROS-Integrated API for the KUKA LBR iiwa Collaborative Robot IFAC-PapersOnLine 50 15859–64.
 
8.
KALLWEIT S., WALENTA R., GOTTSCHALK M., 2016, ROS Based Safety Concept for Collaborative Robots in Industrial Applications, Advances in Intelligent Systems and Computing, 27–35.
 
9.
KUTS V., RASSOLKIN A., PARTYSHEV A., JEGOROV S., RJABTSIKOV V., 2021, ROS Middle-Layer Integration to Unity 3D as an Interface Option for Propulsion Drive Simulations of Autonomous Vehicles IOP Conference Series: Materials Science and Engineering, 1140 012008.
 
10.
BAKLOUTI S., GALLOT G., VIAUD J., SUBRIN K., 2021, On the Improvement of Ros-Based Control for Teleoperated Yaskawa Robots, Applied Sciences (Switzerland), 11.
 
11.
KREITZ J., LEE M., SUBPARK H., OH P.Y., OH J.H., 2020, Implementing ROS Communications for Sensor Integration with the RB5 Collaborative Robot, 2020 10th Annual Computing and Communication Workshop and Conference, 378–383.
 
12.
SITA E., HORVATH C.M., THOMESSEN T., KORONDI P., PIPE A.G., 2018, ROS-Unity3D Based System for Monitoring of an Industrial Robotic Process, 2017 IEEE/SICE International Symposium on System Integration, 1047–1052.
 
13.
MADDIKUNTA P.K.R., PHAM Q-V., PRABADEVI B., DEEPA N., DEV K., GADEKALLU T.R, RUBY R., LIYANAGE M., 2021, Industry 5.0: A Survey on Enabling Technologies and Potential Applications, Journal of Industrial Information Integration, 100257.
 
14.
KUTS V., CHEREZOVA N., SARKANS M., OTTO T., 2020, Digital Twin: Industrial Robot Kinematic Model Integration to the Virtual Reality Environment, Journal of Machine Engineering, 20/2, 53–64.
 
15.
KUTS V., OTTO T., BONDARENKO Y., YU F., 2020, Digital Twin: Collaborative Virtual Reality Environment for Multi-Purpose Industrial Applications, ASME International Mechanical Engineering Congress and Exposition, Proceedings, IMECE2020-23390, V02BT02A010.
 
16.
BILBERG A., MALIK A.A., 2019, Digital Twin Driven Human–Robot Collaborative Assembly, CIRP Annals, 68/1, 499–502.
 
17.
PEREZ L., RODRIGUEZ-JIMENEZ S., RODRIGUEZ N., USAMENTIAGA R., GARCIA D.F., 2020, Digital Twin and Virtual Reality Based Methodology for Multi-Robot Manufacturing Cell Commissioning, Applied Sciences 10 3633.
 
18.
SIEGELE D., STEINER D., GIUSTI A., RIEDL M., MATT D.T., 2021, Optimizing Collaborative Robotic Workspaces in Industry by Applying Mixed Reality, International Conference on Augmented Reality, Virtual Reality and Computer Graphics, 544–559.
 
19.
MARVEL J.A., BAGCHI S., ZIMMERMAN M., AKSU M., ANTONISHEK B., LI X., WANG Y., MEAD R., FONG T., BEN AMOR H., 2021, Novel and Emerging Test Methods and Metrics for Effective HRI, ACM/IEEE International Conference on Human-Robot Interaction, 730–732.
 
20.
KOUSI N., GKOURNELOS C., AIVALIOTIS S., LOTSARIS K., BAVELOS A.C., BARIS P., MICHALOS G., MAKRIS S., 2021, Digital Twin for Designing and Reconfiguring Human–Robot Collaborative Assembly Lines, Applied Sciences (Switzerland), 11.
 
22.
KUTS V., MODONI G.E., OTTO T., SACCO M., TÄHEMAA T., BONDARENKO Y., WANG R., 2019, Synchronizing Physical Factory and its Digital Twin Throughan iiot Middleware: A case study, Proceedings of the Estonian Academy of Sciences, 68, 364–70.
 
 
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ISSN:1895-7595
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