{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,20]],"date-time":"2026-04-20T15:41:19Z","timestamp":1776699679969,"version":"3.51.2"},"reference-count":46,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T00:00:00Z","timestamp":1639094400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Advances are being made in applying digital twin (DT) and human\u2013robot collaboration (HRC) to industrial fields for safe, effective, and flexible manufacturing. Using a DT for human modeling and simulation enables ergonomic assessment during working. In this study, a DT-driven HRC system was developed that measures the motions of a worker and simulates the working progress and physical load based on digital human (DH) technology. The proposed system contains virtual robot, DH, and production management modules that are integrated seamlessly via wireless communication. The virtual robot module contains the robot operating system and enables real-time control of the robot based on simulations in a virtual environment. The DH module measures and simulates the worker\u2019s motion, behavior, and physical load. The production management module performs dynamic scheduling based on the predicted working progress under ergonomic constraints. The proposed system was applied to a parts-picking scenario, and its effectiveness was evaluated in terms of work monitoring, progress prediction, dynamic scheduling, and ergonomic assessment. This study demonstrates a proof-of-concept for introducing DH technology into DT-driven HRC for human-centered production systems.<\/jats:p>","DOI":"10.3390\/s21248266","type":"journal-article","created":{"date-parts":[[2021,12,10]],"date-time":"2021-12-10T08:17:58Z","timestamp":1639124278000},"page":"8266","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":88,"title":["Digital Twin-Driven Human Robot Collaboration Using a Digital Human"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0628-4828","authenticated-orcid":false,"given":"Tsubasa","family":"Maruyama","sequence":"first","affiliation":[{"name":"National Institute of Advanced Industrial Science and Technology, Koto-ku,  Tokyo 135-0064, Japan"}]},{"given":"Toshio","family":"Ueshiba","sequence":"additional","affiliation":[{"name":"National Institute of Advanced Industrial Science and Technology, Koto-ku,  Tokyo 135-0064, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6784-2016","authenticated-orcid":false,"given":"Mitsunori","family":"Tada","sequence":"additional","affiliation":[{"name":"National Institute of Advanced Industrial Science and Technology, Koto-ku,  Tokyo 135-0064, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8908-1561","authenticated-orcid":false,"given":"Haruki","family":"Toda","sequence":"additional","affiliation":[{"name":"National Institute of Advanced Industrial Science and Technology, Koto-ku,  Tokyo 135-0064, Japan"}]},{"given":"Yui","family":"Endo","sequence":"additional","affiliation":[{"name":"National Institute of Advanced Industrial Science and Technology, Koto-ku,  Tokyo 135-0064, Japan"}]},{"given":"Yukiyasu","family":"Domae","sequence":"additional","affiliation":[{"name":"National Institute of Advanced Industrial Science and Technology, Koto-ku,  Tokyo 135-0064, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6450-2099","authenticated-orcid":false,"given":"Yoshihiro","family":"Nakabo","sequence":"additional","affiliation":[{"name":"National Institute of Advanced Industrial Science and Technology, Koto-ku,  Tokyo 135-0064, Japan"}]},{"given":"Tatsuro","family":"Mori","sequence":"additional","affiliation":[{"name":"Toyota Motor Corporation, Toyota 471-8573, Japan"}]},{"given":"Kazutsugu","family":"Suita","sequence":"additional","affiliation":[{"name":"Toyota Motor Corporation, Toyota 471-8573, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2021,12,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"107992","DOI":"10.1016\/j.ijpe.2020.107992","article-title":"Industry 4.0 and the human factor\u2013A systems framework and analysis methodology for successful development","volume":"233","author":"Neumann","year":"2021","journal-title":"Int. J. Prod. Econ."},{"key":"ref_2","unstructured":"Grieves, M. (2014). Digital Twin: Manufacturing Excellence through Virtual Factory Replication, Michael Grieves, LLC. A White Paper."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.jmsy.2020.06.017","article-title":"Review of digital twin about concepts, technologies, and industrial applications","volume":"58","author":"Liu","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sepasgozar, S.M.E. (2021). Differentiating Digital Twin from Digital Shadow: Elucidating a Paradigm Shift to Expedite a Smart, Sustainable Built Environment. Buildings, 11.","DOI":"10.3390\/buildings11040151"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Oyekan, J., Farnsworth, M., Hutabarat, W., Miller, D., and Tiwari, A. (2020). Applying a 6 DoF Robotic Arm and Digital Twin to Automate Fan-Blade Reconditioning for Aerospace Maintenance, Repair, and Overhaul. Sensors, 20.","DOI":"10.3390\/s20164637"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"101917","DOI":"10.1016\/j.rcim.2019.101917","article-title":"Digital twin-enabled Graduation Intelligent Manufacturing System for fixed-position assembly islands","volume":"63","author":"Guo","year":"2020","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"101839","DOI":"10.1016\/j.rcim.2019.101839","article-title":"A digital twin-driven approach for the assembly-commissioning of high precision products","volume":"61","author":"Sun","year":"2020","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"26754","DOI":"10.1109\/ACCESS.2017.2773127","article-title":"Working Together: A Review on Safe Human-Robot Collaboration in Industrial Environments","volume":"5","author":"Becerra","year":"2017","journal-title":"IEEE Access"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Matheson, E., Minto, R., Zampieri, E.G.G., Faccio, M., and Rosati, G. (2019). Human\u2013Robot Collaboration in Manufacturing Applications: A Review. Robotics, 8.","DOI":"10.3390\/robotics8040100"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1016\/j.promfg.2018.10.047","article-title":"Digital twins of human robot collaboration in a production setting","volume":"17","author":"Malik","year":"2018","journal-title":"Procedia Manuf."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.promfg.2018.12.020","article-title":"Digital twin for adaptation of robots\u2019 behavior in flexible robotic assembly lines","volume":"28","author":"Kousi","year":"2019","journal-title":"Procedia Manuf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.procir.2018.02.010","article-title":"A Machine Learning-Enhanced Digital Twin Approach for Human- Robot-Collaboration","volume":"76","author":"Bobka","year":"2018","journal-title":"Procedia CIRP"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"105485","DOI":"10.1016\/j.cie.2018.10.046","article-title":"Motion Analysis System (MAS) for production and ergonomics assessment in the manufacturing processes","volume":"139","author":"Bortolini","year":"2020","journal-title":"Comput. Ind. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0003-6870(93)90080-S","article-title":"RULA: A survey method for the investigation of work-related upper limb disorders","volume":"24","author":"McAtamney","year":"1993","journal-title":"Appl. Ergon."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/S0003-6870(99)00039-3","article-title":"Rapid Entire Body Assessment (REBA)","volume":"31","author":"Hignett","year":"2000","journal-title":"Appl. Ergon."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1007\/s10055-010-0156-8","article-title":"Fatigue evaluation in maintenance and assembly operations by digital human simulation in virtual environment","volume":"15","author":"Ma","year":"2011","journal-title":"Virtual Real."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"194","DOI":"10.1016\/j.mechatronics.2018.08.006","article-title":"Seamless human robot collaborative assembly\u2013An automotive case study","volume":"55","author":"Michalos","year":"2018","journal-title":"Mechatronics"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Bonci, A., Cen Cheng, P.D., Indri, M., Nabissi, G., and Sibona, F. (2021). Human-Robot Perception in Industrial Environments: A Survey. Sensors, 21.","DOI":"10.3390\/s21051571"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.rcim.2018.10.003","article-title":"A cyber physical system (CPS) approach for safe human-robot collaboration in a shared workplace","volume":"56","author":"Nikolakis","year":"2019","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2602","DOI":"10.1109\/LRA.2020.2972874","article-title":"Towards Efficient Human-Robot Collaboration With Robust Plan Recognition and Trajectory Prediction","volume":"5","author":"Cheng","year":"2020","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"817","DOI":"10.1109\/TRO.2019.2911800","article-title":"Adaptive Motion Planning for a Collaborative Robot Based on Prediction Uncertainty to Enhance Human Safety and Work Efficiency","volume":"35","author":"Kanazawa","year":"2019","journal-title":"IEEE Trans. Robot."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Fera, M., Greco, A., Caterino, M., Gerbino, S., Caputo, F., Macchiaroli, R., and D\u2019Amato, E. (2020). Towards Digital Twin Implementation for Assessing Production Line Performance and Balancing. Sensors, 20.","DOI":"10.3390\/s20010097"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"837","DOI":"10.1016\/j.jmsy.2021.02.011","article-title":"A digital twin-driven human-robot collaborative assembly approach in the wake of COVID-19","volume":"60","author":"Lv","year":"2021","journal-title":"J. Manuf. Syst."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Zhang, S., Chen, Y., Zhang, J., and Jia, Y. (August, January 31). Real-Time Adaptive Assembly Scheduling in Human-Multi-Robot Collaboration Accord-ing to Human Capability*. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9196618"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1016\/j.cirp.2019.04.011","article-title":"Digital twin driven human\u2013robot collaborative assembly","volume":"68","author":"Bilberg","year":"2019","journal-title":"CIRP Ann."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"101998","DOI":"10.1016\/j.rcim.2020.101998","article-title":"Emerging research fields in safety and ergonomics in industrial collaborative robotics: A systematic literature review","volume":"67","author":"Gualtieri","year":"2021","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.rcim.2018.07.006","article-title":"The effectiveness of virtual environments in developing collaborative strategies between industrial robots and humans","volume":"55","author":"Oyekan","year":"2019","journal-title":"Robot. Comput. Integr. Manuf."},{"key":"ref_28","unstructured":"Veikko, L. (1992). OWAS: A Method for the Evaluation of Postural Load during Work, Institute of Occupational Health."},{"key":"ref_29","unstructured":"Waters, T.R., Putz-Anderson, V., and Garg, A. (1994). Applications Manual for the Revised NIOSH Lifting Equation, National Institute for Occupational Safety and Health."},{"key":"ref_30","unstructured":"Colombini, D., Occhipinti, E., and Alverez-Casado, E. (2013). The Revised OCRA Checklist Method, Editorial Factor Humans."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Maderna, R., Poggiali, M., Zanchettin, A.M., and Rocco, P. (August, January 31). An online scheduling algorithm for human-robot collaborative kitting. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9197431"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"der Spaa, L.V., Gienger, M., Bates, T., and Kober, J. (August, January 31). Predicting and Optimizing Ergonomics in Physical Human-Robot Cooperation Tasks. Proceedings of the 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France.","DOI":"10.1109\/ICRA40945.2020.9197296"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Greco, A., Caterino, M., Fera, M., and Gerbino, S. (2020). Digital Twin for Monitoring Ergonomics during Manufacturing Production. Appl. Sci., 10.","DOI":"10.3390\/app10217758"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"986","DOI":"10.1016\/j.promfg.2019.06.097","article-title":"Digital Human and Robot Simulation in Automotive Assembly using Siemens Process Simulate: A Feasibility Study","volume":"34","author":"Baskaran","year":"2019","journal-title":"Procedia Manuf."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"6093","DOI":"10.1007\/s12652-020-01926-y","article-title":"Analyzing the kinematic and kinetic contributions of the human upper body\u2019s joints for ergonomics assessment","volume":"11","author":"Menychtas","year":"2020","journal-title":"J. Ambient. Intell. Humaniz. Comput."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"376","DOI":"10.20965\/ijat.2014.p0376","article-title":"Hand modeling and motion reconstruction for individuals","volume":"8","author":"Endo","year":"2014","journal-title":"Int. J. Autom. Technol."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Endo, Y., Tada, M., and Mochimaru, M. (2015, January 2\u20137). Estimation of arbitrary human models from anthropometric dimensions. Proceedings of the International Conference on Digital Human Modeling and Applications in Health Safety, Ergonomics and Risk Management, Los Angeles, CA, USA.","DOI":"10.1007\/978-3-319-21070-4_1"},{"key":"ref_38","unstructured":"(2019, September 11). AIST Japanese Body Size Database. (In Japanese)."},{"key":"ref_39","unstructured":"(2021, December 08). OptiTrack Motive. Available online: https:\/\/optitrack.com\/software\/motive\/."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"122","DOI":"10.9746\/jcmsi.13.122","article-title":"Inertial Measurement Unit to Segment Calibration Based on Physically Constrained Pose Generation","volume":"13","author":"Maruyama","year":"2020","journal-title":"SICE J. Control. Meas. Syst. Integr."},{"key":"ref_41","unstructured":"Endo, Y., Tada, M., and Mochimaru, M. (2014, January 20\u201322). Dhaiba: Development of virtual ergonomic assessment system with human models. Proceedings of the 3rd International Digital Human Symposium, Tokyo, Japan."},{"key":"ref_42","unstructured":"Specification, O.M.G. (2021, December 08). The Real-Time Publish-Subscribe Protocol (RTPS) DDS Interoperability Wire Protocol Specification. Object Management Group Pct07-08-04. Available online: https:\/\/www.omg.org\/spec\/DDSI-RTPS\/2.2."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Yang, J., Sandstr\u00f6m, K., Nolte, T., and Behnam, M. (2012, January 17\u201321). Data Distribution Service for industrial automation. Proceedings of the 2012 IEEE 17th International Conference on Emerging Technologies Factory Automation (ETFA 2012), Krakow, Poland.","DOI":"10.1109\/ETFA.2012.6489544"},{"key":"ref_44","unstructured":"(2021, December 08). eProsima FastDDS. Available online: https:\/\/www.eprosima.com\/index.php\/products-all\/eprosima-fast-dds."},{"key":"ref_45","unstructured":"(2021, December 08). Xsens MTwAwinda. Available online: https:\/\/www.xsens.com\/products\/mtw-awinda."},{"key":"ref_46","unstructured":"(2021, December 08). AzureKinect DK. Available online: https:\/\/azure.microsoft.com\/en-us\/services\/kinect-dk\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/24\/8266\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:45:00Z","timestamp":1760168700000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/24\/8266"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,10]]},"references-count":46,"journal-issue":{"issue":"24","published-online":{"date-parts":[[2021,12]]}},"alternative-id":["s21248266"],"URL":"https:\/\/doi.org\/10.3390\/s21248266","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,12,10]]}}}