{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T11:42:57Z","timestamp":1782301377418,"version":"3.54.5"},"reference-count":24,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T00:00:00Z","timestamp":1705881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>This article discusses creating a methodology for the asymmetric measuring of values and processes of collision forces and pressures of the collaborative robot dependent on time. Furthermore, it verifies the usefulness of this methodology in practice by successfully performing the experimental measurement and verifying the possibility of using these results by analysing and stating the collaboration level for a robot of the given type. According to the suggested methodology, the measurement results are a specific output based on real measured data, which can be easily rated and can quickly determine the collaborative level of any robot. Measurements were aimed at determining the values of pressure and force with which the robot acts at certain speeds related to distance from the base. Due to the controlled symmetrical impact of the robot on the measuring device, the transfer of energy from the robot to the human body was guaranteed. In theoretical terms, this article primarily provides the assembly of the theoretical foundation of the collaborative environment between humans and robots, and a comprehensive overview of the possibilities of using the technical specification ISO\/TS 15066:2016 when deploying a robot in collaboration with humans in a collaborative environment. This new information is highly valuable for both manufacturers and users of collaborative robots. The presented article analyses the possibilities of measuring collaboration and safety elements in cooperation with a robot. The most significant practical benefit is the presentation of a methodology for measuring robot collaboration and verifying its functionality by conducting experimental measurements of robot collaboration according to this methodology. The measurement was performed on a robot made by Universal Robots, model UR10. The measurement coordinates were stationed in a way to create a spatial measurement model. Boundary coordinates of the spatial model were as follows: [450; 200], [450; 500], [850; 200], and [850; 500]. Collisions were measured at 8 different speeds for each coordinate (20 mms\u22121, 50 mms\u22121, 100 mms\u22121, 200 mms\u22121, 250 mms\u22121, 300 mms\u22121, 350 mms\u22121, and 400 mms\u22121) to enable the observation of changes in accordance with speed. The measured values indicate a significant fact: the closer the collision is to the robot\u2019s base, the higher the collision forces. An important aspect is that the measured values were only for speeds up to 400 mms\u22121, which is a very low value for industrial use to meet the desired cycle time. It can be stated with absolute certainty that speed has the greatest impact on collision force values. The speed of the collaborative robot arm can therefore be considered a limiting factor for use in industrial applications with a requirement of a short cycle time. Focusing on the results of the measured values, it can be stated that a new finding is the correct design of robotic movements in relation to possible contact with humans is crucial. The result of the measurement according to the proposed methodology is a specific output of realistically measured data, which can be easily evaluated and the level of collaboration of any robot can be quickly determined. The measured data will also serve as a basis for further processing and preparation of new simulation software. It will be possible to use the intended software for detecting and predetermining the safe asymmetric movements of the collaborative robot already at the stage of production preparations, unlike the method of measuring force and pressure on robots which can be used until the time of implementation into production. In the future, this software may also allow users of collaborative robots to easily and quickly evaluate the robots specified.<\/jats:p>","DOI":"10.3390\/sym16010131","type":"journal-article","created":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T11:36:41Z","timestamp":1705923401000},"page":"131","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Force and Pressure Dependent Asymmetric Workspace Research of a Collaborative Robot and Human"],"prefix":"10.3390","volume":"16","author":[{"given":"Josef","family":"Ponikelsk\u00fd","sequence":"first","affiliation":[{"name":"Faculty of Mechanical Engineering, University of Jan Evangelista Purkyne in Ust\u00ed nad Labem, Pasteurova 1, 40096 Ust\u00ed nad Labem, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9366-1371","authenticated-orcid":false,"given":"Milan","family":"Chalupa","sequence":"additional","affiliation":[{"name":"Faculty of Military Technology, University of Defence in Brno, 66210 Brno, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6816-1124","authenticated-orcid":false,"given":"V\u00edt","family":"\u010cernohl\u00e1vek","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical Engineering, University of Jan Evangelista Purkyne in Ust\u00ed nad Labem, Pasteurova 1, 40096 Ust\u00ed nad Labem, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan","family":"\u0160t\u011brba","sequence":"additional","affiliation":[{"name":"Faculty of Mechanical Engineering, University of Jan Evangelista Purkyne in Ust\u00ed nad Labem, Pasteurova 1, 40096 Ust\u00ed nad Labem, Czech Republic"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,22]]},"reference":[{"key":"ref_1","unstructured":"(2011). Roboty a Robotick\u00e1 Za\u0159\u00edzen\u00ed\u2014Po\u017eadavky na Bezpe\u010dnost Pr\u016fmyslov\u00fdch Robot\u016f: \u010c\u00e1st 2: Syst\u00e9my Robot\u016f a Integrace. Standard No. \u010cSN EN ISO 10218-2."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Javernik, A., Kovi\u010d, K., Pal\u010di\u010d, I., and Ojster\u0161ek, R. (2023). Audio-Visual Effects of a Collaborative Robot on Worker Efficiency. Symmetry, 15.","DOI":"10.3390\/sym15101907"},{"key":"ref_3","unstructured":"(2016). Robots and Robotic Devices\u2014Collaborative Robots. Standard No. ISO\/TS 15066."},{"key":"ref_4","unstructured":"Matthias, B., and Reisinger, T. (2016, January 21\u201322). Example Application of ISO\/TS 15066 to a Collaborative Assembly Scenario. Proceedings of the ISR 2016 47st International Symposium on Robotics, Munich, Germany."},{"key":"ref_5","unstructured":"Triebig, G. Druckschmerzschwellen bei Druckreizen, 51. Jahrestagung der Deutschen Gesellschaft f\u00fcr Arbeitsmedizin und Umweltmedizin (DGAUM), Deutsche Gesellschaft f\u00fcr Arbeitsmedizin und Umweltmedizin."},{"key":"ref_6","unstructured":"Kossman, M. (2019). Sicherheit in der Mensch-Roboter-Interaktion durch Einen Biofidelen Bewertungsansatz. [Ph.D. Thesis, Technische Universit\u00e4t M\u00fcnchen]."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"\u0160varn\u00fd, P. (2020). 3D Collision-Force-Map for Safe Human-Robot Collaboration, \u010cVUT.","DOI":"10.1109\/ICRA48506.2021.9561845"},{"key":"ref_8","unstructured":"Behrens, R., and Zimmermann, J. (2021, November 03). Determination of Biomechanical Corridors for the Evaluation of Mechanical Hazards and Estimation of Stiffness Parameters for Future Measurement Devices\u2014Final Report on the Research Project of Fraunhofer IFF and IFA. Available online: https:\/\/www.dguv.de\/medien\/ifa\/en\/fac\/kollaborierende_roboter\/ifa-skl_final_report.pdf."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Suszy\u0144ski, M., Peta, K., \u010cernohl\u00e1vek, V., and Svoboda, M. (2022). Mechanical Assembly Sequence Determination Using Artificial Neural Networks Based on Selected DFA Rating Factors. Symmetry, 14.","DOI":"10.3390\/sym14051013"},{"key":"ref_10","first-page":"904","article-title":"No Clamp Robotic Assembly with Use of Point Cloud Data from Low-Cost Triangulation Scanner","volume":"25","author":"Suszynski","year":"2018","journal-title":"Teh. Vjesn."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Klimenda, F., Cizek, R., and Suszynski, M. (2022). Measurement of a Vibration on a Robotic Vehicle. Sensors, 22.","DOI":"10.3390\/s22228649"},{"key":"ref_12","first-page":"99","article-title":"Research of Robots in Cooperative Mode in Human Body Part Detection","volume":"23","author":"Ponikelsky","year":"2023","journal-title":"Manuf. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Mathavan Jeyabalan, P.K., Nehrujee, A., Elias, S., Magesh Kumar, M., Sujatha, S., and Balasubramanian, S. (2023). Design and Characterization of a Self-Aligning End-Effector Robot for Single-Joint Arm Movement Rehabilitation. Robotics, 12.","DOI":"10.20944\/preprints202307.2117.v1"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Zhang, X., Yang, F., Jin, Q., Lou, P., and Hu, J. (2023). Path Planning Algorithm for Dual-Arm Robot Based on Depth Deterministic Gradient Strategy Algorithm. Mathematics, 11.","DOI":"10.3390\/math11204392"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"P\u00e1stor, M., Hagara, M., Ga\u0161p\u00e1r, \u0160., and Sapieta, M. (2023). Design and Implementation of a Low-Cost Torque Sensor for Manipulators. Appl. Sci., 13.","DOI":"10.3390\/app13169406"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Suszy\u0144ski, M., and Peta, K. (2021). Assembly Sequence Planning Using Artificial Neural Networks for Mechanical Parts Based on Selected Criteria. Appl. Sci., 11.","DOI":"10.3390\/app112110414"},{"key":"ref_17","first-page":"357","article-title":"Draft of robotic workstation for laser engraving","volume":"21","author":"Klimenda","year":"2021","journal-title":"Manuf. Technol."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Batista, J.G., Ramalho, G.L.B., Torres, M.A., Oliveira, A.L., and Ferreira, D.S. (2023). Collision Avoidance for a Selective Compliance Assembly Robot Arm Manipulator Using Topological Path Planning. Appl. Sci., 13.","DOI":"10.3390\/app132111642"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Carriero, G., Calzone, N., Sileo, M., Pierri, F., Caccavale, F., and Mozzillo, R. (2023). Human-Robot Collaboration: An Augmented Reality Toolkit for Bi-Directional Interaction. Appl. Sci., 13.","DOI":"10.3390\/app132011295"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Herbster, S., Behrens, R., and Elkmann, N. (2023). Modeling the Contact Force in Constrained Human-Robot Collisions. Machines, 11.","DOI":"10.3390\/machines11100955"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Yan, Y., Su, H., and Jia, Y. (2023). Modeling and Analysis of Human Comfort in Human-Robot Collaboration. Biomimetics, 8.","DOI":"10.3390\/biomimetics8060464"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Cernohlavek, V., Klimenda, F., Houska, P., and Suszy\u0144ski, M. (2023). Vibration Measurements on a Six-Axis Collaborative Robotic Arm\u2014Part I. Sensors, 23.","DOI":"10.3390\/s23031629"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Toledano-Garc\u00eda, A.A., P\u00e9rez-Cabrera, H.R., Ortega-Cabrera, D., Navarro-Dur\u00e1n, D., and P\u00e9rez-Hern\u00e1ndez, E.M. (2023). Trajectory Generator System for a UR5 Collaborative Robot in 2D and 3D Surfaces. Machines, 11.","DOI":"10.3390\/machines11090916"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Anatoliotakis, N., Paraskevopoulos, G., Michalakis, G., Michalellis, I., Zacharaki, E.I., Koustoumpardis, P., and Moustakas, K. (2023). Dynamic Human-Robot Collision Risk Based on Octree Representation. Machines, 11.","DOI":"10.3390\/machines11080793"}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/16\/1\/131\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:47:19Z","timestamp":1760104039000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/16\/1\/131"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1,22]]},"references-count":24,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2024,1]]}},"alternative-id":["sym16010131"],"URL":"https:\/\/doi.org\/10.3390\/sym16010131","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1,22]]}}}