Analysis Randon Causes Repeatability Errors Inducted by Friction at Joints in Industrial Robots

Document Type : Original Article


1 Department of Transport and Hydrocarbons Equipment, Hydrocarbons and Chemistry Faculty, University of M’hamed Bougara-Boumerdes (UMBB), Boumerdes, Algeria

2 Department of Mechanical and Production Engineering, Mechanical and Process Engineering Faculty, University of Science and Technology Houari Boumediene (USTHB), BP 32 El Alia 16111 Bab Ezzouar Alger, Algeria


The present study was carried out to investigate and analyze the positionning repeatability introduced by friction variations based on stochastic ellipsoids. A mixed friction model has been developed with improved properties compared to existing standard models. The contact is presented as a multitude of micro contacts whose nature can be of two types: lubricated and solid. This model is experimentally tested on a reciprocating tribometer under extreme friction conditions, with sliding speed varying from 0.1 to 3 m/s and load modified from 40N to 150N to discuss the effect of speed, the effect of nominal contact pressure and the effect of sliding distance on friction parameters. The results showed how this model can be represented as a sum of functions of the relevant states, which are linear and nonlinear in the friction parameters. Thus, these results were used to evaluate the covariance matrix in order to locate the different ranges of errors which have an impact on the repeatability of position.


Main Subjects

  1. Tang, G., Webb, P., Thrower, J.J.R. and Manufacturing, C.-I., "The development and evaluation of robot light skin: A novel robot signalling system to improve communication in industrial human–robot collaboration", Robotics and Computer-Integrated Manufacturing, Vol. 56, (2019), 85-94, doi: 10.1016/j.rcim.2018.08.005
  2. Khorashadizadeh, S. and Fateh, M.M.J.R., "Uncertainty estimation in robust tracking control of robot manipulators using the fourier series expansion", Vol. 35, No. 2, (2017), 310-336, doi: 10.1017/S026357471500051X
  3. Sangdani, M. and Tavakolpour-Saleh, A.J.I.J.o.E., "Parameters identification of an experimental vision-based target tracker robot using genetic algorithm", International Journal of Engineering, Transactions C: Aspects, Vol. 31, No. 3, (2018), 480-486, doi: 10.5829/ije.2018.31.03c.11
  4. Savkiv, V., Mykhailyshyn, R., Duchon, F. and Mikhalishin, M.J.J.o.E.E., "Energy efficiency analysis of the manipulation process by the industrial objects with the use of bernoulli gripping devices", Journal of Electrical Engineering, Vol. 68, No. 6, (2017), 496, doi: 10.1515/jee-2017-0087
  5. Mykhailyshyn, R., Savkiv, V., Mikhalishin, M. and Duchon, F., "Experimental research of the manipulatiom process by the objects using bernoulli gripping devices", in 2017 IEEE International Young Scientists Forum on Applied Physics and Engineering (YSF), IEEE. (2017), 8-11.
  6. Wan, W., Igawa, H., Harada, K., Onda, H., Nagata, K. and Yamanobe, N.J.A.R., "A regrasp planning component for object reorientation", Vol. 43, No. 5, (2019), 1101-1115, doi: 10.1007/s10514-018-9781-y
  7. Savkiv, V., Mykhailyshyn, R., Maruschak, P., Kyrylovych, V., Duchon, F. and Chovanec, Ľ.J.T., "Gripping devices of industrial robots for manipulating offset dish antenna billets and controlling their shape", Vol. 36, No. 1, (2021), 63-74, doi: 10.3846/transport.2021.14622
  8. Wermelinger, M., Johns, R., Gramazio, F., Kohler, M., Hutter, M.J.I.R. and Letters, A., "Grasping and object reorientation for autonomous construction of stone structures", IEEE Robotics and Automation Letters, Vol. 6, No. 3, (2021), 5105-5112, doi: 10.1109/LRA.2021.3070300
  9. Deblaise, D., "Contribution à la modélisation et à l'étalonnage élasto-géométriques des manipulateurs à structure parallèle", INSA de Rennes, (2006),
  10. Assoumou Nzue, R., Brethe, J.-F., Vasselin, E. And Lefebvre, D., "Comparaison de la répétabilité des robots manipulateurs sériels et parallèles à l'aide des ellipsoïdes stochastiques", in Congrès français de mécanique, AFM, Maison de la Mécanique, 39/41 rue Louis Blanc, 92400 Courbevoie, France, (2011).
  11. Kumičáková, D., Tlach, V. and Císar, M., "Testing the performance characteristics of manipulating industrial robots", International Organization for Standardization (2016).
  12. Al-Bender, F. and Swevers, J.J.I.C.S.M., "Characterization of friction force dynamics", IEEE Control Systems Magazine Vol. 28, No. 6, (2008), 64-81, doi: 10.1109/MCS.2008.929279
  13. Bona, B. and Indri, M., "Friction compensation in robotics: An overview", in Proceedings of the 44th IEEE Conference on Decision and Control, IEEE. (2005), 4360-4367.
  14. Venkata Vishnu. A and Sudhakar Babub. S, "Mathematical modeling and multi response optimization for improving machinability of alloy steel using rsm, grey relational analysis and jaya algorithm", International Journal of Engineering, Transactions C: Aspects, Vol. 34, No. 09, (2021), 1257-1266, doi: 10.5829/ije.2021.34.09C.13
  15. Belarifi, F., Blouet, J., Inglebert, G., Benamar, A.J.M. and Industry, "Confrontation d'un modèle théorique en lubrification mixte avec une étude expérimentale du comportement au frottement d'une denture d'engrenage droit", Vol. 7, No. 5-6, (2006), 527-536, doi: 10.1051/meca:2007010
  16. Zailani. Z-A, R.N.S.N. and Shuaiba. N-A, "Effect of cutting environment and swept angle selection in milling operation", International Journal of Engineering, Transactions B: Applications, Vol. 34, No. 11, (2021), 2578-2584, doi: 10.5829/ije.2021.34.12c.02
  17. Robbe-Valloire, F., Progri, R., Paffoni, B. and Gras, R., "Prediction of wear rate dispersion in mixed lubrication", in World Tribology Congress. Vol. 42010, (2005), 453-454.