Abstract
This paper proposes a new method for controlling robotic contact force based on an online environment stiffness admittance controller on curved and complex surfaces. A second-order system models the robot’s interaction with the environment, while a position-based admittance controller adjusts the reference force. A proposed method obtains the desired force by estimating the online environment stiffness based on the robot’s stiffness and combining the damped force. An exponential stability theorem was utilized to check the stability of this controller. The simulations were conducted to determine the efficiency of this method using different robot stiffnesses. Accurate positions were found at robot stiffnesses of (0.6) and (0.8) N/m and environment stiffnesses of (8500) and (9000) N/m for both surfaces at a force of 50 N. Moreover, polishing experiments were applied on the surfaces based on the simulation results. The contact force fluctuations did not exceed \( \pm 1.25 \) and \( \pm 1.3 \) N out of 10 N for both cases. Furthermore, roughness values were reduced from ranges of 40 to − 20 and 20 to − 20 \(\upmu \)m to ranges of 3.5 to − 3 and 5 to − 5.75 \(\upmu \)m for a vertical and horizontal line of the curved surface, respectively. Similarly, roughness values decreased from ranges of 180 to − 60 and 0 to − 66 \(\upmu \)m to ranges of 2.5 to − 3 and 3.75 to − 2.3 \(\upmu \)m for the vertical and horizontal lines for the complex surface, respectively. The approach was able to track desired force on these surfaces, which is quite challenge.
Similar content being viewed by others
Availability of Data and Materials
Not applicable.
Code Availability
Not applicable.
References
Realyvásquez-Vargas, A.; Arredondo-Soto, K.C.; García-Alcaraz, J.L.; Márquez-Lobato, B.Y.; Cruz-García, J.: Introduction and configuration of a collaborative robot in an assembly task as a means to decrease occupational risks and increase efficiency in a manufacturing company. Robot. Comput. Integr. Manuf. 57, 315–328 (2019). https://doi.org/10.1016/j.rcim.2018.12.015
Liu, H.; Wang, L.: Remote human–robot collaboration: a cyber-physical system application for hazard manufacturing environment. J. Manuf. Syst. 54, 24–34 (2020). https://doi.org/10.1016/j.jmsy.2019.11.001
Middleton, R.H.; Goodwin, G.C.; Longman, R.W.: A method for improving the dynamic accuracy of a robot performing a repetitive task. Int. J. Robot. Res. 8(5), 67–74 (1989). https://doi.org/10.1177/027836498900800506
Qiao, H.; Wang, M.; Su, J.; Jia, S.; Li, R.: The concept of attractive region in environment and its application in high-precision tasks with low-precision systems. IEEE/ASME Trans. Mechatron. 20(5), 2311–2327 (2014). https://doi.org/10.1109/TMECH.2014.2375638
Guan, W.; Chen, S.; Wen, S.; Tan, Z.; Song, H.; Hou, W.: High-accuracy robot indoor localization scheme based on robot operating system using visible light positioning. IEEE Photon. J. 12(2), 1–16 (2020). https://doi.org/10.1109/JPHOT.2020.2981485
Heyer, C.: Human–robot interaction and future industrial robotics applications. In: 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4749–4754. IEEE (2010). https://doi.org/10.1016/j.jmsy.2019.11.001
Ochoa, H.; Cortesão, R.: Impedance control architecture for robotic-assisted micro-drilling tasks. J. Manuf. Process. 67, 356–363 (2021). https://doi.org/10.1016/j.jmapro.2021.04.066
Xu, Z.; Li, S.; Zhou, X.; Cheng, T.: Dynamic neural networks based adaptive admittance control for redundant manipulators with model uncertainties. Neurocomputing 357, 271–281 (2019). https://doi.org/10.1016/j.neucom.2019.04.069
Han, B.; Zoppi, M.; Molfino, R.: Variable impedance actuation using biphasic media. Mech. Mach. Theory 62, 1–12 (2013). https://doi.org/10.1016/2012.11.001
Mohsin, I.; He, K.; Li, Z.; Du, R.: Path planning under force control in robotic polishing of the complex curved surfaces. Appl. Sci. 9(24), 5489 (2019). https://doi.org/10.3390/app9245489
Duan, J.; Gan, Y.; Chen, M.; Dai, X.: Adaptive variable impedance control for dynamic contact force tracking in uncertain environment. Robot. Auton. Syst. 102, 54–65 (2018). https://doi.org/10.1016/j.robot.2018.01.009
Hamedani, M.H.; Sadeghian, H.; Zekri, M.; Sheikholeslam, F.; Keshmiri, M.: Intelligent Impedance Control using Wavelet Neural Network for dynamic contact force tracking in unknown varying environments. Control. Eng. Pract. 113, 104840 (2021). https://doi.org/10.1016/j.robot.2018.01.009
Basu, B.; Nagarajaiah, S.; Chakraborty, A.: Online identification of linear time-varying stiffness of structural systems by wavelet analysis. Struct. Health Monit. 7(1), 21–36 (2008). https://doi.org/10.1177/1475921707081968
Jinjun, D.; Yahui, G.; Ming, C.; Xianzhong, D.: Symmetrical adaptive variable admittance control for position/force tracking of dual-arm cooperative manipulators with unknown trajectory deviations. Robot. Comput. Integr. Manuf. 57, 357–369 (2019). https://doi.org/10.1016/j.rcim.2018.12.012
Wahballa, H.; Duan, J.; Wang, W.; Dai, Z.: Experimental study of robotic polishing process for complex violin surface. Machines 11(2), 147 (2023). https://doi.org/10.3390/machines11020147
Li, Z.; Huang, H.; Song, X.; Xu, W.; Li, B.: A fuzzy adaptive admittance controller for force tracking in an uncertain contact environment. IET Control Theory Appl. 15(17), 2158–2170 (2021). https://doi.org/10.1049/cth2.12175
Jung, S.; Jeong, D.J.: Admittance force tracking control schemes for robot manipulators under uncertain environment and dynamics. Int. J. Control Autom. Syst. 19(11), 3753–3763 (2021). https://doi.org/10.1007/s12555-020-0959-7
Roveda, L.; Piga, D.: Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks. Auton. Robot. 45(3), 371–388 (2021). https://doi.org/10.1007/s10514-021-09970-z
Jung, S.: Admittance force tracking control for position-controlled robot manipulators under unknown environment. In: 2020 20th International Conference on Control, Automation and Systems (ICCAS), pp. 219–224. IEEE (2020). https://doi.org/10.23919/ICCAS50221.2020.9268417
Mao, D.; Yang, W.; Du, Z.: Fuzzy variable impedance control based on stiffness identification for human-robot cooperation. In: IOP Conference Series: Earth and Environmental Science, Vol. 69, No. 1, p. 012090. IOP Publishing (2017). https://doi.org/10.1088/1755-1315/69/1/012
Liu, C.; He, Y.; Chen, X.; Cao, H.: Adaptive enhanced admittance force-tracking controller design for highly dynamic interactive tasks. In: Industrial Robot: The International Journal of Robotics Research and Application (2022). https://doi.org/10.1108/IR-10-2021-0222
Cieślak, P.; Ridao, P.: . Adaptive admittance control in task-priority framework for contact force control in autonomous underwater floating manipulation. In: International Conference on Intelligent Robots and Systems (IROS), pp. 6646–6651 (2018). https://doi.org/10.1109/IROS.2018.8593542
Li, H.Y.; Paranawithana, I.; Yang, L.; Lim, T.S.K.; Foong, S.; Ng, F.C.; Tan, U.X.: Stable and compliant motion of physical human-robot interaction coupled with a moving environment using variable admittance and adaptive control. IEEE Robot. Autom. Lett. 3(3), 2493–2500 (2018). https://doi.org/10.1109/LRA.2018.2812916
Ramírez-Vera; V. I.; Mendoza-Gutiérrez; M. O.; Bonilla-Gutiérrez, I.: Impedance control with bounded actions for human–robot interaction. Arab. J. Sci. Eng. (2022). https://doi.org/10.1007/s13369-022-06638-3
Dimeas, F.; Aspragathos, N.: Fuzzy learning variable admittance control for human–robot cooperation. In: 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4770–4775. IEEE (2014). https://doi.org/10.1109/IROS.2014.6943240
Tufail, M.; Anwar, S.; Khan, Z.A.; Khan, M.T.: Real-time impedance control based on learned inverse dynamics. Arab. J. Sci. Eng. 45(7), 5043–5055 (2020). https://doi.org/10.1007/s13369-019-04334-3
Calanca, A.; Muradore, R.; Fiorini, P.: Impedance control of series elastic actuators: passivity and acceleration-based control. Mechatronics 47, 37–48 (2017). https://doi.org/10.1016/j.mechatronics.2017.08.010
Song, P.; Yu, Y.; Zhang, X.: A tutorial survey and comparison of impedance control on robotic manipulation. Robotica 37(5), 801–836 (2019). https://doi.org/10.1017/S0263574718001339
La Mura, F.; Todeschini, G.; Giberti, H.: High performance motion-planner architecture for hardware-in-the-loop system based on position-based-admittance-control. Robotics 7(1), 8 (2018). https://doi.org/10.3390/robotics7010008
Ahmed, A.; Yu, M.; Chen, F.: Inverse kinematic solution of 6-DOF robot-arm based on dual quaternions and axis invariant methods. Arab. J. Sci. Eng. (2022). https://doi.org/10.1007/s13369-022-06794-6
Afzal, A.; Ansari, Z.; Faizabadi, A.R.; Ramis, M.K.: Parallelization strategies for computational fluid dynamics software: state of the art review. Arch. Comput. Methods Eng. 24(2), 337–363 (2017). https://doi.org/10.1007/s11831-016-9165-4
Afzal, A.; Ansari, Z.; Ramis, M.K.: Parallelization of numerical conjugate heat transfer analysis in parallel plate channel using OpenMP. Arab. J. Sci. Eng. 45(11), 8981–8997 (2020). https://doi.org/10.1007/s13369-020-04640-1
Zhou, H.; Ma, S.; Wang, G.; Deng, Y.; Liu, Z.: A hybrid control strategy for grinding and polishing robot based on adaptive impedance control. Adv. Mech. Eng. (2021) https://doi.org/10.1177/16878140211004034
Shen, Y.; Lu, Y.; Zhuang, C.: A fuzzy-based impedance control for force tracking in unknown environment. J. Mech. Sci. Technol. 36(6), 5231–5242 (2022). https://doi.org/10.1007/s12206-022-0936-6
Saleh, B.; Sundar, S.; Aly, A.A.; Ramana, E.V.; Sharma, K.V.; Afzal, A.; Abdelrhman, Y.; Sousa, A.C.M.: A fuzzy-based impedance control for force tracking in unknown environment. J. Mech. Sci. Technol. 36(6), 5231–5242 (2022). https://doi.org/10.1007/s12206-022-0936-6
Acknowledgements
The authors thank a teamwork of Bionic Engineering at the School of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics.
Funding
This work was supported by the National Natural Science Foundation of China under project No. (62233008) and No. (52205017).
Author information
Authors and Affiliations
Contributions
The below lists are the authors’ contributions to this paper: conceptualizing and modeling, H.W.; simulations and experiments, H.W. and J.D.; analysis and evaluation, H.W.; writing and preparation, Z.D.; revising manuscript, supervision, Z.D. All authors have read and agreed to publish this manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declared there are no any potential conflicts of interest.
Ethics Approval
Not applicable.
Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Wahballa, H., Duan, J. & Dai, Z. Controlling Robotic Contact Force on Curved and Complex Surfaces Based on an Online Identification Admittance Controller. Arab J Sci Eng 49, 1625–1641 (2024). https://doi.org/10.1007/s13369-023-07826-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13369-023-07826-5