Abstract
To achieve accurate dynamic model identification of the hyper-redundant manipulator, a novel identification method based on whale optimization algorithm is proposed. Firstly, the dynamic model of the hyper-redundant manipulator and the base parameter set are introduced, and a joint nonlinear friction model is established. The excitation trajectory is generated using genetic algorithm to optimize the condition number of the regression matrix. Secondly, physical feasibility constraints of the manipulator dynamic model are established, and the whale optimization algorithm (WOA) is applied for dynamic parameter identification under nonlinear constraints. Finally, experiments are conducted to verify the effectiveness of the identification method. The experimental results demonstrate that, compared with the traditional least squares (LS) algorithm and weighted least squares (WLS) algorithm, the proposed identification algorithm can improve the sum of identify torque residual root mean square (RMS) of joints by 11.51 \({\text{N}}{\cdot }{\text{m}}\) and 6.29 \({\text{N}}{\cdot }{\text{m}}\), respectively. The experimental results demonstrate the superiority of the algorithm proposed in this paper.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Xiao, B., Yin, S.: Exponential tracking control of robotic manipulators with uncertain dynamics and kinematics. IEEE Trans. Industr. Inf. 15(2), 689–698 (2019). https://doi.org/10.1109/TII.2018.2809514
Li, Y., Li, Y., Zhu, M., Zhenbang, X., Deqiang, M.: A nonlinear momentum observer for sensorless robot collision detection under model uncertainties. Mechatronics 78, 102603 (2021). https://doi.org/10.1016/j.mechatronics.2021.102603
Han, Y., Wu, J., Liu, C., et al.: An iterative approach for accurate dynamic model identification of industrial robots. IEEE Trans. Rob. 99, 1–18 (2020)
Dehio, N., Smith, J., Wigand, D.L., et al.: Enabling impedance-based physical human–multi–robot collaboration: experiments with four torque-controlled manipulators. Int. J. Robot. Res. 41(1), 68–84 (2022)
Khalil, W., Bennis, F.: Direct calculation of minimum set of inertial parameters of serial robots. IEEE Trans. Robot. Autom. 6(1), 368–373 (1994)
Dong, J., Jianming, Xu., Zhou, Q., Zhu, J., Li, Yu.: Dynamic Identification of Industrial robot based on nonlinear friction model and LS-SOS algorithm. IEEE Trans. Instrum. Meas. 70, 1–12 (2021). https://doi.org/10.1109/TIM.2021.3124039
Presse, C., Gautier, M.: New criteria of exciting trajectories for robot identification. Int. Conf. Robot. Autom. 3, 907–912 (1993)
Galafiore, G., Indri, M., Bona, B.: Robot dynamic calibration: Optimal excitation trajectories and experimental parameter estimation. J. Robot. Syst. 18(2), 55–68 (2001)
Gautier, M., Bonnet, V.: Optimal Exciting Dance for Identifying Inertial Parameters of an Anthropomorphic Structure. IEEE Trans. Robot. (2016)
Jin, J., Gans, N.: Parameter identification for industrial robots with a fast and robust trajectory design approach. Robot. Comput. Integr. Manuf. 31(1), 21–29 (2015)
Swevers, J., Ganseman, C., Tukel, D.B.: Optimal robot excitation and identification. IEEE Trans. Robot. Autom. 13, 730–740 (1997)
Atkeson, C.G., An, C.H., Hollerbach, J.M.: Estimation of Inertial parameters of manipulator loads and links. Int. J. Robot. Res. 5(3), 101–119 (1986)
Wu, W., Zhu, S., Wang, X., et al.: Closed-loop dynamic parameter identification of robot manipulators using modified fourier series. Int. J. Adv. Rob. Syst. 9(1), 1 (2012)
Gautier, M.: Dynamic identification of robots with power model. Int. Conf. Robot. Autom. 3, 1922–1927 (1997)
Lee, T., Park, F.C.: A geometric algorithm for robust multibody inertial parameter identification. IEEE Robot. Autom. Lett., 1 (2018)
Lee, T., Wensing, P.M., Park, F.C.: Geometric robot dynamic identification: a convex programming approach. IEEE Trans. Rob. 36(2), 348–365 (2020)
Mirjalili, S., Lewis, A., et al.: The Whale Optimization Algorithm. Adv. Eng. Softw. 95, 51–67 (2016)
Sousa, C.D., Cortesao, R.: Physical feasibility of robot base inertial parameter identification: a linear matrix inequality approach. Int. J. Robot. Res. 33(6), 931–944 (2014)
Acknowledgements
This research was supported by the National Natural Science Foundation of China (Grant No. 62173047).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Zhou, Y., Li, Z., Feng, A., Zhang, X., Zhu, M. (2023). A Novel Hyper-Redundant Manipulator Dynamic Identification Method Based on Whale Optimization and Nonlinear Friction Model. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14267. Springer, Singapore. https://doi.org/10.1007/978-981-99-6483-3_8
Download citation
DOI: https://doi.org/10.1007/978-981-99-6483-3_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-6482-6
Online ISBN: 978-981-99-6483-3
eBook Packages: Computer ScienceComputer Science (R0)