Abstract
Upright balance control is the most fundamental, yet essential, function of a humanoid robot to enable the performance of various tasks that are traditionally performed by human being in various unstructured environments. Such control schemes were conventionally implemented by developing accurate physical and kinematic models based on fixed torque-ankle states, which often lack robustness to external disturbing forces. This paper presents a variable impedance control method that generates the desired torques for stable humanoid robot upright balance control, to address this limitation. The robustness of the proposed method was brought by a variable parameter approach with the support of the impedance model. The variable parameter of the ankle angle is able to describe the balance state of a humanoid robot, and the proper adjustment of such parameter ensures the effectiveness of the control model. The proposed approach was applied to a humanoid robot on a moving vehicle, and the experimental results demonstrated its efficacy and robustness.
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References
Mende, M., Scott, M.L., Van Doorn, J., Grewal, D., Shanks, I.: Service robots rising: how humanoid robots influence service experiences and elicit compensatory consumer responses. J. Mark. Res. 56(4), 535–556 (2019)
Rajasekaran, V., Aranda, J., Casals, A., Pons, J.L.: An adaptive control strategy for postural stability using a wearable robot. Robot. Auton. Syst. 16–23 (2015)
Yin, K., et al.: Artificial human balance control by calf muscle activation modelling. IEEE Access 8, 86732–86744 (2020)
Tokur, D., Grimmer, M., Seyfarth, A.: Review of balance recovery in response to external perturbations during daily activities. Hum. Mov. Sci. 69, 102546 (2020)
Vukobratovic, M., Frank, A.A., Juricic, D.: On the stability of biped locomotion. IEEE Trans. Biomed. Eng. BME-17(1), 25–36 (1970)
Al-Shuka, H.F., Corves, B., Zhu, W.-H., Vanderborght, B.: Multi-level control of zero-moment point-based humanoid biped robots: a review. Robotica 34(11), 2440–2446 (2016)
Shin, H.K., Kim, B.K.: Energy-efficient reference walking trajectory generation using allowable ZMP (Zero Moment Point) region for biped robots. J. Inst. Control 17(10), 1029–1036 (2011)
Azad, M., Featherstone, R.: Angular momentum based balance controller for an under-actuated planar robot. Auton. Robot. 40(1), 93–107 (2015). https://doi.org/10.1007/s10514-015-9446-z
Lee, S.H., Goswami, A.: A momentum-based balance controller for humanoid robots on non-level and non-stationary ground. Auton. Robot. 33(4), 399–414 (2012). https://doi.org/10.1007/s10514-012-9294-z
Liu, C., Ning, J., Chen, Q.: Dynamic walking control of humanoid robots combining linear inverted pendulum mode with parameter optimization. Int. J. Adv. Robot. Syst. 15(1), 1729881417749672 (2018)
Hinata, R., Nenchev, D.N.: Balance stabilization with angular momentum damping derived from the reaction null-space. In: 2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) (2018)
Yang, C., Jiang, Y., Na, J., Li, Z., Cheng, L.: Finite-time convergence adaptive fuzzy control for dual-arm robot with unknown kinematics and dynamics. IEEE Trans. Fuzzy Syst. 27(3), 574–588 (2018)
Fang, W., Chao, F., Lin, M.C., Yang, L., Shang, C., Zhou, C.: An improved fuzzy brain emotional learning model network controller for humanoid robots. Front. Neurorobotics, 13(2) (2019)
Yin, K., Xiang, K., Pang, M., Chen, J., Yang, L.: Personalised control of robotic ankle exoskeleton through experience-based adaptive fuzzy inference. IEEE Access 7, 72221–72233 (2019)
Mattioli, T., Vendittelli, M.: Interaction force reconstruction for humanoid robots. IEEE Robot. Autom. Lett. 2(1), 282–289 (2016)
Neville, H.: Impedance control: an approach to manipulation: part i-theory. J. Dyn. Syst. Meas. Control, 107 (1985)
Song, P., Yu, Y., Zhang, X.: A tutorial survey and comparison of impedance control on robotic manipulation. Robotica 37(5), 801–836 (2019)
Pang, M., Li, M., Xiang, K., Ge, Y.: Human ankle joint reflex and impedance control during upright stance balance. Huazhong Univ. Sci. Technol. (Nat. Sci. Ed.) 45(10), 49–53 (2017)
Li, Z., Huang, Z., He, W., Su, C.-Y.: Adaptive impedance control for an upper limb robotic exoskeleton using biological signals. IEEE Trans. Industr. Electron. 64(2), 1664–1674 (2016)
Li, Y., Li, M., Pang, M., Wang, J., Tong, J., Dong, E.: Analysis of dynamics properties of ankle joint during push-forward disturbance rejection. In: 2016 IEEE International Conference on Information and Automation (ICIA). IEEE, pp. 712–717 (2016)
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Yin, K., Xue, Y., Wang, Y., Yang, L. (2022). Ankle Variable Impedance Control for Humanoid Robot Upright Balance Control. In: Jansen, T., Jensen, R., Mac Parthaláin, N., Lin, CM. (eds) Advances in Computational Intelligence Systems. UKCI 2021. Advances in Intelligent Systems and Computing, vol 1409. Springer, Cham. https://doi.org/10.1007/978-3-030-87094-2_18
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DOI: https://doi.org/10.1007/978-3-030-87094-2_18
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