Abstract
Dynamic walking fulfill agility and stability simultaneously is one of the most difficulty for biped robot control. The traditional zero moment point (ZMP) is the most commonly used reference point for biped robot static and quasi dynamic walking control. However, human walking experimental results indicate that during walking process of human beings, the ZMP trajectory is not always conformed to the requirement of stability, such as giant strides, acceleration walking or fast walking. In order to reveal the mechanism of the biped dynamic walking, this paper proposed a novel stability criterion for the biped walking by tuning the conventional fixed support polygon area to an adjustable one. This method includes the tiptoe underactuated phase of the support foot during the biped walking. A new algorithm for the real-time biped walking generation by combining central pattern generation (CPG) with foot rotation indicator (FRI) is presented. The FRI monitor establishes the mapping function between the center of mass of the biped robot with the boundary of the elastic support polygon. By introducing FRI information, the CPG parameters can be adjusted in real time to generate a rhythmic and stable walking pattern. Numerical simulation results show that the proposed algorithm extends the application area of the ZMP criterion and improves the walking velocity of the biped robot. Moreover, the algorithm builds a bridge for the dynamic biped walking from the robot agility to motor parameters. This means that the agility of the biped robot can be quantitative controlled by modulating the motor parameters.
Similar content being viewed by others
References
Aoi, S., & Tsuchiya, K. (2011). Generation of bipedal walking through interactions among the robot dynamics, the oscillator dynamics, and the environment: Stability characteristics of a five-link planar biped robot. Autonomous Robots, 30(2), 123–141.
Farzaneh, Y., Akbarzadeh, A., & Akbari, A. A. (2014). Online bio-inspired trajectory generation of seven-link biped robot based on t–s fuzzy system. Applied Soft Computing, 14, 167–180.
Ferreira, J. P., Crisostomo, M., & Coimbra, A. P. (2012). SVR controller for a biped robot in the sagittal plane with human-based ZMP trajectory reference and gait. International Journal of Humanoid Robotics, 9(03), 1250018.
Fu, C., & Chen, K. (2006). Research progress on stability and control strategy for biped robots. Chinese High Technology Letters, 16(3), 319–324.
Goswami, A. (1999). Postural stability of biped robots and the foot-rotation indicator (FRI) point. The International Journal of Robotics Research, 18(6), 523–533.
He, B., Wang, Z., Shen, R., & Hu, S. (2014). Real-time walking pattern generation for a biped robot with hybrid CPG–ZMP algorithm. International Journal of Advanced Robotic Systems, 11(10), 160.
Hopfield, J. J. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences, 79(8), 2554–2558.
Huang, Q., & Nakamura, Y. (2005). Sensory reflex control for humanoid walking. IEEE Transactions on Robotics, 21(5), 977–984.
Huang, Q., Yokoi, K., Kajita, S., Kaneko, K., Arai, H., Koyachi, N., et al. (2001). Planning walking patterns for a biped robot. IEEE Transactions on Robotics and Automation, 17(3), 280–289.
Kajita, S., Hirukawa, H., Harada, K., & Yokoi, K. (2014). Introduction to humanoid robotics. Berlin: Springer.
Li, Z., Zhou, C., Zhu, Q., & Xiong, R. (2017). Humanoid balancing behavior featured by underactuated foot motion. IEEE Transactions on Robotics, 33(2), 298–312.
Matsuoka, K. (1985). Sustained oscillations generated by mutually inhibiting neurons with adaptation. Biological Cybernetics, 52(6), 367–376.
Miyake, Y. (2009). Interpersonal synchronization of body motion and the Walk-Mate walking support robot. IEEE Transactions on Robotics, 25(3), 638–644.
Nakamura, Y., Mori, T., Sato, M.-A., & Ishii, S. (2007). Reinforcement learning for a biped robot based on a CPG—Actor—Critic method. Neural Networks, 20(6), 723–735.
Nassour, J., Hénaff, P., Ouezdou, F. B., Cheng, G. (2010). A study of adaptive locomotive behaviors of a biped robot: Patterns generation and classification. In International conference on simulation of adaptive behavior, pp. 313–324.
Or, J. (2010). A hybrid CPG–ZMP control system for stable walking of a simulated flexible spine humanoid robot. Neural Networks, 23(3), 452–460.
Or, J., & Takanishi, A. (2004). A biologically inspired CPG–ZMP control system for the real-time balance of a single-legged belly dancing robot. IEEE/RSJ International Conference on Intelligent Robots and Systems, 1, 931–936.
Park, H.-W., Ramezani, A., & Grizzle, J. (2013). A finite-state machine for accommodating unexpected large ground-height variations in bipedal robot walking. IEEE Transactions on Robotics, 29(2), 331–345.
Perrin, N., Stasse, O., Baudouin, L., Lamiraux, F., & Yoshida, E. (2012). Fast humanoid robot collision-free footstep planning using swept volume approximations. IEEE Transactions on Robotics, 28(2), 427–439.
Popovic, M. B., Goswami, A., & Herr, H. (2005). Ground reference points in legged locomotion: Definitions, biological trajectories and control implications. The International Journal of Robotics Research, 24(12), 1013–1032.
Taga, G. (1995a). A model of the neuro-musculo-skeletal system for human locomotion. I. Emergence of basic gait. Biological Cybernetics, 73(2), 97–111.
Taga, G. (1995b). A model of the neuro-musculo-skeletal system for human locomotion II. Real-time adaptability under various constraints. Biological Cybernetics, 2(73), 113–121.
Vukobratović, M., & Borovac, B. (2004). Zero-moment point thirty five years of its life. International Journal of Humanoid Robotics, 1(01), 157–173.
Vukobratovic, M., Frank, A., & Juricic, D. (1970). On the stability of biped locomotion. IEEE Transactions on Biomedical Engineering, 1, 25–36.
Wang, L., Liu, Z., Chen, C. P., Zhang, Y., Lee, S., & Chen, X. (2013). Fuzzy SVM learning control system considering time properties of biped walking samples. Engineering Applications of Artificial Intelligence, 26(2), 757–765.
Wang, T., Guo, W., Li, M., Zha, F., & Sun, L. (2012). CPG control for biped hopping robot in unpredictable environment. Journal of Bionic Engineering, 9(1), 29–38.
Wang, Z., He, B., Zhou, Y., Yuan, T., Xu, S., & Shao, M. (2018). An experimental analysis of stability in human walking. Journal of Bionic Engineering, 15(5), 827–838.
Westervelt, E. R., Chevallereau, C., Choi, J. H., Morris, B., & Grizzle, J. W. (2007). Feedback control of dynamic bipedal robot locomotion. Boca Raton: CRC Press.
Acknowledgements
The work was supported by National Natural Science Foundation of China (Grant Nos. 51605334, U1713215, and 51705368), and Shanghai Municipal Science and Technology Commission Project (Grant No. 17DZ1203405). We thank the reviewers and editors for their helpful comments on the manuscript.
Author information
Authors and Affiliations
Corresponding authors
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
He, B., Si, Y., Wang, Z. et al. Hybrid CPG–FRI dynamic walking algorithm balancing agility and stability control of biped robot. Auton Robot 43, 1855–1865 (2019). https://doi.org/10.1007/s10514-019-09839-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10514-019-09839-2