Choi Y., You B. J. & Oh S. R.2004. On the stability of indirect ZMP controller for biped robot systems. In Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2, 1966–1971.

Endo G., Morimoto J., Matsubara T., Nakanishi J. & Cheng G.2008. Learning CPG-based biped locomotion with a policy gradient method: application to a humanoid robot.The International Journal of Robotics Research27(2),213–228.

Erbatur K. & Kurt O.2009. Natural ZMP trajectories for biped robot reference generation. IEEE Transactions on Industrial Electronics56(3),835–845.

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 Computing14,167–180.

Ferreira J. P., Crisóstomo M. & Coimbra A. P.2011. Sagittal stability PD controllers for a biped robot using a neurofuzzy network and an SVR.Robotica29(5),717–731.

Hu L., Zhou C. & Sun Z.2008. Estimating biped gait using spline-based probability distribution function with Q-learning.IEEE Transactions on Industrial Electronics55(3),1444–1452.

Kajita S., Kanehiro F., Kaneko K., Yokoi K. & Hirukawa H.2001. The 3D linear inverted pendulum mode: a simple modeling for a biped walking pattern generation. In Proceedings of 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems,1, 239–246.

Kajita S., Morisawa M., Harada K., Kaneko K., Kanehiro F., Fujiwara K. & Hirukawa H.2006. Biped walking pattern generator allowing auxiliary ZMP control. In Proceedings of 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2993–2999.

Kajita S., Nagasaki T., Kaneko K. & Hirukawa H.2007. ZMP-based biped running control. IEEE Robotics & Automation Magazine2(14),63–72.

Kim D., Seo S. J. & Park G. T.2005. Zero-moment point trajectory modelling of a biped walking robot using an adaptive neuro-fuzzy system.IEE Proceedings – Control Theory and Applications152(4),411–426.

Li T. H. S., Kuo P. H., Ho Y. F., Kao M. C. & Tai L. H.2015. A biped gait learning algorithm for humanoid robots based on environmental impact assessed artificial bee colony. IEEE Access3, 13–26.

Li T. H. S., Su Y. T., Lai S. W. & Hu J. J.2011. Walking motion generation, synthesis, and control for biped robot by using PGRL, LPI, and fuzzy logic.IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)41(3),736–748.

Liu C., Wang D. & Chen Q.2013. Central pattern generator inspired control for adaptive walking of biped robots. IEEE Transactions on Systems, Man, and Cybernetics: Systems43(5),1206–1215.

Michel O.2004. WebotsTM: professional mobile robot simulation. International Journal of Advanced Robotic Systems1(1),39–42.

Nassour J., Hugel V., Ouezdou F. B. & Cheng G.2013. Qualitative adaptive reward learning with success failure maps: applied to humanoid robot walking.IEEE Transactions on Neural Networks and Learning Systems24(1),81–93.

Park K.-H., Jo J. & Kim J.-H.2004. Stabilization of biped robot based on two mode Q-learning. InProceedings of the 2nd International Conference on Autonomous Robots and Agents, 446–451.

Shin H. K. & Kim B. K.2014. Energy-efficient gait planning and control for biped robots utilizing the allowable ZMP region.IEEE Transactions on Robotics30(4),986–993.

Su Y. T., Chong K. Y. & Li T. H. S.2011. Design and implementation of fuzzy policy gradient gait learning method for walking pattern generation of humanoid robots. International Journal of Fuzzy Systems13(4),369–382.

Taskiran E., Yilmaz M., Koca O., Seven U. & Erbatur K.2010. Trajectory generation with natural ZMP references for the biped walking robot SURALP. In Proceedings of 2010 IEEE International Conference on Robotics and Automation (ICRA), 4237–4242.

Tedrake R., Zhang T. W. & Seung H. S.2004. Stochastic policy gradient reinforcement learning on a simple 3D biped. In Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 3, 2849–2854.

Vukobratović M. & Stepanenko J.1972. On the stability of anthropomorphic systems. Mathematical Biosciences15(1),1–37.