Skip to main content

Advertisement

Log in

Trajectory Generation Using GA for an 8 DOF Biped Robot with Deformation at the Sole of the Foot

  • Published:
Journal of Intelligent and Robotic Systems Aims and scope Submit manuscript

Abstract

In biped robot dynamics, the foot is generally considered rigid. However, in practical cases, there will be a layer of rubber on the sole to act as a shock absorber. Such electrodynamic contact has been studied in the case of industrial robots, but the experience with biped robots is rare. The goal of this paper is to device a trajectory generation method using a genetic algorithm (GA) for an 8 DOF robot that can walk on flat terrain and climb stairs with deformation at the sole. The proposed method uses splines to model each joint angle and needs a single GA layer, which makes it faster and simpler than earlier models. The method incorporates the dynamics of an actual 8 DOF robot to find the most energy optimal gait. A simple control method is proposed that corrects the computed angle required to follow ZMP incorporating the deformation of the sole. Using the control method the computed angle is first corrected and then the trajectory optimized. Energy consumed in three cases were compared: walk on flat ground with no sole deformation, walk with uncorrected deformed soft sole and walk with deformed soft sole with correction of deformation. It is found that the least energy was consumed in the case of soft sole with correction for deformation. This proves the need for deformation correction of soft sole and the usefulness of our proposed method.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Vukobratovic, M., Potkonjak, V., Matijevic, V.: Dynamics of Robots with Contact Tasks, pp. 211–217. Kluwer, Boston, MA (2003)

    Google Scholar 

  2. Ono, K., Liu, R.: Optimal biped walking locomotion solved by trajectory planning method. Trans. Am. Soc. Mech. Eng. 124(December), 554–565 (2002)

    Google Scholar 

  3. Shih, C.-L.: Inverted pendulum-like walking pattern of a 5-link biped robot. In: ICAR ’97 Proceedings of 8th International Conference on Advanced Robotics, pp. 83–88, 7–9 July 1997

  4. Nagasaka, K., Inoue, H., Inaba, M.: Dynamic walking patter generation for a humanoid robot based on optimal gradient method. IEEE Proc. Int. Conf. Cybern. Soc. 6, 908–913 (1999)

    Google Scholar 

  5. Arakawa, T., Fukuda, T.: Natural motion generation of biped locomotion robot using hierarchical trajectory generation method consisting of GA, EP layers. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 211–216, Albuquerque, April 1997

  6. Hasegawa, Y., Arakawa, T., Fukuda, T.: Trajectory generation for biped locomotion robot. Mechatronics 10, 67–89 (2000)

    Article  Google Scholar 

  7. Capi, G., Nasu, Y., Baroll, L., Mitobe, K., Takeda, K.: Application of genetic algorithms for biped robot gait synthesis optimization during walking and going up stairs. Adv. Robot. 15(6), 675–694 (2001)

    Article  Google Scholar 

  8. Vukobratovic, M., et al.: On the stability of biped locomotion. IEEE Trans. Biomed. Eng., BME 17(1), 25–26 (1970)

    Google Scholar 

  9. Takanishi, A., Ishida, M., Yamazaki, Y., Kato, I.: The realization of dynamic walking robot WL-10RD. In: Proceeding of International Conference on Advanced Robotics, pp. 459–466 (1985)

  10. Shih, C.L., Li, Y.Z., Churng, S., Lee, T.T., Cruver, W.A.: Trajectory synthesis and physical admissibility for a biped robot during the single support phase. In: Proceeding of IEEE International Conference on Robotics and Automation, pp. 1646–1652 (1990)

  11. Shih, C.: Gait synthesis for a biped robot. Robotica 15, 599–607 (1997)

    Article  Google Scholar 

  12. Shih, C.L., Li, Y.Z., Churng, S., Lee, T.T., Cruver, W.A.: Trajectory synthesis and physical admissibility for a biped robot during the single support phase. In: Proceeding of IEEE International Conference on Robotics and Automation, pp. 1646–1652 (1990)

  13. Dasgupta, A., Nakamura, Y.: Making feasible walking motion of humanoid robots from human motion capture data. In: Proceeding of IEEE International Conference on Robotics and Automation, pp. 1044–1049 (1999)

  14. Shih, C.: Ascending and descending stairs for a biped robot. IEEE Trans. Syst. Man Cybern. A 29(3) (1999)

  15. Huang, Q.: Planning walking patterns for a biped robot. IEEE Trans. Robot. Autom. 17(3) (2001)

  16. Boeing, A, Braunl, T.: Evolving splines: an alternative locomotion controller for a bipedal robot. In: Seventh International Conference on Control, Automation, Robotics and Vision (ICARCV’OZ), Singapore, December 2002

  17. Silva, F.M., et al.: Dynamic performance of biped locomotion systems. In: Proceedings of the AMC 98 (5th Workshop on Advanced Motion Control), Combra

  18. Peng, Z., Huang, Q., Zhao, X., Xiao, T., Li, K.: Online trajectory generation based on of-line trajectory for biped humanoid. In: Proceedings of the IEEE International Conference on Robotics and Biomimetics, pp.752–756 (2004)

  19. Capi, G., Kaneko, S., Mitobe, K., Barolli, L., Nasu, Y.: Optimal trajectory generation for a prismatic jointed biped robot using GA. Robot. Auton. Syst. 38, 119–128 (2002)

    Article  MATH  Google Scholar 

  20. Capi, G., Nasu, Y., Barolli, L., Mitobe, K.: Real time gait generation for autonomous humanied robots: a case study for walking. Robot. Auton. Syst. 42, 107–116 (2003)

    Article  MATH  Google Scholar 

  21. Mitobe, K., Capi, G., Nasu, Y.: A new control method for walking robots based on angular momentum. Mechatronics 14, 163–174 (2004)

    Article  Google Scholar 

  22. Salatian, A.W., Yi, K.Y., Zheng, Y.F.: Reinforcement learning for biped robot to climb sloping surfaces. J. Robot. Syst. 14(4), 283–296 (1998)

    Article  Google Scholar 

  23. Kulkarni, P., Goswami, D., Guha, P., Dutta, A.: Path planning for a statically stable biped robot using PRM and reinforcement learning. J. Intell. Robot. Syst. 47, 197–214 (2006)

    Article  Google Scholar 

  24. Gordy, M.B.: GA.M: a matlab routine for function maximization using a genetic algorithm. Matlab codes GA, revised 12 Feb (1996)

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ashish Dutta.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Shrivastava, M., Dutta, A. & Saxena, A. Trajectory Generation Using GA for an 8 DOF Biped Robot with Deformation at the Sole of the Foot. J Intell Robot Syst 49, 67–84 (2007). https://doi.org/10.1007/s10846-007-9129-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-007-9129-x

Key words

Navigation