Graphics enhanced version of this site

Acquisition of a Biped Walking Pattern Using an Approximate Poincare Map
J. Morimoto, J. Nakanishi, G. Endo, G. Cheng, C. Atkeson, and G. Zeglin
Proceedings of the IEEE-RAS/RSJ Int. Conf. on Humanoid Robots (Humanoids 2004), November, 2004, pp. 912 - 924.

Jump to: Download | Abstract | Notes | Text Reference | BibTeX Reference

Adobe portable document format (pdf) [1034 KB]

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

We propose a model-based reinforcement learning algorithm for biped walking in which the robot learns to appropriately place the swing leg. This decision is based on a learned model of the Poincare map of the periodic walking pattern. The model maps from a state at a single support phase and foot placement to a state at the next single support phase. We applied this approach to both a simulated robot model and an actual biped robot. We show that successful walking patterns are acquired.

Associated project: Dynamic Biped

Number of pages: 13

J. Morimoto, J. Nakanishi, G. Endo, G. Cheng, C. Atkeson, and G. Zeglin, "Acquisition of a Biped Walking Pattern Using an Approximate Poincare Map," Proceedings of the IEEE-RAS/RSJ Int. Conf. on Humanoid Robots (Humanoids 2004), November, 2004, pp. 912 - 924.

@inproceedings{Morimoto_2004_5594,
   author = "Jun Morimoto and Jun Nakanishi and Gen Endo and Gordon Cheng and Chris Atkeson and Garth Zeglin",
   title = "Acquisition of a Biped Walking Pattern Using an Approximate Poincare Map",
   booktitle = "Proceedings of the IEEE-RAS/RSJ Int. Conf. on Humanoid Robots (Humanoids 2004)",
   month = "November",
   year = "2004",
   pages = "912 - 924"
}