Minimax Differential Dynamic Programming: An Application to Robust Biped Walking
Abstract
We developed a robust control policy design method in high-dimensional state space by using differential dynamic programming with a minimax criterion. As an example, we applied our method to a simulated five link biped robot. The results show lower joint torques from the optimal con- trol policy compared to a hand-tuned PD servo controller. Results also show that the simulated biped robot can successfully walk with unknown disturbances that cause controllers generated by standard differential dy- namic programming and the hand-tuned PD servo to fail. Learning to compensate for modeling error and previously unknown disturbances in conjunction with robust control design is also demonstrated.
Cite
Text
Morimoto and Atkeson. "Minimax Differential Dynamic Programming: An Application to Robust Biped Walking." Neural Information Processing Systems, 2002.Markdown
[Morimoto and Atkeson. "Minimax Differential Dynamic Programming: An Application to Robust Biped Walking." Neural Information Processing Systems, 2002.](https://mlanthology.org/neurips/2002/morimoto2002neurips-minimax/)BibTeX
@inproceedings{morimoto2002neurips-minimax,
title = {{Minimax Differential Dynamic Programming: An Application to Robust Biped Walking}},
author = {Morimoto, Jun and Atkeson, Christopher G.},
booktitle = {Neural Information Processing Systems},
year = {2002},
pages = {1563-1570},
url = {https://mlanthology.org/neurips/2002/morimoto2002neurips-minimax/}
}