Minimax Differential Dynamic Programming: An Application to Robust Biped Walking
Conference Paper, Proceedings of (NeurIPS) Neural Information Processing Systems, pp. 1563 - 1570, December, 2002
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 control 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 dynamic 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.
BibTeX
@conference{Morimoto-2002-16863,author = {Jun Morimoto and Chris Atkeson},
title = {Minimax Differential Dynamic Programming: An Application to Robust Biped Walking},
booktitle = {Proceedings of (NeurIPS) Neural Information Processing Systems},
year = {2002},
month = {December},
pages = {1563 - 1570},
}
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