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Carnegie Mellon Robotics Institute

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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.

Notes

Associated Project(s): Dynamic Biped

Number of pages: 8

Text Reference

Jun Morimoto and Chris Atkeson, "Minimax Differential Dynamic Programming: An Application to Robust Biped Walking," Neural Information Processing Systems 2002, 2002.

BibTeX Reference

@inproceedings{Morimoto_2002_5597,
   author = "Jun Morimoto and Chris Atkeson",
   title = "Minimax Differential Dynamic Programming: An Application to Robust Biped Walking",
   booktitle = "Neural Information Processing Systems 2002",
   year = "2002",
}

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