The Robotics Institute

Carnegie Mellon Robotics Institute

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Abstract

We have developed a robust control policy design method for high-dimensional state spaces 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 using the optimal control policy compared to torques generated by 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. We applied the proposed method to a real biped robot to optimize swing leg trajectories.

Notes

Associated Project(s): Dynamic Biped

Number of pages: 6

Text Reference

Jun Morimoto, Garth Zeglin, and Chris Atkeson, "Minimax Differential Dynamic Programming: Application to a Biped Walking Robot," Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2003.

BibTeX Reference

@inproceedings{Morimoto_2003_5596,
   author = "Jun Morimoto and Garth Zeglin and Chris Atkeson",
   title = "Minimax Differential Dynamic Programming: Application to a Biped Walking Robot",
   booktitle = "Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems",
   year = "2003",
}

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