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Towards fast and adaptive optimal control policies for robots: A direct policy search approach

Didier Marin 1, 2, * Olivier Sigaud 1, 2
* Corresponding author
2 AMAC
ISIR - Institut des Systèmes Intelligents et de Robotique
Abstract : Optimal control methods are generally too expensive to be applied on-line and in real-time to the control of robots. An alternative method consists in tuning a parametrized reactive controller so that it converges to optimal behavior. In this paper we present such a method based on the "direct Policy Search" paradigm to get a cost-efficient control policy for a simulated two degrees-of-freedom planar arm actuated by six muscles. We learn a parametric controller from demonstration using a few near-optimal trajectories. Then we tune the parameters of this controller using two versions of a Cross-Entropy Policy Search method that we compare. Finally, we show that the resulting controller is 20000 times faster than an optimal control method producing the same trajectories.
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Conference papers
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https://hal.sorbonne-universite.fr/hal-00703755
Contributor : Didier Marin <>
Submitted on : Monday, June 4, 2012 - 12:08:46 PM
Last modification on : Friday, March 19, 2021 - 3:32:54 AM

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  • HAL Id : hal-00703755, version 1

Citation

Didier Marin, Olivier Sigaud. Towards fast and adaptive optimal control policies for robots: A direct policy search approach. Robotica 2012, 2012, Guimaraes, Portugal. pp.21-26. ⟨hal-00703755⟩

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