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arXiv · 1905.06144

Feedback MPC for Torque-Controlled Legged Robots

Ruben Grandia·Farbod Farshidian·René Ranftl·Marco Hutter
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Abstract

The computational power of mobile robots is currently insufficient to achieve torque level whole-body Model Predictive Control (MPC) at the update rates required for complex dynamic systems such as legged robots. This problem is commonly circumvented by using a fast tracking controller to compensate for model errors between updates. In this work, we show that the feedback policy from a Differential Dynamic Programming (DDP) based MPC algorithm is a viable alternative to bridge the gap between the low MPC update rate and the actuation command rate. We propose to augment the DDP approach with a relaxed barrier function to address inequality constraints arising from the friction cone. A frequency-dependent cost function is used to reduce the sensitivity to high-frequency model errors and actuator bandwidth limits. We demonstrate that our approach can find stable locomotion policies for the torque-controlled quadruped, ANYmal, both in simulation and on hardware.

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Ruben Grandia, Farbod Farshidian, René Ranftl, Marco Hutter. 2019-08-09. Feedback MPC for Torque-Controlled Legged Robots. https://arxiv.org/abs/1905.06144

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