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arXiv · 2605.04607

Right Model, Right Time: Real-Time Cascaded-Fidelity MPC for Bipedal Walking

Franek Stark·Felix Wiebe·Shubham Vyas·Dennis Mronga·Frank Kirchner
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Abstract

This paper presents a multi-phase whole-body model predictive control (MPC) approach for bipedal walking, combining a detailed whole-body model in the near horizon with a simplified single-rigid-body model in the later prediction steps. This reduces computational complexity while retaining prediction capabilities. The resulting nonlinear optimal control problem is solved entirely within the general-purpose, off-the-shelf nonlinear MPC framework acados, using sequential quadratic programming (SQP). Given a contact schedule and a target walking speed, the controller optimizes joint torques without depending on preselected footstep locations. The controller is validated in MuJoCo simulation on the 18-DoF bipedal robot HyPer-2.

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Franek Stark, Felix Wiebe, Shubham Vyas, Dennis Mronga, Frank Kirchner. 2026-05-06. Right Model, Right Time: Real-Time Cascaded-Fidelity MPC for Bipedal Walking. https://arxiv.org/abs/2605.04607

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