Publication
Right Model, Right Time: Real-Time Cascaded-Fidelity MPC for Bipedal Walking
Franek Stark; Felix Wiebe; Shubham Vyas; Dennis Mronga; Frank Kirchner
In: ICRA Workshop on Frontiers of Optimization for Robotics, 2nd Edition. Workshop on Frontiers of Optimization for Robotics, June 1, Vienna, Austria, IEEE, 2026.
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.
Projects
- CoEx - Entwicklung von Methoden zur Co-Adaptation für die Ermöglichung und Verbesserung von Exoskelett-basiertee (Tele-) Rehabilitation
- ActGPT - Adaptive robot ConTrol with Generative Pre-trained Transformers
