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arXiv · 2410.06790

Discrete time model predictive control for humanoid walking with step adjustment

Vishnu Joshi·Suraj Kumar·Nithin V·Shishir Kolathaya
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Abstract

This paper presents a Discrete-Time Model Predictive Controller (MPC) for humanoid walking with online footstep adjustment. The proposed controller utilizes a hierarchical control approach. The high-level controller uses a low-dimensional Linear Inverted Pendulum Model (LIPM) to determine desired foot placement and Center of Mass (CoM) motion, to prevent falls while maintaining the desired velocity. A Task Space Controller (TSC) then tracks the desired motion obtained from the high-level controller, exploiting the whole-body dynamics of the humanoid. Our approach differs from existing MPC methods for walking pattern generation by not relying on a predefined foot-plan or a reference center of pressure (CoP) trajectory. The overall approach is tested in simulation on a torque-controlled Humanoid Robot. Results show that proposed control approach generates stable walking and prevents fall against push disturbances.

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Vishnu Joshi, Suraj Kumar, Nithin V, Shishir Kolathaya. 2024-10-09. Discrete time model predictive control for humanoid walking with step adjustment. https://arxiv.org/abs/2410.06790

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