# A Predictive Momentum-Based Whole-Body Torque Controller: Theory and Simulations for the iCub Stepping

## TL;DR

This paper introduces a model predictive control strategy for humanoid robots that predicts future states to determine contact forces, enhancing balance recovery during disturbances like pushes.

## Contribution

It presents a novel predictive momentum-based torque controller that incorporates contact switching for improved balance recovery in humanoid robots.

## Key findings

- High robustness in simulation for stepping recovery
- Effective handling of external disturbances
- Seamless contact switching in control strategy

## Abstract

When balancing, a humanoid robot can be easily subjected to unexpected disturbances like external pushes. In these circumstances, reactive movements as steps become a necessary requirement in order to avoid potentially harmful falling states. In this paper we conceive a Model Predictive Controller which determines a desired set of contact wrenches by predicting the future evolution of the robot, while taking into account constraints switching in case of steps. The control inputs computed by this strategy, namely the desired contact wrenches, are directly obtained on the robot through a modification of the momentum-based whole-body torque controller currently implemented on iCub. The proposed approach is validated through simulations in a stepping scenario, revealing high robustness and reliability when executing a recovery strategy.