  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.
