  This extended abstract provides a short introduction on our recently
developed perception-based controller for quadrupedal locomotion. Compared to
our previous approach based on Visual Foothold Adaptation (VFA) and Model
Predictive Control (MPC), our new framework combines a fast approximation of
the safe foothold regions based on Neural Network regression, followed by a
convex decomposition routine in order to generate safe landing areas where the
controller can freely optimize the footholds location. The aforementioned
framework, which combines prediction, convex decomposition, and MPC solution,
is tested in simulation on our 140kg hydraulic quadruped robot (HyQReal).
