Vision based control for Humanoid robots

International audienceThis paper presents a visual servoing scheme to control humanoid dynamic walk. Whereas most of the existing approaches follow a perception-decision-action scheme, we hereby introduce a method that uses the on-line information given by an on-board camera. This close looped approach allows the system to react to changes in its environment and adapt to modelling error. Our approach is based on a new reactive pattern generator which modifies footsteps, center of mass and center of pressure trajectories at the control level for the center of mass to track a reference velocity. In this workshop, we present three ways of servoing dynamical humanoid walk : a naive one that compute a reference velocity using a visual servoing control law, a second one that takes into account the sway motion induced by the walk and an on going work on vision predictive control that directly introduces the visual error in the cost function of the pattern generator. The two first approaches have been validated on the HRP-2 robot. These close loop approaches give a more accurate positioning than the one obtained when executing a planned trajectory especially when rotational motion are involved