Robust control of 6 DOF displacements reconstructed from a weakly calibrated camera

In this paper, we use sliding mode control theory to design a 3D vision based controller that is robust to bounded parametric estimation errors. First, we give a model of an eye-in-hand 6 DOF robotic system, including the Pose Reconstruction Algorithm (PRA) used to estimate the position and orientation of the camera with respcet to the scene. In a second step, we propose a model for the uncertainties that involves bounded parametric errors on the vision system. Thanks to an appropriate selection of the sliding surface, based on the quaternion representation for rotations, a switching controller, with a variable control gain, is then proposed. Six degrees of freedom vision based tracking experiments under weak calibration conditions emphasize the practical efficiency of the controller.