Tactile data modeling and interpretation for stable grasping and manipulation

This paper is devoted to present the latest results on the exploitation of the force/tactile sensor developed by the authors in terms of modeling and interpretation of the data provided by the device. An analytical nonlinear model of the elastically deformable sensor is derived and validated, which allows to reconstruct the position and orientation of the surface in contact with a rigid object on the basis of the sensor signals. The reconstruction is performed via an Extended Kalman Filter able to counteract the measurement noise and to handle the nonlinearity of the model at the same time. The contact plane position and orientation information together with the contact force vector measured by the sensor are used to estimate the physical parameter most relevant to manipulation control purposes: the friction coefficient. A slippage control algorithm is presented which exploits the estimated friction and a novel slipping detection algorithm is proposed to cope with the unavoidable uncertainties of the real world and its effectiveness is experimentally proved in comparison with the existing techniques.