Tactile shape sensing via single- and multifingered hands

For mechanical hands, control of contact points is facilitated by fingertip force sensors which are capable of measuring the local surface normal of an unknown object. In addition to this information, joint angle sensors and knowledge of the kinematic parameters of the hand commonly provide the physical location of the surface contact point. This enables a surface recovery scheme to utilize both kinds of contact information. Here, a simple multifingered surface-exploration procedure is proposed which allows surface data to be obtained from a kinematic simulation. Using a linear formulation of the surface normal data, the shape estimator can be a simple sequential least-squares routine or the more versatile Kalman filter. Estimator performance is then evaluated for hands with no more than five fingers, with and without the surface normal data. >