Robust grasping of everyday objects is still an open problem in robotics due to uncertainties affecting object physical properties like weight and friction. The present paper proposes to exploit the perception data provided by a tactile sensor to obtain useful information on the contact state, like normal and tangential components of the contact force. A novel mechanical model of the contact between the soft fingertip and the grasped object is here presented and supported by both FEM analysis and experimental verification. The proposed algorithm to extract such information from tactile raw data, based on this model, is simple enough to allow implementation of the grasp control strategy on the control hardware embedded into a standard robotic parallel gripper, so as to mimic human reactive grip responses, which occur when the control of an held object appears uncertain.
Modeling and Calibration of a Tactile Sensor for Robust Grasping
De Maria, G.;Natale, C.;Pirozzi, S.
2017
Abstract
Robust grasping of everyday objects is still an open problem in robotics due to uncertainties affecting object physical properties like weight and friction. The present paper proposes to exploit the perception data provided by a tactile sensor to obtain useful information on the contact state, like normal and tangential components of the contact force. A novel mechanical model of the contact between the soft fingertip and the grasped object is here presented and supported by both FEM analysis and experimental verification. The proposed algorithm to extract such information from tactile raw data, based on this model, is simple enough to allow implementation of the grasp control strategy on the control hardware embedded into a standard robotic parallel gripper, so as to mimic human reactive grip responses, which occur when the control of an held object appears uncertain.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
