Adaptive tactile control for in-hand manipulation tasks of deformable objects

Abstract

Tactile sensors are key components for a robot hand system, which are usually used to obtain the object’s features. The use of tactile sensors to obtain information from the objects is an open topic of research. In this paper, a new strategy for in-hand extraction of object’s properties and for control of the interaction forces with robot fingers, mainly based on tactile data, is presented. The scope of this strategy is to grasp and manipulate solid objects, including rigid and soft bodies. Assuming that the hand is in an initial configuration in which the object is grasped, the properties’ extraction approach is executed. After the extraction of properties is finished, the object can be classified in regard to a general body listing: rigid body, soft elastic body, or soft plastic object. Once the object is classified, for in-hand manipulation tasks, the contact points between the object grasped and the fingers are maintained using the information given by the tactile sensors in order to perform manipulation tasks. Each task is defined by a sequence of basic actions, in which the contact points and applied forces are adapted depending on the action to be performed and the estimated features for the object. The presented approach tries to imitate the behavior of human beings, in which the applied forces by the fingers are changed when the human estimates the rigidity of a body and when the fingers react to unexpected movements of the object to keep the contact points.