How far and how hard: tactile feedback for robotic manipulators

Manipulators based on rigid, kinematically constrained structures and highly geared electromagnetic actuators are poorly suited in applications where objects are soft, delicate, or have an irregular shape, especially if they operate outside of the highly structured environment of a factory. Intrinsically soft DEA, imparted with the ability to self-sense enable the creation of soft, smart artificial muscles provide a way forward. Inherent compliance simplifies manipulator trajectory planning and force control, enables the manipulator to conform to the object, and provides natural damping of mechanical disturbances. In this paper we present a simple proof-of-concept building block that could be used to create a compliant DEA-based manipulator with self-sensing feedback. Capacitive self-sensing has been used to both detect when contact is made with an object and gather information about the object's stiffness. Integrated into a manipulator, this information could be used to adjust the grip directly, or used to reposition or reorient the manipulator to achieve a desired grasp.