Towards autonomous soft grasping of deformable objects using flexible thin-film electro-adhesive gripper and online capacitance measure

Grasping fragile or deformable objects is a more complex task with respect to the traditional pick and place of solid objects. In such cases, a retention action is typically preferred over a compression force in order to avoid damaging the objects. The proposed work presents a robotic manipulation grasping system that leverages a gripper realized with the flexible thin-film electro-adhesive (EA) devices technology and a vision pipeline based on an RGB-D camera to detect the grasp pose configuration and track the target during the holding phase to check whether the task has been successfully completed. Several tests have been done to assess the capabilities of the proposed robotic system, picking and placing deformable objects, comparing the EA gripper with a traditional parallel jaw gripper. Furthermore, a self-sensing circuit capacitance has been developed for measuring the variation of the capacitance between electrodes of an EA device during the adhesion providing useful information to automatically detect the successful grip of an object and the possible loss of adhesion during manipulation