Slipping Control Algorithms for Object Manipulation with Sensorized Parallel Grippers

Parallel jaw grippers have a limited dexterity, however they can still be used for in-hand manipulation tasks, such as pivoting or other controlled sliding motions of the grasped object. A rotational sliding maneuver is challenging since the grasped object can easily slip if the grip force is not properly adjusted to allow rotational sliding while avoiding translational sliding at the same time. This paper has a twofold aim. First, it intends to refine control algorithms to avoid both rotational and linear slippage, already presented by the authors, by proposing a novel sliding motion model that leads to a grip force as small as possible to avoid slippage, so as to enlarge the set of fragile and deformable objects that can be safely grasped with this approach. Second, the paper exploits the motion model to set up a new algorithm for controlled rotational sliding, thus enabling challenging in-hand manipulation actions. All control algorithms are sensor-based, exploiting a sensorized gripper equipped with a six-axis force/tactile sensor, which provides contact force and torque measurements as well as orientation of the object with respect to the gripper. A set of experiments are executed on a Kuka iiwa showing how the proposed control algorithms are effective to both avoid slippage and allow a controlled sliding motion.