Soft fingertips have shown significant adaptability for grasping a wide range of object shapes thanks to elasticity. This ability can be enhanced to grasp soft, delicate objects by adding touch sensing. However, in these cases, the complete restraint and robustness of the grasps have proved to be challenging, as the exertion of additional forces on the fragile object can result in damage. This paper presents a novel soft fingertip design for delicate objects based on the concept of embedded air cavities, which allow the dual ability of tactile sensing and active shapechanging. The pressurized air cavities act as soft tactile sensors to control gripper position from internal pressure variation; and active fingertip deformation is achieved by applying positive pressure to these cavities, which then enable a delicate object to be kept securely in position, despite externally applied forces, by form closure. We demonstrate this improved grasping capability by comparing the displacement of grasped delicate objects exposed to high-speed motions. Results show that passive soft fingertips fail to restrain fragile objects at accelerations as low as 0.1 m/s 2 , in contrast, with the proposed fingertips delicate objects are completely secure even at accelerations of more than 5 m/s 2 .
Contact models for soft fingertips are able to precisely compute deformation when information about contact forces and object position is known, thus improving the traditional soft finger contact model. However, the functionality of these approaches for the study of in-hand manipulation with robot hands has been shown to be limited, since the location of the manipulated object is uncertain due to compliance and closed-loop constraints. This paper presents a novel, tractable approach for contact modelling of soft fingertips in within-hand dexterous manipulation settings. The proposed method is based on a relaxation of the kinematic equivalent of point contact with friction, modelling the interaction between fingertips and objects as joints with clearances rather than ideal instances, and then approximating clearances via affine arithmetic to facilitate computation. These ideas are introduced using planar manipulation to aid discussion, and are used to predict the reachable workspace of a two-fingered robot hand with fingertips of different hardness and geometry. Numerical and empirical experiments are conducted to analyse the effects of soft fingertips on manipulation operability; results demonstrate the functionality of the proposed approach, as well as a tradeoff between hardness and depth in soft fingertips to achieve better manipulation performance of dexterous robot hands.
While the grasping capability of robotic grippers has shown significant development, the ability to manipulate objects within the hand is still limited. One explanation for this limitation is the lack of controlled contact variation between the grasped object and the gripper. For instance, human hands have the ability to firmly grip object surfaces, as well as slide over object faces, an aspect that aids the enhanced manipulation of objects within the hand without losing contact. In this letter, we present a parametric, origami-inspired thin surface capable of transitioning between a high friction and a low friction state, suitable for implementation as an epidermis in robotic fingers. A numerical analysis of the proposed surface based on its design parameters, force analysis, and performance in in-hand manipulation tasks is presented. Through the development of a simple two-fingered two-degree-of-freedom gripper utilizing the proposed variablefriction surfaces with different parameters, we experimentally demonstrate the improved manipulation capabilities of the hand when compared to the same gripper without changeable friction. Results show that the pattern density and valley gap are the main parameters that effect the in-hand manipulation performance. The origami-inspired thin surface with a higher pattern density generated a smaller valley gap and smaller height change, producing a more stable improvement of the manipulation capabilities of the hand.
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