skip to main content

Title: A Novel Variable Stiffness Compliant Robotic Gripper Based on Layer Jamming
Abstract In this paper, we present a novel compliant robotic gripper with three variable stiffness fingers. While the shape morphing of the fingers is cable-driven, the stiffness variation is enabled by layer jamming. The inherent flexibility makes compliant gripper suitable for tasks such as grasping soft and irregular objects. However, their relatively low load capacity due to intrinsic compliance limits their applications. Variable stiffness robotic grippers have the potential to address this challenge as their stiffness can be tuned on demand of tasks. In our design, the compliant backbone of finger is made of 3D-printed PLA materials sandwiched between thin film materials. The workflow of the robotic gripper follows two basic steps. First, the compliant skeleton is driven by a servo motor via a tension cable and bend to a desired shape. Second, upon application of a negative pressure, the finger is stiffened up because friction between contact surfaces of layers that prevents their relative movement increases. As a result, their load capacity will be increased proportionally. Tests for stiffness of individual finger and load capacity of the robotic gripper are conducted to validate capability of the design. The results showed a 180-fold increase in stiffness of individual finger and more » a 30-fold increase in gripper’s load capacity. « less
; ; ;
Award ID(s):
Publication Date:
Journal Name:
Journal of Mechanisms and Robotics
Sponsoring Org:
National Science Foundation
More Like this
  1. Compliant grasping is crucial for secure handling objects not only vary in shapes but also in mechanical properties. We propose a novel soft robotic gripper with decoupled stiffness and shape control capability for performing adaptive grasping with minimum system complexity. The proposed soft fingers conform to object shapes facilitating the handling of objects of different types, shapes, and sizes. Each soft gripper finger has a length constraining mechanism (an articulable rigid backbone) and is powered by pneumatic muscle actuators. We derive the kinematic model of the gripper and use an empirical approach to simultaneously map input pressures to stiffness controlmore »and bending deformation of fingers. We use these mappings to demonstrate decoupled stiffness and shape (bending) control of various grasping configurations. We conduct tests to quantify the grip quality when holding objects as the gripper changes orientation, the ability to maintain the grip as the gripper is subjected to translational and rotational movements, and the external force perturbations required to release the object from the gripper under various stiffness and shape (bending) settings. The results validate the proposed gripper’s performance and show how the decoupled stiffness and shape control can improve the grasping quality in soft robotic grippers.« less
  2. Traditional parallel-jaw grippers are insufficient for delicate object manipulation due to their stiffness and lack of dexterity. Other dexterous robotic hands often have bulky fingers, rely on complex time-varying cable drives, or are prohibitively expensive. In this paper, we introduce a novel low-cost compliant gripper with two centimeter-scaled 3-DOF delta robots using off-the-shelf linear actuators and 3D-printed soft materials. To model the kinematics of delta robots with soft compliant links, which diverge from typical rigid links, we train neural networks using a perception system. Furthermore, we analyze the delta robot’s force profile by varying the starting position in its workspacemore »and measuring the resulting force from a push action. Finally, we demonstrate the compliance and dexterity of our gripper through six dexterous manipulation tasks involving small and delicate objects. Thus, we present the groundwork for creating modular multi-fingered hands that can execute precise and low-inertia manipulations.« less
  3. Individual differences in tactile acuity are observed within and between age cohorts. Such differences in acuity may be attributed to various sources, including aspects of nervous system, skin mechanics, finger size, cognitive and behavioral factors, etc. This work considers individual differences, within a younger cohort of participants, in discriminating compliant surfaces. These participants exhibit a range of finger size and stiffness. Interestingly, both their finger size and stiffness well predict their discriminative performance, where softer/smaller fingers outperform stiffer/larger fingers. Stereo imaging captured biomechanical cues in the skin’s deformation, including contact area and penetration depth, and their change rates. In thosemore »individuals with stiffer/larger fingers, who perceptually performed worse, we observed less distinguishable contact areas and eccentricities, compared to softer/smaller fingers. These particular cues well predicted individual differences observed in perceptual discrimination. In comparison, with two other cues, curvature and penetration depth, the imaging readily distinguished the compliant surfaces irrespective of finger stiffness/size, not aligned with discrimination. In conclusion, in passive touch, we find that individuals with softer/smaller fingers were better at discriminating compliances, and that certain skin deformation cues predict individual differences in perception.« less
  4. Soft robotics has yielded numerous examples of soft grippers that utilize compliance to achieve impressive grasping performances with great simplicity, adaptability, and robustness. Designing soft grippers with substantial grasping strength while remaining compliant and gentle is one of the most important challenges in this field. In this paper, we present a light-weight, vacuum-driven soft robotic gripper made of an origami “magic-ball” and a flexible thin membrane. We also describe the design and fabrication method to rapidly manufacture the gripper with different combinations of low- cost materials for diverse applications. Grasping experiments demonstrate that our gripper can lift a large varietymore »of objects, including delicate foods, heavy bottles, and other miscellaneous items. The grasp force on 3D-printed objects is also characterized through mechanical load tests. The results reveal that our soft gripper can produce significant grasp force on various shapes using negative pneumatic pressure (vacuum). This new gripper holds the potential for many practical applications that require safe, strong, and simple grasping.« less
  5. Abstract Soft robotic grippers can gently grasp and maneuver objects. However, they are difficult to model and control due to their highly deformable fingers and complex integration with robotic systems. This paper investigates the design requirements as well as the grasping capabilities and performance of a soft gripper system based on fluidic prestressed composite (FPC) fingers. An analytical model is constructed as follows: each finger is modeled using the chained composite model (CCM); strain energy and work done by pressure and loads are computed using polynomials with unknown coefficients; net energy is minimized using the Rayleigh–Ritz method to calculate themore »deflected equilibrium shapes of the finger as a function of pressure and loads; and coordinate transformation and gripper geometries are combined to analyze the grasping performance. The effects of prestrain, integration angle, and finger overlap on the grasping performance are examined through a parametric study. We also analyze gripping performance for cuboidal and spherical objects and show how the grasping force can be controlled by varying fluidic pressure. The quasi-static responses of fabricated actuators are measured under pressures and loads. It is shown that the actuators’ modeled responses agree with the experimental results. This work provides a framework for the theoretical analysis of soft robotic grippers and the methods presented can be extended to model grippers with different types of actuation.« less