More Like this

1. Multi-segment soft robotic fingers enable robust precision grasping

   https://doi.org/10.1177/0278364920910465  

   Teeple, Clark B. ; Koutros, Theodore N. ; Graule, Moritz A. ; Wood, Robert J. ( March 2020 , The International Journal of Robotics Research)

   In this work, we discuss the design of soft robotic fingers for robust precision grasping. Through a conceptual analysis of the finger shape and compliance during grasping, we confirm that antipodal grasps are more stable when contact with the object occurs on the side of the fingers (i.e., pinch grasps) instead of the fingertips. In addition, we show that achieving such pinch grasps with soft fingers for a wide variety of objects requires at least two independent bending segments each, but only requires actuation in the proximal segment. Using a physical prototype hand, we evaluate the improvement in pinch-grasping performancemore »of this two-segment proximally actuated finger design compared to more typical, uniformly actuated fingers. Through an exploration of the relative lengths of the two finger segments, we show the tradeoff between power grasping strength and precision grasping capabilities for fingers with passive distal segments. We characterize grasping on the basis of the acquisition region, object sizes, rotational stability, and robustness to external forces. Based on these metrics, we confirm that higher-quality precision grasping is achieved through pinch grasping via fingers with the proximally actuated finger design compared to uniformly actuated fingers. However, power grasping is still best performed with uniformly actuated fingers. Accordingly, soft continuum fingers should be designed to have at least two independently actuated serial segments, since such fingers can maximize grasping performance during both power and precision grasps through controlled adaptation between uniform and proximally actuated finger structures.

   « less
2. A Novel Variable Stiffness Compliant Robotic Gripper Based on Layer Jamming

   https://doi.org/10.1115/1.4047156  

   Gao, Yuan ; Huang, Xiguang ; Mann, Ishan Singh ; Su, Hai-Jun ( October 2020 , Journal of Mechanisms and Robotics)

   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 thinmore »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 a 30-fold increase in gripper’s load capacity.« less
3. A Vacuum-driven Origami “Magic-ball” Soft Gripper

   Shuguang Li, John J. ( April 2019 , International Conference on Robotics and Automation (ICRA))

   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
4. A Low-Cost Compliant Gripper Using Cooperative Mini-Delta Robots for Dexterous Manipulation

   Mannam, P. ; Rudich, A. ; Zhang, Kevin L. ; Veloso, M. ; Kroemer, O. ; Temel, Z. ( July 2021 , Robotics science and systems)

   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
5. Fit2Form: 3D Generative Model for Robot Gripper Form Design

   Ha, Huy ; Agrawal, Shubham ; Song, Shuran ( November 2020 , Proceedings of the 2020 Conference on Robot Learning)

   The 3D shape of a robot’s end-effector plays a critical role in determining it’s functionality and overall performance. Many of today’s industrial applications rely on highly customized gripper design for a given task to ensure the system’s robustness and accuracy. However, the process of manual hardware design is both costly and time-consuming, and the quality of the design is also dependent on the engineer’s experience and domain expertise, which can easily be out-dated or inaccurate. The goal of this paper is to use machine learning algorithms to automate this design process and generate task-specific gripper designs that satisfy a setmore »of pre-defined design objectives. We model the design objectives by training a Fitness network to predict their values for a pair of gripper fingers and a grasp object. This Fitness network is then used to provide training supervision to a 3D Generative network that produces a pair of 3D finger geometries for the target grasp object. Our experiments demonstrate that the proposed 3D generative design framework generates parallel jaw gripper finger shapes that achieve more stable and robust grasps as compared to other general-purpose and task-specific gripper design algorithms.« less