Inflatable Particle-Jammed Robotic Gripper Based on Integration of Positive Pressure and Partial Filling.

Journal: Soft robotics
Published Date:

Abstract

In this work, we proposed an inflatable particle-jamming gripper based on a novel grasping strategy of integrating the positive pressure and partial filling, in which the positive pressure increases the contact area between the gripper and objects, and the grain package in a partial-filled state provides significant grasping adaptation for the gripper. First, we design and fabricate the inflatable particle-jamming gripper and clarify its working mechanism. Then three kinds of grippers, including the proposed inflatable gripper, full-filled gripper, and partial-filled gripper, are experimentally compared for the capability of grasping objects of various sizes, and their performances from four metrics (compliance, reliability, grasping robustness, and lifting efficiency) are evaluated as well. Furthermore, a theoretical analysis is carried out for different grasping performances among the three kinds of grippers, in which the inflatable gripper performs a more promising grasping performance. In this article, by inflating the gripper to an ordered extent with positive pressure, the originally full-filled gripper turns into a partial-filled state. Based on the unique grasping strategy of the proposed gripper, it is possible to achieve a brilliant compliance and robust grasps. Even though the object is located 20 mm away from the gripper-center-axis, valid grasps are observed as well. It is concluded that the proposed gripper could potentially have a wide range of applications in the industry and daily activities.

Authors

  • Yanjie Wang
    Zhejiang Key Laboratory of Blood-Stasis-Toxin Syndrome, Zhejiang Chinese Medical University, Hangzhou, 310000, China.
  • Zhiwei Yang
  • Han Zhou
    Jiangsu Provincial Key Laboratory of Special Robot Technology, Hohai University, Changzhou, China.
  • Chun Zhao
    Jiangsu Provincial Key Laboratory of Special Robot Technology, Hohai University, Changzhou, China.
  • Benjamin Barimah
    Jiangsu Provincial Key Laboratory of Special Robot Technology, Hohai University, Changzhou, China.
  • Bo Li
    Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming, Yunnan, China.
  • Chaoqun Xiang
    SoftLab, Bristol Robotics Laboratory, University of Bristol, Bristol, United Kingdom.
  • Lijie Li
    College of Engineering, Swansea University, Bay Campus, Swansea SA1 8EN, UK. L.Li@swansea.ac.uk.
  • Xiaofan Gou
    Jiangsu Provincial Key Laboratory of Special Robot Technology, Hohai University, Changzhou, China.
  • Minzhou Luo
    Jiangsu Provincial Key Laboratory of Special Robot Technology, Hohai University, Changzhou, China.