Robotics (May 2024)

Automated Grasp Planning and Finger Design Space Search Using Multiple Grasp Quality Measures

  • Roshan Kumar Hota,
  • Gaoyuan Liu,
  • Bieke Decraemer,
  • Barry Swevels,
  • Sofie Burggraeve,
  • Tom Verstraten,
  • Bram Vanderborght,
  • Greet Van de Perre

DOI
https://doi.org/10.3390/robotics13050074
Journal volume & issue
Vol. 13, no. 5
p. 74

Abstract

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As the industry shifts to automated manufacturing and the assembly of parts in smaller batches, there is a clear need for an efficient design of grippers. This paper presents a method for automated grasp planning and finger design for multiple parts using four grasp quality measures that capture the following important requirements for grasping: (i) uniform contact force distribution; (ii) better gravity wrench resistance; (iii) robustness against gripper positioning error; and (iv) ability to resist larger external wrench on the object. We introduce the fingertip score to quantify the grasp performance of a fingertip design over all the objects. The method takes the CAD model of the objects as the input and outputs the optimal grasp location and the best finger design. We use the method for a three-point grasp with a parallel jaw gripper. We validate our method on two sets of objects. Results show how each grasp quality measure behaves on different objects and the variation in the fingertip score with finger design. Finally, we test the effectiveness of the optimal finger design experimentally. The three-point grasp is suitable for grasping objects larger than is possible with shape-matching fingertips.

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