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Efficient leather spreading operations by dual-arm robotic systems.

Yuan Huan1, Gongchang Ren2, Jiangong Sun1

  • 1College of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xi'an, China.

Scientific Reports
|July 14, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new robotic method for grasping and spreading irregular soft materials like leather. The technique uses improved object recognition and specific grasping strategies, achieving a 72% success rate in experiments.

Keywords:
Grasping and unfolding techniquesGrasping posture optimizationNon-uniform and sheet-like soft objectsOptimal grasping pointsYOLOV8 improvement

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Area of Science:

  • Robotics
  • Computer Vision
  • Materials Science

Background:

  • Robotic manipulation of soft, irregular objects like leather presents challenges due to edge irregularities and ambiguous feature points.
  • Existing methods struggle with precise grasping and spreading of deformable materials.

Purpose of the Study:

  • To develop an innovative robotic method for precise grasping and spreading of irregular sheet-like soft objects, specifically leather.
  • To enhance object recognition for grasping key points on irregular surfaces.

Main Methods:

  • An improved YOLOV8 algorithm incorporating BIFPN and WIOU loss was developed for high-precision recognition of grasping points.
  • A novel grasping strategy involving alternate lowest point grasping and planar techniques was implemented.
  • An experimental platform was constructed to test the proposed method.

Main Results:

  • The developed method achieved a 72% success rate in grasping and spreading leather in experimental trials.
  • High-precision recognition of lowest grasping points and planar grasping points was demonstrated.
  • Analysis of failed experiments provided insights into current limitations.

Conclusions:

  • The proposed method offers a viable solution for robotic manipulation of irregular soft materials.
  • Further research can build upon the identified limitations to improve future robotic grasping systems.