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Picking Towels in Point Clouds.

Xiaoman Wang1, Xin Jiang2, Jie Zhao3

  • 1Mechanical Engineering and Automation, Harbin Institute of Technology, Shenzhen 518055, China. 16b953039@stu.hit.edu.cn.

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This study introduces a novel method for robotic grasping of towels, even when entangled or similarly colored. The algorithm achieves an 80% success rate in automated textile handling tasks.

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Area of Science:

  • Robotics
  • Computer Vision
  • Textile Automation

Background:

  • Automated picking of laundry items, especially those with similar visual characteristics or entanglement, presents a significant challenge in textile industry automation.
  • Existing methods often require item segmentation or distinct visual features, limiting their applicability.

Purpose of the Study:

  • To develop a robust grasp pose determination method for picking towels in automated systems.
  • To overcome limitations of current methods by not requiring item segmentation or color distinction.

Main Methods:

  • The proposed algorithm segments 3D point clouds into convex wrinkles.
  • It then identifies optimal grasp points and plans grasp orientation relative to these wrinkles.
  • This approach avoids the need for individual towel segmentation or color differentiation.

Main Results:

  • The method was evaluated on picking white and square towels.
  • An average success rate of approximately 80% was achieved.
  • The wrinkle-based grasp orientation planning significantly reduced grasp failures.

Conclusions:

  • The developed grasp pose determination method offers an effective solution for automated towel picking.
  • The approach demonstrates robustness in handling challenging conditions like entanglement and similar colors.
  • This contributes to advancing automation in the laundry and textile industries.