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Perception of Entangled Tubes for Automated Bin Picking

  • Gonçalo LeãoEmail author
  • Carlos M. Costa
  • Armando Sousa
  • Germano Veiga
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1092)

Abstract

Bin picking is a challenging problem common to many industries, whose automation will lead to great economic benefits. This paper presents a method for estimating the pose of a set of randomly arranged bent tubes, highly subject to occlusions and entanglement. The approach involves using a depth sensor to obtain a point cloud of the bin. The algorithm begins by filtering the point cloud to remove noise and segmenting it using the surface normals. Tube sections are then modeled as cylinders that are fitted into each segment using RANSAC. Finally, the sections are combined into complete tubes by adopting a greedy heuristic based on the distance between their endpoints. Experimental results with a dataset created with a Zivid sensor show that this method is able to provide estimates with high accuracy for bins with up to ten tubes. Therefore, this solution has the potential of being integrated into fully automated bin picking systems.

Keywords

Bin picking Industrial robots Linear objects Pose estimation Robot vision 

Notes

Acknowledgments

The research leading to these results has received funding from the European Union’s Horizon 2020 - The EU Framework Programme for Research and Innovation 2014–2020, under grant agreement No. 723658.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Gonçalo Leão
    • 1
    Email author
  • Carlos M. Costa
    • 1
    • 2
  • Armando Sousa
    • 1
    • 2
  • Germano Veiga
    • 1
    • 2
  1. 1.FEUP - Faculty of EngineeringUniversity of PortoPortoPortugal
  2. 2.INESC TEC - INESC Technology and SciencePortoPortugal

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