Surface-Graph-Based 6DoF Object-Pose Estimation for Shrink-Wrapped Items Applicable to Mixed Depalletizing Robots

Taiki Yano, Nobutaka Kimura, Kiyoto Ito

2023

Abstract

We developed an object-recognition method that enables six degrees of freedom (6DoF) pose and size estimation of shrink-wrapped items for use with a mixed depalletizing robot. Shrink-wrapped items consist of multiple products wrapped in transparent plastic wrap, the boundaries of which are unclear, making it difficult to identify the area of a single item to be picked. To solve this problem, we propose a surface-graph-based 6DoF object-pose estimation method. This method constructs a surface graph representing the connection of products by using their surfaces as graph nodes and determines the boundary of each shrink-wrapped item by detecting the homogeneity of the edge length, which corresponds to the distance between the centers of the products. We also developed a recognition-process flow that can be applied to various objects by appropriately switching between conventional box-shape object recognition and shrink-wrapped object recognition. We conducted an experiment to evaluation the proposed method, and the results indicate that the proposed method can achieve an average recognition rate of more than 90%, which is higher than that with a conventional object-recognition method in a depalletizing work environment that includes shrink-wrapped items.

Paper Citation

in Harvard Style

Yano T., Kimura N. and Ito K. (2023). Surface-Graph-Based 6DoF Object-Pose Estimation for Shrink-Wrapped Items Applicable to Mixed Depalletizing Robots. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 503-511. DOI: 10.5220/0011635000003417

in Bibtex Style

@conference{visapp23,
author={Taiki Yano and Nobutaka Kimura and Kiyoto Ito},
title={Surface-Graph-Based 6DoF Object-Pose Estimation for Shrink-Wrapped Items Applicable to Mixed Depalletizing Robots},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP},
year={2023},
pages={503-511},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011635000003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP
TI - Surface-Graph-Based 6DoF Object-Pose Estimation for Shrink-Wrapped Items Applicable to Mixed Depalletizing Robots
SN - 978-989-758-634-7
AU - Yano T.
AU - Kimura N.
AU - Ito K.
PY - 2023
SP - 503
EP - 511
DO - 10.5220/0011635000003417
PB - SciTePress