Estimation of Robot Motion Parameters Based on Functional Consistency for Randomly Stacked Parts

Takahiro Suzuki, Manabu Hashimoto

2023

Abstract

In this paper, we propose a method for estimating robot motion parameters necessary for robots to automatically assemble objects. Generally, parts used in assembly are often randomly stacked. The proposed method estimates the robot motion parameters from this state. Each part has a role referred to as a “function” such as “to be grasped” or “to be assembled with other parts” for each region. Related works have defined functions for everyday objects, but in this paper, we defined a novel functional label for industrial parts. In addition, we proposed novel ideas which is the functional consistency of part. Functional consistency refers to the constraints that functional labels have. Functional consistency is used in adapting to various bin scene because it is invariant no matter what state the parts are placed in. Functional consistency is used in the proposed method as a cue, robot motion parameters are estimated on the basis of relationship between parameters and functions. In an experiment using connecting rods, the average success rate was 81.5%. The effectiveness of the proposed method was confirmed from the ablation studies and comparison with related work.

Paper Citation

in Harvard Style

Suzuki T. and Hashimoto M. (2023). Estimation of Robot Motion Parameters Based on Functional Consistency for Randomly Stacked Parts. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 519-528. DOI: 10.5220/0011683500003417

in Bibtex Style

@conference{visapp23,
author={Takahiro Suzuki and Manabu Hashimoto},
title={Estimation of Robot Motion Parameters Based on Functional Consistency for Randomly Stacked Parts},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={519-528},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011683500003417},
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 4: VISAPP
TI - Estimation of Robot Motion Parameters Based on Functional Consistency for Randomly Stacked Parts
SN - 978-989-758-634-7
AU - Suzuki T.
AU - Hashimoto M.
PY - 2023
SP - 519
EP - 528
DO - 10.5220/0011683500003417
PB - SciTePress