3D Pose Estimation of Bin Picking Object using Deep Learning and 3D Matching
Junesuk Lee, Sangseung Kang, Soon-Yong Park
2018
Abstract
In this paper, we propose a method to estimate 3D pose information of an object in a randomly piled-up environment by using image data obtained from an RGB-D camera. The proposed method consists of two modules: object detection by deep learning, and pose estimation by Iterative Closest Point (ICP) algorithm. In the first module, we propose an image encoding method to generate three channel images by integrating depth and infrared images captured by the camera. We use these encoded images as both the input data and training data set in a deep learning-based object detection step. Also, we propose a depth-based filtering method to improve the precision of object detection and to reduce the number of false positives by preprocessing input data. ICP-based 3D pose estimation is done in the second module, where we applied a plane-fitting method to increase the accuracy of the estimated pose.
DownloadPaper Citation
in Harvard Style
Lee J., Kang S. and Park S. (2018). 3D Pose Estimation of Bin Picking Object using Deep Learning and 3D Matching.In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-321-6, pages 318-324. DOI: 10.5220/0006858203180324
in Bibtex Style
@conference{icinco18,
author={Junesuk Lee and Sangseung Kang and Soon-Yong Park},
title={3D Pose Estimation of Bin Picking Object using Deep Learning and 3D Matching},
booktitle={Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2018},
pages={318-324},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006858203180324},
isbn={978-989-758-321-6},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - 3D Pose Estimation of Bin Picking Object using Deep Learning and 3D Matching
SN - 978-989-758-321-6
AU - Lee J.
AU - Kang S.
AU - Park S.
PY - 2018
SP - 318
EP - 324
DO - 10.5220/0006858203180324