| Title: | OS12-2 Estimation of Image-Based End-Effector Approach Angles for Tomato Harvesting Robots |
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| Publication: | ICAROB2025 |
| Volume: | 30 |
| Pages: | 347-350 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2025.OS12-2 |
| Author(s): | Kizuna Yoshinaga, Hikaru Sato, Kazuo Ishii, Shinsuke Yasukawa |
| Publication Date: | February 13, 2025 |
| Keywords: | Image processing, Robot vision, Agricultural robot, Harvesting robot |
| Abstract: | We propose a method to estimate a suitable approach angle for the end-effector of a tomato harvesting robot based on image data. Agricultural harvesting robots often face obstacles such as other fruits or stems around the target crop. Additionally, it is important to approach the target from a direction appropriate for harvesting, considering the shape of the end-effector. The proposed method uses a deep learning-based instance segmentation model to extract regions of fruits and stems, and estimates the suitable approach angle based on their positional relationships. We demonstrated the usefulness of the proposed method using an image dataset acquired in an actual tomato greenhouse. |
| PDF File: | https://alife-robotics.co.jp/members2025/icarob/data/html/data/OS/OS12/OS12-2.pdf |
| Copyright: | © The authors. This article is distributed under the terms of the Creative Commons Attribution License 4.0, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited. See for details: https://creativecommons.org/licenses/by-nc/4.0/ |
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