| Title: | OS17-7 Grasp Point Estimation using Simulator-Generated Datasets Including Pose Information |
|---|---|
| Publication: | ICAROB2025 |
| Volume: | 30 |
| Pages: | 495-498 |
| ISSN: | 2188-7829 |
| DOI: | 10.5954/ICAROB.2025.OS17-7 |
| Author(s): | Ryoga Maruno, Tomoya Shiba, Naoki Yamaguchi, Hakaru Tamukoh |
| Publication Date: | February 13, 2025 |
| Keywords: | Object recognition, Pose estimation, Dataset generation, Grasp point |
| Abstract: | We develop a system that automatically generates training datasets for object recognition models using a simulator. In this study, we incorporate pose information into the dataset. Using this system, we develop a method for estimating grasp points for objects that are difficult for robots to grasp, selecting a toy airplane as the target object. Three specific points are assigned to the object: the front, center, and back. In the grasp point estimation process, the center point is designated as the grasp point. The robot's arm achieves an appropriate grasp by moving perpendicularly to the line connecting the front and back points toward this grasp point. |
| PDF File: | https://alife-robotics.co.jp/members2025/icarob/data/html/data/OS/OS17/OS17-7.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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